{"pageNumber":"894","pageRowStart":"22325","pageSize":"25","recordCount":184904,"records":[{"id":70198127,"text":"70198127 - 2018 - Improving predictions of hydrological low-flow indices in ungaged basins using machine learning","interactions":[],"lastModifiedDate":"2018-07-17T09:55:03","indexId":"70198127","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Improving predictions of hydrological low-flow indices in ungaged basins using machine learning","docAbstract":"<p><span>We compare the ability of eight machine-learning</span><span><span><span><span>&nbsp;</span>models (elastic net, gradient boosting, kernel-k-nearest neighbors, two variants of<span> support vector machines</span>, M5-cubist, random forest, and a meta-learning ensemble M5-cubist model) and four baseline models (ordinary<span> kriging</span></span>, a unit area discharge model, and two variants of censored regression) to generate estimates of the annual minimum 7-day mean<span> streamflow</span></span><span>&nbsp;</span>with an annual exceedance probability of 90% (7Q10) at 224 unregulated sites in South Carolina, Georgia, and Alabama, USA. The machine-learning models produced substantially lower cross validation errors compared to the baseline models. The meta-learning M5-cubist model had the lowest root-mean-squared-error of 26.72 cubic feet per second. Partial dependence plots show that 7Q10s are likely moderated by late summer and early fall precipitation and the infiltration capacity of basin soils.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2017.12.021","usgsCitation":"Worland, S.C., Farmer, W.H., and Kiang, J.E., 2018, Improving predictions of hydrological low-flow indices in ungaged basins using machine learning: Environmental Modelling and Software, v. 101, p. 169-182, https://doi.org/10.1016/j.envsoft.2017.12.021.","productDescription":"14 p.","startPage":"169","endPage":"182","ipdsId":"IP-080308","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":468958,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2017.12.021","text":"Publisher Index Page"},{"id":437995,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5S4T","text":"USGS data release","linkHelpText":"7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015)"},{"id":355718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, South Carolina","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.984916,35.005881],[-85.466713,34.982972],[-83.619985,34.986592],[-83.620185,34.992091],[-83.108714,35.000768],[-82.787867,35.085024],[-82.776357,35.081349],[-82.781973,35.066817],[-82.757704,35.068019],[-82.728961,35.091978],[-82.694898,35.098456],[-82.68604,35.124545],[-82.662381,35.118123],[-82.642237,35.129215],[-82.629031,35.126155],[-82.547436,35.160306],[-82.52593,35.156749],[-82.476136,35.175486],[-82.460092,35.178143],[-82.448969,35.165037],[-82.439595,35.165863],[-82.419744,35.198613],[-82.390439,35.215395],[-82.371298,35.181449],[-82.361469,35.190831],[-82.326917,35.185056],[-82.27492,35.200071],[-81.043625,35.149877],[-81.051204,35.133237],[-81.038968,35.126299],[-81.032806,35.108049],[-81.052078,35.096276],[-81.058029,35.07319],[-81.041489,35.044703],[-80.93495,35.107409],[-80.782042,34.935782],[-80.796997,34.823874],[-79.675299,34.804744],[-78.541087,33.851112],[-78.584841,33.844282],[-78.714116,33.800138],[-78.812931,33.743472],[-78.938076,33.639826],[-79.028516,33.533365],[-79.084588,33.483669],[-79.135441,33.403867],[-79.180318,33.254141],[-79.172394,33.206577],[-79.18787,33.173712],[-79.24609,33.124865],[-79.329909,33.089986],[-79.359961,33.006672],[-79.403712,33.003903],[-79.423447,33.015085],[-79.483499,33.001265],[-79.506923,33.032813],[-79.522449,33.03535],[-79.55756,33.021269],[-79.580725,33.006447],[-79.617611,32.952726],[-79.606194,32.925953],[-79.574951,32.934526],[-79.576006,32.906235],[-79.631149,32.888606],[-79.695141,32.850398],[-79.719879,32.825796],[-79.716761,32.813627],[-79.726389,32.805996],[-79.811021,32.77696],[-79.84035,32.756816],[-79.866742,32.757422],[-79.870336,32.727777],[-79.888028,32.695177],[-79.884961,32.684402],[-79.975248,32.639537],[-79.999374,32.611851],[-80.121368,32.590523],[-80.148406,32.578479],[-80.171764,32.546118],[-80.20523,32.555547],[-80.332438,32.478104],[-80.363956,32.496098],[-80.413487,32.470672],[-80.423454,32.497989],[-80.439407,32.503472],[-80.472068,32.496964],[-80.484617,32.460976],[-80.480156,32.447048],[-80.467588,32.425259],[-80.446075,32.423721],[-80.429941,32.401782],[-80.455192,32.326458],[-80.545688,32.282076],[-80.596394,32.273549],[-80.658634,32.248638],[-80.669166,32.216783],[-80.721463,32.160427],[-80.812503,32.109746],[-80.844431,32.109709],[-80.858735,32.099581],[-80.905378,32.051943],[-80.885517,32.0346],[-80.84313,32.024226],[-80.841913,32.002643],[-80.862814,31.969346],[-80.911207,31.943769],[-80.929101,31.944964],[-80.930279,31.956705],[-80.948491,31.95723],[-80.972392,31.94127],[-80.975714,31.923602],[-80.968494,31.915822],[-80.934508,31.90918],[-80.99269,31.857641],[-81.065255,31.877095],[-81.05907,31.850106],[-81.075812,31.829031],[-81.039808,31.823],[-81.036873,31.812721],[-81.068116,31.768735],[-81.130634,31.722692],[-81.192784,31.733245],[-81.203572,31.719448],[-81.161084,31.691401],[-81.149369,31.699304],[-81.131137,31.695774],[-81.133493,31.623348],[-81.173079,31.555908],[-81.186114,31.568032],[-81.204315,31.568183],[-81.214536,31.557601],[-81.254218,31.55594],[-81.260076,31.54828],[-81.258809,31.52906],[-81.217948,31.527284],[-81.199518,31.537596],[-81.17831,31.52241],[-81.278798,31.367214],[-81.282923,31.326491],[-81.25482,31.315452],[-81.274688,31.289454],[-81.288403,31.211065],[-81.314183,31.207938],[-81.339028,31.186918],[-81.368241,31.136534],[-81.399677,31.134113],[-81.401267,31.072781],[-81.420474,31.016703],[-81.451444,31.015515],[-81.493651,30.977528],[-81.475789,30.965976],[-81.453568,30.965573],[-81.447388,30.956732],[-81.426929,30.956615],[-81.420108,30.974076],[-81.408484,30.977718],[-81.403409,30.957914],[-81.405153,30.908203],[-81.460061,30.769912],[-81.45947,30.741979],[-81.444124,30.709714],[-81.472597,30.713312],[-81.489537,30.7261],[-81.528278,30.723359],[-81.544679,30.713969],[-81.601206,30.728141],[-81.617663,30.722046],[-81.625098,30.733017],[-81.646137,30.727591],[-81.662173,30.746521],[-81.672824,30.738935],[-81.692815,30.7471],[-81.719927,30.744634],[-81.745035,30.765039],[-81.768192,30.773954],[-81.779171,30.768062],[-81.806652,30.789683],[-81.868608,30.792754],[-81.89572,30.821098],[-81.910926,30.815889],[-81.949787,30.827493],[-81.959759,30.821168],[-81.961989,30.800443],[-81.979061,30.776415],[-82.017051,30.791657],[-82.022866,30.787991],[-82.011597,30.763122],[-82.035964,30.750998],[-82.043795,30.729641],[-82.036426,30.706585],[-82.050432,30.676266],[-82.049507,30.655548],[-82.027338,30.606726],[-82.012109,30.593773],[-82.005477,30.563495],[-82.018361,30.531184],[-82.016982,30.478779],[-82.036203,30.43846],[-82.036825,30.377884],[-82.047917,30.363265],[-82.081106,30.358806],[-82.116385,30.367335],[-82.165192,30.358035],[-82.189847,30.375938],[-82.210291,30.42459],[-82.201416,30.485164],[-82.225026,30.50783],[-82.234952,30.533066],[-82.231916,30.55627],[-82.214818,30.568517],[-83.499876,30.645671],[-84.86346,30.711506],[-84.8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 \"}}]}","volume":"101","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc483e4b0f5d57878ea9e","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":740155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":740156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196176,"text":"70196176 - 2018 - Fire and climate suitability for woody vegetation communities in the south central United States","interactions":[],"lastModifiedDate":"2019-10-28T09:26:31","indexId":"70196176","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fire and climate suitability for woody vegetation communities in the south central United States","docAbstract":"Climate and fire are primary drivers of plant species distributions. Long-term management of south central United States woody vegetation communities can benefit from information on potential changes in climate and fire frequencies, and how these changes might affect plant communities. We used historical (1900 to 1929) and future (2040 to 2069 and 2070 to 2099) projected climate data for the conterminous US to estimate reference and future fire probabilities\nusing a physical chemistry fire frequency model. We then used the fire probability data with additional climate parameters to construct maximum entropy environmental suitability models for three south central US vegetation communities. The modeled communities included an oak type (dominated by post oak, Quercus stellata Wangenh., and blackjack oak, Q. marilandica Münchh.), a mesquite type (dominated by honey mesquite, Prosopis glandulosa Torr., and velvet mesquite, P. velutina Wooton), and a pinyon−juniper type (dominated by pinyon pine, Pinus edulis Engelm., and Utah juniper, Juniperus osteosperma [Torr.] Little). We mapped baseline and future mean fire-climate suitability using data from three global climate models for 2040 to 2069 and 2070 to 2099; we also mapped future locations of threshold conditions for which all three models agreed on suitability for each community. Future projections included northward, southward, and eastward shifts in suitable conditions for the oaks along a broad path of fire-climate stability; an overall reduction in suitable area for historic mesquite communities coupled with potential expansion to new areas; and constriction and isolation of suitable conditions for pinyon−juniper communities. The inclusion of fire probability adds an important driver of vegetation distribution to climate envelope modeling. The simple models showed good fit, but future projections failed to account for future management activities or land use changes. Results provided information on potential future de-coupling and spatial re-arrangement of environmental conditions under which these communities have historically persisted and been managed. In particular, consensus threshold maps can inform long-term planning for maintenance or restoration of these communities, and they can be used as a potential tool for other communities in fire-prone environments within the study area and beyond its borders.","language":"English","publisher":"Springer","doi":"10.4996/fireecology.140110612","usgsCitation":"Stroh, E., Struckhoff, M., Stambaugh, M.C., and Guyette, R.P., 2018, Fire and climate suitability for woody vegetation communities in the south central United States: Fire Ecology, v. 14, no. 1, p. 106-124, https://doi.org/10.4996/fireecology.140110612.","productDescription":"19 p.","startPage":"106","endPage":"124","ipdsId":"IP-088298","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.140110612","text":"Publisher Index Page"},{"id":352785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0bc","contributors":{"authors":[{"text":"Stroh, Esther 0000-0003-4291-4647","orcid":"https://orcid.org/0000-0003-4291-4647","contributorId":202825,"corporation":false,"usgs":true,"family":"Stroh","given":"Esther","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struckhoff, Matthew 0000-0002-4911-9956","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":201512,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stambaugh, Michael C.","contributorId":202826,"corporation":false,"usgs":false,"family":"Stambaugh","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":731539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guyette, Richard P.","contributorId":176595,"corporation":false,"usgs":false,"family":"Guyette","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":731540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196133,"text":"70196133 - 2018 - National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry","interactions":[],"lastModifiedDate":"2018-05-04T15:12:28","indexId":"70196133","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry","docAbstract":"<p id=\"abspara0010\">The National Gas Hydrate Program Expedition 01 (NGHP-01) targeted gas hydrate accumulations offshore of the Indian Peninsula and along the Andaman convergent margin. The primary objectives of coring were to understand the geologic and geochemical controls on the accumulation of methane hydrate and their linkages to underlying petroleum systems. Four areas were investigated: 1) the Kerala-Konkan Basin in the eastern Arabian Sea, 2) the Mahanadi and 3) Krishna-Godavari Basins in the western Bay of Bengal, and 4) the Andaman forearc Basin in the Andaman Sea.</p><p id=\"abspara0015\">Upward flux of methane at three of the four of the sites cored during NGHP-01 is apparent from the presence of seafloor mounds, seismic evidence for upward gas migration, shallow sub-seafloor geochemical evidence of methane oxidation, and near-seafloor gas composition that resembles gas from depth.</p><p id=\"abspara0020\">The Kerala-Konkan Basin well contained only CO<sub>2</sub><span>&nbsp;</span>with no detectable hydrocarbons suggesting there is no gas hydrate system here. Gas and gas hydrate from the Krishna-Godavari Basin is mainly microbial methane with δ<sup>13</sup>C values ranging from −58.9 to −78.9‰, with small contributions from microbial ethane (−52.1‰) and CO<sub>2</sub>. Gas from the Mahanadi Basin was mainly methane with lower concentrations of C<sub>2</sub>-C<sub>5</sub><span>&nbsp;</span>hydrocarbons (C<sub>1</sub>/C<sub>2</sub><span>&nbsp;</span>ratios typically &gt;1000) and CO<sub>2</sub>. Carbon isotopic compositions that ranged from −70.7 to −86.6‰ for methane and −62.9 to −63.7‰ for ethane are consistent with a microbial gas source; however deeper cores contained higher molecular weight hydrocarbon gases suggesting a small contribution from a thermogenic gas source. Gas composition in the Andaman Basin was mainly methane with lower concentrations of ethane to isopentane and CO<sub>2,</sub><span>&nbsp;</span>C<sub>1</sub>/C<sub>2</sub><span>&nbsp;</span>ratios were mainly &gt;1000 although deeper samples were &lt;1000. Carbon isotopic compositions range from −65.2 to −80.7‰ for methane, −53.1 to −55.2‰ for ethane is consistent with mainly microbial gas sources, although one value recorded of −35.4‰ for propane suggests a thermogenic source. Gas hydrate accumulations in the Krishna-Godavari and Mahanadi Basins are the result of a microbially sourced gas hydrate system. The system is enhanced by the migration of microbial gas from surrounding areas through pathways including high-porosity delta sands, shale diapirism, faulting and folding of sediment due to the local processes associated with rapid sediment deposition, sediment overpressure, and the recycling of methane from a rapidly upward moving gas hydrate stability zone. The gas hydrate system in the Andaman Basin is less well constrained due to lack of exploration and occurs in a forearc basin. Each of these hydrate-bearing systems overlies and is likely supported by the presence and possible migration of gas from deeper gas-prone petroleum systems currently generating thermogenic hydrocarbons at much greater depths.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2017.11.011","usgsCitation":"Lorenson, T., and Collett, T.S., 2018, National Gas Hydrate Program Expedition 01 offshore India; gas hydrate systems as revealed by hydrocarbon gas geochemistry: Marine and Petroleum Geology, v. 92, p. 477-492, https://doi.org/10.1016/j.marpetgeo.2017.11.011.","productDescription":"16 p.","startPage":"477","endPage":"492","ipdsId":"IP-077202","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2017.11.011","text":"Publisher Index Page"},{"id":353004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","volume":"92","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0c0","contributors":{"authors":[{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":731492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731493,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196173,"text":"70196173 - 2018 - Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines","interactions":[],"lastModifiedDate":"2018-03-22T09:59:54","indexId":"70196173","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines","docAbstract":"<p><span>Understanding intrinsic (physiological) and extrinsic (e.g., temperature) causes of variation in embryonic development time (incubation period) is important because they can have different impacts on individual quality. Robert Ricklefs and colleagues have argued that longer incubation periods result primarily from intrinsic physiological programs that increase individual quality and adult survival. They claim that incubation periods are largely invariant and that extrinsic factors like temperature have little impact. We have argued that adult survival may be a cause rather than a consequence of much of the variation in embryonic development time. A reduction in extrinsic sources of annual adult mortality (e.g., migration, predation, nonbreeding-season mortality) favors reduced parental effort during incubation to minimize costs to future reproduction and survival. Reduced parental effort, in turn, manifests as cooler average egg temperatures that yield longer incubation periods. Ricklefs and colleagues mischaracterized our hypothesis and deconstructed their own incorrect version, while also making some incorrect statements. We show that reevaluation of previous evidence provided by this group actually supports a role of egg temperature for the variation in incubation periods. We also summarize other observational and experimental evidence that incubation periods are not invariant and that egg temperature has a strong causal influence on variation within and among species. In fact, egg temperature explains ∼60% of the difference in incubation periods among species. The remaining ∼40% reflects intrinsic physiological programs and other factors, potentially providing intrinsic benefits. Ultimately, annual adult mortality explains substantial variation in parental effort and egg temperature, and the latter strongly explains variation in incubation periods. Both intrinsic programs and extrinsic temperature effects need to be considered in attempts to understand incubation strategies.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-124.1","usgsCitation":"Martin, T.E., Ton, R., and Oteyza, J.C., 2018, Adaptive influence of extrinsic and intrinsic factors on variation of incubation periods among tropical and temperate passerines: The Auk, v. 135, no. 1, p. 101-113, https://doi.org/10.1642/AUK-17-124.1.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-088493","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-17-124.1","text":"Publisher Index Page"},{"id":352727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee711e4b0da30c1bfc0be","contributors":{"authors":[{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":731534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ton, Riccardo","contributorId":95334,"corporation":false,"usgs":true,"family":"Ton","given":"Riccardo","affiliations":[],"preferred":false,"id":731547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oteyza, Juan C.","contributorId":166761,"corporation":false,"usgs":false,"family":"Oteyza","given":"Juan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731548,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196051,"text":"70196051 - 2018 - Developing a framework for evaluating tallgrass prairie reconstruction methods and management","interactions":[],"lastModifiedDate":"2018-03-15T11:44:40","indexId":"70196051","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"title":"Developing a framework for evaluating tallgrass prairie reconstruction methods and management","docAbstract":"<p><span>The thousands of hectares of prairie reconstructed each year in the tallgrass prairie biome can provide a valuable resource for evaluation of seed mixes, planting methods, and post-planting management if methods used and resulting characteristics of the prairies are recorded and compiled in a publicly accessible database. The objective of this study was to evaluate the use of such data to understand the outcomes of reconstructions over a 10-year period at two U.S. Fish and Wildlife Service refuges. Variables included number of species planted, seed source (combine-harvest or combine-harvest plus hand-collected), fire history, and planting method and season. In 2015 we surveyed vegetation on 81 reconstructions and calculated proportion of planted species observed; introduced species richness; native species richness, evenness and diversity; and mean coefficient of conservatism. We conducted exploratory analyses to learn how implied communities based on seed mix compared with observed vegetation; which seeding or management variables were influential in the outcome of the reconstructions; and consistency of responses between the two refuges. Insights from this analysis include: 1) proportion of planted species observed in 2015 declined as planted richness increased, but lack of data on seeding rate per species limited conclusions about value of added species; 2) differing responses to seeding and management between the two refuges suggest the importance of geographic variability that could be addressed using a public database; and 3) variables such as fire history are difficult to quantify consistently and should be carefully evaluated in the context of a public data repository.</span></p>","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.36.1.6","usgsCitation":"Larson, D.L., Ahlering, M., Drobney, P., Esser, R., Larson, J.L., and Viste-Sparkman, K., 2018, Developing a framework for evaluating tallgrass prairie reconstruction methods and management: Ecological Restoration, v. 36, no. 1, p. 6-18, https://doi.org/10.3368/er.36.1.6.","productDescription":"13 p.","startPage":"6","endPage":"18","ipdsId":"IP-082530","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee712e4b0da30c1bfc0c4","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahlering, Marissa 0000-0002-3913-428X","orcid":"https://orcid.org/0000-0002-3913-428X","contributorId":171943,"corporation":false,"usgs":false,"family":"Ahlering","given":"Marissa","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":731144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drobney, Pauline","contributorId":178447,"corporation":false,"usgs":false,"family":"Drobney","given":"Pauline","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":731146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esser, Rebecca","contributorId":197592,"corporation":false,"usgs":false,"family":"Esser","given":"Rebecca","affiliations":[],"preferred":false,"id":731145,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Jennifer L.","contributorId":178444,"corporation":false,"usgs":false,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":731148,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viste-Sparkman, Karen","contributorId":197593,"corporation":false,"usgs":false,"family":"Viste-Sparkman","given":"Karen","email":"","affiliations":[],"preferred":false,"id":731147,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196211,"text":"70196211 - 2018 - Ground ruptures attributed to groundwater overexploitation damaging Jocotepec city in Jalisco, Mexico: 2016 field excursion of IGCP-641","interactions":[],"lastModifiedDate":"2020-12-15T22:41:37.225266","indexId":"70196211","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5657,"text":"Episodes, Journal of International Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Ground ruptures attributed to groundwater overexploitation damaging Jocotepec city in Jalisco, Mexico: 2016 field excursion of IGCP-641","docAbstract":"IGCP Project 641 (Mechanisms, Monitoring and Modeling Earth\nFissure generation and Fault activation due to subsurface Fluid\nexploitation – M3EF3) held its second international workshop from\nNovember 2 to 6, 2016, in Puerto Vallarta and included a two-day\nfield trip to Guadalajara and Jocotepec in the Mexican state of Jalisco\n(Fig. 1a). M3EF3 is aimed at i) understanding the mechanisms that\ncause the formation of “ground ruptures”, as a response to changes in\nthe stress state in the subsoil, ii) monitoring their occurrence, and iii)\ndeveloping appropriate approaches to model their formation and\ngrowth. Notice that many times it is difficult to discern whether a particular\ninstance of a “ruptured” land surface is due to an earth fissure\nwith a surface manifestation or a surface failure associated with the\nactivation of a pre-existing fault, especially where a fault has not been\nmapped and where there is no obvious scarp. Therefore, in M3EF3\nwe preferred to use the term “ground rupture”, to refer to both such\noccurrences.","language":"English","publisher":"IUGS, Geological Society of Korea","doi":"10.18814/epiiugs/2018/v41i1/007","usgsCitation":"Teatini, P., Carreon-Freyre, D., Ochoa-Gonzalez, G., Ye, S., Galloway, D.L., and Hernandez-Marin, M., 2018, Ground ruptures attributed to groundwater overexploitation damaging Jocotepec city in Jalisco, Mexico: 2016 field excursion of IGCP-641: Episodes, Journal of International Geoscience, v. 41, no. 1, p. 69-73, https://doi.org/10.18814/epiiugs/2018/v41i1/007.","productDescription":"5 p.","startPage":"69","endPage":"73","ipdsId":"IP-086773","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":460999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.18814/epiiugs/2018/v41i1/007","text":"Publisher Index Page"},{"id":352784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Jalisco","city":"Jocotepec","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.47833633422852,\n              20.25543335716953\n            ],\n            [\n              -103.4113883972168,\n              20.25543335716953\n            ],\n            [\n              -103.4113883972168,\n              20.320321149740877\n            ],\n            [\n              -103.47833633422852,\n              20.320321149740877\n            ],\n            [\n              -103.47833633422852,\n              20.25543335716953\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0b8","contributors":{"authors":[{"text":"Teatini, Pietro","contributorId":203529,"corporation":false,"usgs":false,"family":"Teatini","given":"Pietro","email":"","affiliations":[{"id":36643,"text":"Department of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy","active":true,"usgs":false}],"preferred":false,"id":731704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carreon-Freyre, Dora","contributorId":203530,"corporation":false,"usgs":false,"family":"Carreon-Freyre","given":"Dora","email":"","affiliations":[{"id":36644,"text":"Centro de Geociencias, Universidad Nacional Autónoma de México, Campus Juriquilla, Queretaro, Mexico","active":true,"usgs":false}],"preferred":false,"id":731705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ochoa-Gonzalez, Gil","contributorId":203531,"corporation":false,"usgs":false,"family":"Ochoa-Gonzalez","given":"Gil","email":"","affiliations":[{"id":36645,"text":"Western Institute of Technology and Higher Education (Instituto Tecnológico y de Estudios Superiores de Occidente ITESO), Jalisco, Mexico","active":true,"usgs":false}],"preferred":false,"id":731706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ye, Shujun","contributorId":203532,"corporation":false,"usgs":false,"family":"Ye","given":"Shujun","email":"","affiliations":[{"id":36646,"text":"Dept. of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing P. R. China","active":true,"usgs":false}],"preferred":false,"id":731707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hernandez-Marin, Martin","contributorId":203533,"corporation":false,"usgs":false,"family":"Hernandez-Marin","given":"Martin","email":"","affiliations":[{"id":36647,"text":"Department of Geotechnics and Hydraulics, Autonomous University of Aguascalientes (Universidad Autónoma de Aguascalientes), Aguascalientes, Mexico","active":true,"usgs":false}],"preferred":false,"id":731708,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197209,"text":"70197209 - 2018 - Does behavioural thermoregulation underlie seasonal movements in Lake Erie walleye?","interactions":[],"lastModifiedDate":"2018-05-22T15:07:24","indexId":"70197209","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Does behavioural thermoregulation underlie seasonal movements in Lake Erie walleye?","docAbstract":"<p><span>Thermoregulation is presumed to be a widespread determinant of behaviour in fishes, but has not often been investigated as a mechanism shaping long-distance migrations. We used acoustic telemetry and animal-borne thermal loggers to test the hypothesis that seasonal migration in adult walleye (</span><i>Sander vitreus</i><span>) in Lake Erie is size- and (or) sex-specific and related to behavioural thermoregulation. Female walleye migrated out of the warm, shallow western basin earlier than did males and were 1.8 times more likely to be detected on acoustic receivers in the deeper and cooler eastern basin. The few fish that remained in the western basin were restricted to a smaller range of higher temperatures (≥20 °C) than those that migrated to the central and eastern basins (∼16–21 °C). However, temperature records from walleye in the central basin were nearly indistinguishable from those in the eastern basin, suggesting thermal preferences alone could not explain migration to the eastern basin. As such, our effort to understand the mechanisms that cause migratory behaviours has generated mixed evidence on the role of temperature and that factors like foraging opportunities may have synergistic roles in the migration.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0145","usgsCitation":"Raby, G.D., Vandergoot, C., Hayden, T., Faust, M.D., Kraus, R.T., Dettmers, J.M., Cooke, S., Zhao, Y., Fisk, A.T., and Krueger, C., 2018, Does behavioural thermoregulation underlie seasonal movements in Lake Erie walleye?: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 3, p. 488-496, https://doi.org/10.1139/cjfas-2017-0145.","productDescription":"9 p.","startPage":"488","endPage":"496","ipdsId":"IP-085286","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":460997,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/82828","text":"External Repository"},{"id":354397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84,\n              41\n            ],\n            [\n              -78.49731445312499,\n              41\n            ],\n            [\n              -78.49731445312499,\n              43.36512572875844\n            ],\n            [\n              -84,\n              43.36512572875844\n            ],\n            [\n              -84,\n              41\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"75","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d9be4b092d9651e1b77","contributors":{"authors":[{"text":"Raby, Graham D.","contributorId":205145,"corporation":false,"usgs":false,"family":"Raby","given":"Graham","email":"","middleInitial":"D.","affiliations":[{"id":32936,"text":"Great Lakes Institute for Environmental Research, University of Windsor","active":true,"usgs":false}],"preferred":false,"id":736214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":736213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayden, Todd A.","contributorId":205146,"corporation":false,"usgs":false,"family":"Hayden","given":"Todd A.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":736215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faust, Matthew D.","contributorId":145776,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":736216,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":736222,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":736217,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":736218,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhao, Yingming","contributorId":205147,"corporation":false,"usgs":false,"family":"Zhao","given":"Yingming","email":"","affiliations":[{"id":37034,"text":"Ontario Ministry of Natural Resources and Forestry, Aquatic Research and Monitoring Section","active":true,"usgs":false}],"preferred":false,"id":736219,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fisk, Aaron T.","contributorId":127340,"corporation":false,"usgs":false,"family":"Fisk","given":"Aaron","email":"","middleInitial":"T.","affiliations":[{"id":6778,"text":"University of Windsor, Windsor, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":736220,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Krueger, Charles C.","contributorId":67821,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles C.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":736221,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70196334,"text":"70196334 - 2018 - Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2019-08-30T06:57:40","indexId":"70196334","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","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":"Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model","docAbstract":"<div><p>For more than 20&nbsp;yrs, damage patterns and instrumental recordings have highlighted the influence of the local 3D geologic structure on earthquake ground motions (e.g.,<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span>&nbsp;6.7 Northridge, California,<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf14\">Gao<span>&nbsp;</span><i>et&nbsp;al.</i>, 1996</a>;<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-4\" class=\"math\"><span><span id=\"MathJax-Span-5\" class=\"mrow\"><span id=\"MathJax-Span-6\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span>&nbsp;6.9 Kobe, Japan,<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf18\">Kawase, 1996</a>;<span>&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span>&nbsp;6.8 Nisqually, Washington,<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf9\">Frankel, Carver, and Williams, 2002</a>). Although this and other local‐scale features are critical to improving seismic hazard forecasts, historically they have not been explicitly incorporated into the U.S. National Seismic Hazard Model (NSHM, national model and maps), primarily because the necessary basin maps and methodologies were not available at the national scale. Instead, the U.S. Geological Survey (USGS), its partners, and external groups developed urban seismic hazard maps (urban models and maps) that consider detailed site effects in local areas (e.g.,<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf27\">Wong<span>&nbsp;</span><i>et&nbsp;al.</i>, 2002</a>;<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf6\">Cramer<span>&nbsp;</span><i>et&nbsp;al.</i>, 2006</a>;<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf13\">Frankel<span>&nbsp;</span><i>et&nbsp;al.</i>, 2007</a>;<span>&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf15\">Graves<span>&nbsp;</span><i>et&nbsp;al.</i>, 2011</a>). The disconnect between the urban and national hazard models, however, means that the national models, which underlie U.S. building codes and other applications, do not make use of all of the scientific results informing earthquake ground‐shaking hazards.</p></div><div><p>We recommend that future U.S. national seismic hazard assessment make use of all available regional information, including that in urban models. In this column, we describe the roles of and differences between the urban and national models, and discuss the obstacles to and benefits of integrating the urban models with the national model. Future progress on this issue will require further coordination and implementation efforts between the USGS and external partners.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170261","usgsCitation":"Moschetti, M.P., Luco, N., Frankel, A.D., Petersen, M.D., Aagaard, B.T., Baltay Sundstrom, A.S., Blanpied, M.L., Boyd, O.S., Briggs, R.W., Gold, R.D., Graves, R., Hartzell, S.H., Rezaeian, S., Stephenson, W.J., Wald, D.J., Williams, R., and Withers, K., 2018, Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model: Seismological Research Letters, v. 89, no. 3, p. 967-970, https://doi.org/10.1785/0220170261.","productDescription":"4 p.","startPage":"967","endPage":"970","ipdsId":"IP-094326","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":353086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0ae","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":732357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":732359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":732360,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blanpied, Michael L. 0000-0002-3294-4458 mblanpied@usgs.gov","orcid":"https://orcid.org/0000-0002-3294-4458","contributorId":203801,"corporation":false,"usgs":true,"family":"Blanpied","given":"Michael","email":"mblanpied@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":732361,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":732362,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732363,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732364,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":732365,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732366,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732367,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732368,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732369,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Williams, Robert A. 0000-0002-2973-8493","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":203802,"corporation":false,"usgs":false,"family":"Williams","given":"Robert A.","affiliations":[{"id":36721,"text":"USGS-Emeritus","active":true,"usgs":false}],"preferred":false,"id":732370,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Withers, Kyle 0000-0001-7863-3930","orcid":"https://orcid.org/0000-0001-7863-3930","contributorId":203492,"corporation":false,"usgs":true,"family":"Withers","given":"Kyle","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732371,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70196824,"text":"70196824 - 2018 - Response of beach-nesting American Oystercatchers to off-road vehicles: An experimental approach reveals physiological nuances and decreased nest attendance","interactions":[],"lastModifiedDate":"2018-05-03T13:33:33","indexId":"70196824","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Response of beach-nesting American Oystercatchers to off-road vehicles: An experimental approach reveals physiological nuances and decreased nest attendance","docAbstract":"<p><span>Shorebird populations face increasing challenges as rising sea levels and growing human populations constrain their breeding habitats. On recreational beaches, the nesting season often coincides with a season of high visitor use, increasing the potential for conflict, which may negatively influence beach-nesting shorebird species. We designed a field experiment to study the responses of nesting American Oystercatchers (</span><i>Haematopus palliatus</i><span>) to off-road passenger vehicles (ORVs) at Cape Hatteras and Cape Lookout National Seashores in North Carolina, USA. We used continuous video and heart rate recordings to assess changes in the behavior and physiology of incubating oystercatchers. We conducted driving experiments affecting 7 nesting pairs in 2014 and 19 nesting pairs in 2015, between April and July of each year. Experimental treatments were repeated throughout the incubation period for each nest. Although responses were highly variable within and among pairs, paired randomized permutation tests indicated that, overall, oystercatcher pairs spent a greater proportion of time with their heads up and exhibited slower heart rates during driving treatments. Pairs also left their nests more frequently and attended their nests for a lower proportion of time during driving treatments, although these responses diminished over time. Higher nest attendance and lower departure rates late in incubation may have reflected a stronger attachment to nests closer to hatching or habituation to the driving treatment, although individuals continued to exhibit physiological responses to passing vehicles throughout incubation. Beach-nesting birds may benefit from reduced vehicle traffic at their nesting sites, allowing parents to spend more time attending the nest and less time on defensive behaviors.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-84.1","usgsCitation":"Felton, S.K., Pollock, K.H., and Simons, T.R., 2018, Response of beach-nesting American Oystercatchers to off-road vehicles: An experimental approach reveals physiological nuances and decreased nest attendance: The Condor, v. 120, no. 1, p. 47-62, https://doi.org/10.1650/CONDOR-17-84.1.","productDescription":"16 p.","startPage":"47","endPage":"62","ipdsId":"IP-087451","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-84.1","text":"Publisher Index Page"},{"id":353939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Hatteras National Seashore, Cape Lookout National Seashore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.75048828125,\n              34.538237527295756\n            ],\n            [\n              -75.399169921875,\n              34.538237527295756\n            ],\n            [\n              -75.399169921875,\n              36.06686213257888\n            ],\n            [\n              -76.75048828125,\n              36.06686213257888\n            ],\n            [\n              -76.75048828125,\n              34.538237527295756\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0a0","contributors":{"authors":[{"text":"Felton, Shilo K.","contributorId":190179,"corporation":false,"usgs":false,"family":"Felton","given":"Shilo","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":734635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Kenneth H.","contributorId":8590,"corporation":false,"usgs":false,"family":"Pollock","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":734636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196830,"text":"70196830 - 2018 - Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients","interactions":[],"lastModifiedDate":"2018-05-04T11:41:55","indexId":"70196830","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients","docAbstract":"<p><span>Nitrogen (N) and phosphorus (P) commonly stimulate phytoplankton production in lakes, but recent observations from lakes from an agricultural region suggest that nitrate may have a subsidy‐stress effect on chlorophyll&nbsp;</span><i>a</i><span><span>&nbsp;</span>(Chl<span>&nbsp;</span></span><i>a</i><span>). It is unclear, however, how generalizable this effect might be. Here, we analyzed a large water quality dataset of 2385 lakes spanning 60 regions across 17 states in the Northeastern and Midwestern U.S. to determine if N subsidy‐stress effects on phytoplankton are common and to identify regional landscape characteristics promoting N stress effects in lakes. We used a Bayesian hierarchical modeling framework to test our hypothesis that Chl<span>&nbsp;</span></span><i>a</i><span>–total N (TN) threshold relationships would be common across the central agricultural region of the U.S. (“the Corn Belt”), where lake N and P concentrations are high. Data aggregated across all regions indicated that high TN concentrations had a negative effect on Chl<span>&nbsp;</span></span><i>a</i><span><span>&nbsp;</span>in lakes with concurrent high total P. This large‐scale pattern was driven by relationships within only a subset of regions, however. Eight regions were identified as having Chl<span>&nbsp;</span></span><i>a</i><span>–TN threshold relationships, but only two of these regions located within the Corn Belt clearly demonstrated this subsidy‐stress relationship. N stress effects were not consistent across other intense agricultural regions, as we hypothesized. These findings suggest that interactions among regional land use and land cover, climate, and hydrogeology may be important in determining the synergistic conditions leading to N subsidy‐stress effects on lake phytoplankton.</span></p>","language":"English","publisher":"ASLO","doi":"10.1002/lno.10742","usgsCitation":"Filstrup, C.T., Wagner, T., Oliver, S., Stow, C.A., Webster, K.E., Stanley, E.H., and Downing, J., 2018, Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients: Limnology and Oceanography, v. 63, no. S1, p. S324-S339, https://doi.org/10.1002/lno.10742.","productDescription":"16 p.","startPage":"S324","endPage":"S339","ipdsId":"IP-088161","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468964,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10742","text":"Publisher Index Page"},{"id":353963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70160593,"text":"70160593 - 2018 - Understanding map projections","interactions":[],"lastModifiedDate":"2020-08-20T16:57:54.157601","indexId":"70160593","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"15","title":"Understanding map projections","docAbstract":"<p><span>It has probably never been more important in the history of cartography than now that people understand how maps work. With increasing globalization, for example, world maps provide a key format for the transmission of information, but are often poorly used. Examples of poor understanding and use of projections and the resultant maps are many; for instance, the use of rectangular world maps in the United Kingdom press to show Chinese and Korean missile ranges as circles, something which can only be achieved on equidistant projections and then only from one launch point (Vujakovic, 2014).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Routledge handbook of mapping and cartography","largerWorkSubtype":{"id":13,"text":"Handbook"},"language":"English","publisher":"Routledge","isbn":"9781138831025","usgsCitation":"Usery, E.L., 2018, Understanding map projections, chap. 15 <i>of</i> The Routledge handbook of mapping and cartography, 21 p.","productDescription":"21 p.","ipdsId":"IP-068403","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":352881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340035,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.routledge.com/The-Routledge-Handbook-of-Mapping-and-Cartography/Kent-Vujakovic/p/book/9781138831025"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee713e4b0da30c1bfc0de","contributors":{"editors":[{"text":"Kent, Alexander J.","contributorId":191200,"corporation":false,"usgs":false,"family":"Kent","given":"Alexander","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692288,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Vujakovic, Peter","contributorId":191199,"corporation":false,"usgs":false,"family":"Vujakovic","given":"Peter","email":"","affiliations":[],"preferred":false,"id":692289,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Usery, E. Lynn 0000-0002-2766-2173 usery@usgs.gov","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":231,"corporation":false,"usgs":true,"family":"Usery","given":"E.","email":"usery@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":583230,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196225,"text":"70196225 - 2018 - Stability and change in kelp forest habitats at San Nicolas Island","interactions":[],"lastModifiedDate":"2020-12-16T16:29:35.001376","indexId":"70196225","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Stability and change in kelp forest habitats at San Nicolas Island","docAbstract":"<p><span>Kelp forest communities are highly variable over space and time. Despite this complexity it has been suggested that kelp forest communities can be classified into one of 2 states: kelp dominated or sea urchin dominated. It has been further hypothesized that these represent “alternate stable states” because a site can remain in either of these states for decades before some perturbation causes a rapid shift to the other state. Our research group has maintained a subtidal community monitoring program for 38 years at San Nicolas Island consisting of twice-annual scuba-based surveys at 6 sites distributed within 4 regions around the island. Three types of perturbations are thought to be relevant to subtidal community dynamics at San Nicolas: (1) physical disturbances in the form of major storm and El Niño/Southern Oscillation (ENSO) events; (2) invertebrate diseases, which periodically decimate urchin populations; and (3) the reintroduction and subsequent increase of sea otters (</span><i>Enhydra lutris nereis</i><span>). These 3 perturbations differ in spatial and temporal specificity; physical disturbances and disease outbreaks occur periodically and could affect all 4 regions, while sea otter predation has been concentrated primarily at the West End sites over the last 15 years. The different types of perturbations and the duration of the time series at the kelp forests at San Nicolas make the data set ideal for testing the “alternate stable state” hypothesis. We use nonmetric multidimensional scaling (NMDS) to examine spatial and temporal patterns of community similarity at the 4 regions. In particular, we evaluate support for the existence of stable states, which are represented on NMDS plots as distinct spatial clusters. Community dynamics at each site approximated a biased random walk in NMDS space, with one or more basins of attraction and occasional jumps between basins. We found evidence for alternative stable states at some sites, and we show that transitions from one stable state to another may be influenced by interactions between multiple perturbations.</span></p>","language":"English","publisher":"Western North American Naturalist Publications","doi":"10.3398/064.078.0407","usgsCitation":"Kenner, M.C., and Tinker, M.T., 2018, Stability and change in kelp forest habitats at San Nicolas Island: Western North American Naturalist, v. 78, no. 4, p. 633-643, https://doi.org/10.3398/064.078.0407.","productDescription":"11 p.","startPage":"633","endPage":"643","ipdsId":"IP-086463","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488846,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol78/iss4/14","text":"External Repository"},{"id":352844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.58824157714842,\n              33.20881849225547\n            ],\n            [\n              -119.42893981933592,\n              33.20881849225547\n            ],\n            [\n              -119.42893981933592,\n              33.289785856885224\n            ],\n            [\n              -119.58824157714842,\n              33.289785856885224\n            ],\n            [\n              -119.58824157714842,\n              33.20881849225547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0b6","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":203543,"corporation":false,"usgs":false,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":731747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198130,"text":"70198130 - 2018 - Drivers of variability in public‐supply water use across the contiguous United States","interactions":[],"lastModifiedDate":"2018-07-17T09:50:48","indexId":"70198130","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of variability in public‐supply water use across the contiguous United States","docAbstract":"<p><span>This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian‐hierarchical regression models for over 2,500 counties, 18 covariates, and three higher‐level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher‐level groups results in the best out‐of‐sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city‐level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county‐level model, the effect of each variable depends heavily on where a city is located.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017WR021268","usgsCitation":"Worland, S.C., Steinschneider, S., and Hornberger, G.M., 2018, Drivers of variability in public‐supply water use across the contiguous United States: Water Resources Research, v. 54, no. 3, p. 1868-1889, https://doi.org/10.1002/2017WR021268.","productDescription":"22 p.","startPage":"1868","endPage":"1889","ipdsId":"IP-087770","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":488785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr021268","text":"Publisher Index Page"},{"id":355717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"54","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5b6fc483e4b0f5d57878ea9c","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":740159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steinschneider, Scott 0000-0002-8882-1908","orcid":"https://orcid.org/0000-0002-8882-1908","contributorId":206359,"corporation":false,"usgs":false,"family":"Steinschneider","given":"Scott","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":740160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hornberger, George M.","contributorId":206360,"corporation":false,"usgs":false,"family":"Hornberger","given":"George","email":"","middleInitial":"M.","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":740161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194641,"text":"tm14A2 - 2018 - THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual","interactions":[],"lastModifiedDate":"2018-03-01T11:10:52","indexId":"tm14A2","displayToPublicDate":"2018-02-28T17:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"14-A2","title":"THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual","docAbstract":"<p>Precipitation thresholds are used in many areas to provide early warning of precipitation-induced landslides and debris flows, and the software distribution THRESH is designed for automated tracking of precipitation, including precipitation forecasts, relative to thresholds for landslide occurrence. This software is also useful for analyzing multiyear precipitation records to compare timing of threshold exceedance with dates and times of historical landslides. This distribution includes the main program THRESH for comparing precipitation to several kinds of thresholds, two utility programs, and a small collection of Python and shell scripts to aid the automated collection and formatting of input data and the graphing and further analysis of output results. The software programs can be deployed on computing platforms that support Fortran 95, Python 2, and certain Unix commands. The software handles rainfall intensity-duration thresholds, cumulative recent-antecedent precipitation thresholds, and peak intensity thresholds as well as various measures of antecedent precipitation. Users should have predefined rainfall thresholds before running THRESH.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Modeling methods in Book 14: <i>Landslide and debris-flow assessment</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm14A2","usgsCitation":"Baum, R.L., Fischer, S.J., and Vigil, J.C., 2018, THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual: U.S. Geological Survey Techniques and Methods, book 14, chap. A2, 33 p., https://doi.org/10.3133/tm14A2.","productDescription":"Report: v, 33 p.; Software release","onlineOnly":"Y","ipdsId":"IP-087132","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437999,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23XR0","text":"USGS data release","linkHelpText":"Thresh - Software for Tracking Rainfall Thresholds for Landslide and Debris Flow Occurrence, Code Repository"},{"id":352130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/14/a2/coverthb.jpg"},{"id":352140,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7Q23XR0","text":"Software Release","linkHelpText":"THRESH"},{"id":352131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/14/a2/tm14a2.pdf","text":"Report","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 14-A2"}],"publicComments":"This report is Chapter 2 of Section A: Modeling methods in Book 14: <i>Landslide and debris-flow assessment</i>.","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/geohazards\" data-mce-href=\"https://www.usgs.gov/centers/geohazards\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS 966<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Features</li><li>Theoretical Basis of the Program</li><li>Program Operation</li><li>Utility Programs</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Seattle, Washington, Example</li><li>Appendix 2. Example of Using Rainfall Forecasts with Thresholds</li><li>Appendix 3. Hydrological Monitoring Sites</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2018-02-28","noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee713e4b0da30c1bfc0e0","contributors":{"authors":[{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":724706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Sarah J.","contributorId":201201,"corporation":false,"usgs":false,"family":"Fischer","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":724707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vigil, Jacob C.","contributorId":201202,"corporation":false,"usgs":false,"family":"Vigil","given":"Jacob","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":724708,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195704,"text":"tm9A0 - 2018 - General introduction for the “National Field Manual for the Collection of Water-Quality Data”","interactions":[],"lastModifiedDate":"2018-06-22T16:22:10","indexId":"tm9A0","displayToPublicDate":"2018-02-28T14:35:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"9-A0","title":"General introduction for the “National Field Manual for the Collection of Water-Quality Data”","docAbstract":"<h1>Background</h1><p>As part of its mission, the U.S. Geological Survey (USGS) collects data to assess the quality of our Nation’s water resources. A high degree of reliability and standardization of these data are paramount to fulfilling this mission. Documentation of nationally accepted methods used by USGS personnel serves to maintain consistency and technical quality in data-collection activities. “The National Field Manual for the Collection of Water-Quality Data” (NFM) provides documented guidelines and protocols for USGS field personnel who collect water-quality data. The NFM provides detailed, comprehensive, and citable procedures for monitoring the quality of surface water and groundwater. Topics in the NFM include (1) methods and protocols for sampling water resources, (2) methods for processing samples for analysis of water quality, (3) methods for measuring field parameters, and (4) specialized procedures, such as sampling water for low levels of mercury and organic wastewater chemicals, measuring biological indicators, and sampling bottom sediment for chemistry. Personnel who collect water-quality data for national USGS programs and projects, including projects supported by USGS cooperative programs, are mandated to use protocols provided in the NFM per USGS Office of Water Quality Technical Memorandum 2002.13. Formal training, for example, as provided in the USGS class, “Field Water-Quality Methods for Groundwater and Surface Water,” and field apprenticeships supplement the guidance provided in the NFM and ensure that the data collected are high quality, accurate, and scientifically defensible.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: National Field Manual for the Collection of Water-Quality Data in Book 9: <i>Handbooks for Water-Resources Investigations</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A0","usgsCitation":"U.S. Geological Survey, 2018, General introduction for the “National Field Manual for the Collection of Water-Quality Data” (ver. 1.1, June 2018): U.S. Geological Survey Techniques and Methods, book 9, chap. A0, 4 p., https://doi.org/10.3133/tm9A0. [Supersedes USGS Techniques and Methods,<br> book 9, chap. A0, version 1.0.]","productDescription":"iv, 4 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088394","costCenters":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":355125,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/09/a0/versionHist.txt","size":"1 MB","linkFileType":{"id":2,"text":"txt"}},{"id":352088,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a0/coverthb2.jpg"},{"id":352089,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a0/tm9a0.pdf","text":"Report","size":"263 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9A0"}],"edition":"Version 1.1","publicComments":"This report is Chapter 0 of Section A: National Field Manual for the Collection of Water-Quality Data in Book 9: <i>Handbooks for Water-Resources Investigations</i>.\n<p> </p>\n<p>General introduction for the “National Field Manual for the Collection of Water-Quality Data” (ver. 1.1) supersedes version 1.0 released February 2018. </p>","contact":"<p>Chief, Office of Quality Assurance <br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive, MS 432<br> Reston, VA 20192</p>","tableOfContents":"<ul><li>Foreword</li><li>Background</li><li>Transition to a New Series</li><li>Purpose and Scope</li><li>Chapters of the “National Field Manual for the Collection of Water-Quality Data”</li><li>Revision Process</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2018-02-28","revisedDate":"2018-06-22","noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee713e4b0da30c1bfc0e2","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":127955,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":729755,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70196797,"text":"70196797 - 2018 - AMModels: An R package for storing models, data, and metadata to facilitate adaptive management","interactions":[],"lastModifiedDate":"2018-05-01T15:52:43","indexId":"70196797","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","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":"AMModels: An R package for storing models, data, and metadata to facilitate adaptive management","docAbstract":"<p><span>Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package,&nbsp;</span><strong>AMModels</strong><span>. AMModels was developed under R version 3.2.2. The overall goal of<span>&nbsp;</span></span><strong>AMModels</strong><span><span>&nbsp;</span>is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future.<span>&nbsp;</span></span><strong>AMModels</strong><span><span>&nbsp;</span>facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process,<span>&nbsp;</span></span><strong>AMModels</strong><span><span>&nbsp;</span>allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While<span>&nbsp;</span></span><strong>AMModels</strong><span><span>&nbsp;</span>was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge,<span>&nbsp;</span></span><strong>AMModels</strong><span><span>&nbsp;</span>is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188966","usgsCitation":"Donovan, T.M., and Katz, J., 2018, AMModels: An R package for storing models, data, and metadata to facilitate adaptive management: PLoS ONE, v. 13, no. 2, p. 1-57, https://doi.org/10.1371/journal.pone.0188966.","productDescription":"e0188966; 57","startPage":"1","endPage":"57","ipdsId":"IP-081371","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461013,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188966","text":"Publisher Index Page"},{"id":353899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0e4","contributors":{"authors":[{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Jonathan","contributorId":8370,"corporation":false,"usgs":true,"family":"Katz","given":"Jonathan","affiliations":[],"preferred":false,"id":734478,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70195720,"text":"70195720 - 2018 - Anthropogenic impact in the Mayan Lowlands of Petén, Guatemala, during the last 5500 years","interactions":[],"lastModifiedDate":"2018-02-28T09:34:02","indexId":"70195720","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2437,"text":"Journal of Quaternary Science","active":true,"publicationSubtype":{"id":10}},"title":"Anthropogenic impact in the Mayan Lowlands of Petén, Guatemala, during the last 5500 years","docAbstract":"Trace and rare earth elements from a Lake Peten Itzá (Guatemala) sediment core depict the geochemical dynamics affecting the lake from ~5500 y BP to the present. This timing encompasses the Preclassic (4000 to 1700 y BP) and Classic Periods (1700-1000 y BP) when thriving Maya societies extensively cleared land for agriculture. We demonstrate that this land use occurred during times of increased precipitation, where both processes resulted in increased erosion. Rare earth element ratios depict high precipitation rates between 3000 to 1000 y BP, correlating with an increase in allocthonous silicate input and low organic carbon in the “Maya Clay” stratigraphic section, where this layer is ascribed to intensive anthropogenic land use. Cesium anomalies provide additional evidence for runoff due to high rainfalls and amplified by anthropogenic impacts. The Peten Itzá core contains anomalous spikes of arsenic and mercury, where these peaks correspond to documented volcanic eruptions, and therefore are likely due to natural causes. The geochemical composition of sediments and palynological records indicate a re-growth of the forest after ~900 y BP. This increased forest vegetation coincides with the timing of the decline in Maya agriculture.","language":"English","publisher":"Wiley","doi":"10.1002/jqs.3013","usgsCitation":"Battistel, D., Roman, M., Marchetti, A., Kehrwald, N.M., Radaelli, M., Balliana, E., Toscano, G., and Barbante, C., 2018, Anthropogenic impact in the Mayan Lowlands of Petén, Guatemala, during the last 5500 years: Journal of Quaternary Science, v. 33, no. 2, p. 166-176, https://doi.org/10.1002/jqs.3013.","productDescription":"11 p.","startPage":"166","endPage":"176","ipdsId":"IP-085878","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468967,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10278/3697605","text":"External 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Informatics and Statistics, University Ca' Foscari of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":729778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Toscano, Giuseppina","contributorId":202822,"corporation":false,"usgs":false,"family":"Toscano","given":"Giuseppina","email":"","affiliations":[{"id":36531,"text":"Institute for the Dynamics of Environmental Processes -- CNR, University Ca' Foscari of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":729780,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barbante, Carlo","contributorId":202632,"corporation":false,"usgs":false,"family":"Barbante","given":"Carlo","email":"","affiliations":[{"id":36503,"text":"Department of Environmental Sciences, Infomatics, and Statistics, Ca'Foscari University of Venice, Via Torino 155, 30172 Mestre (VE), Italy","active":true,"usgs":false}],"preferred":false,"id":729779,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70195565,"text":"ofr20181029 - 2018 - Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17","interactions":[],"lastModifiedDate":"2018-03-01T11:06:55","indexId":"ofr20181029","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1029","title":"Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17","docAbstract":"<p class=\"p1\">The Green-Duwamish River transports watershed-derived sediment to the Lower Duwamish Waterway Superfund site near Seattle, Washington. Understanding the amount of sediment transported by the river is essential to the bed sediment cleanup process. Turbidity, discharge, suspended-sediment concentration (SSC), and particle-size data were collected by the U.S. Geological Survey (USGS) from February 2013 to January 2017 at the Duwamish River, Washington, within the tidal influence at river kilometer 16.7 (USGS streamgage 12113390; Duwamish River at Golf Course at Tukwila, WA). This report quantifies the timing and magnitude of suspended-sediment transported in the Duwamish River. Regression models were developed between SSC and turbidity and SSC and discharge to estimate 15- minute SSC. Suspended-sediment loads were calculated from the computed SSC and time-series discharge data for every 15-minute interval during the study period. The 2014–16 average annual suspended-sediment load computed was 117,246 tons (106,364 metric tons), of which 73.5 percent or (86,191 tons; 78,191 metric tons) was fine particle (less than 0.0625 millimeter in diameter) suspended sediment. The seasonality of this site is apparent when you divide the year into \"wet\" (October 16– April 15) and \"dry\" (April 16–October 15) seasons. Most (97 percent) of the annual suspended sediment was transported during the wet season, when brief periods of intense precipitation from storms, large releases from the Howard Hanson Dam, or a combination of both were much more frequent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181029","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Senter, C.A., Conn, K.E., Black, R.W., Peterson, N., Vanderpool-Kimura, A., and Foreman, J.R., 2018, Suspended-sediment transport from the Green-Duwamish River to the Lower Duwamish Waterway, Seattle, Washington, 2013–17: U.S. Geological Survey Open-File Report 2018–1029, 23 p., https://doi.org/10.3133/ofr20181029.","productDescription":"Report: vi, 23 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-092733","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":352133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1029/coverthb.jpg"},{"id":352134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1029/ofr20181029.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1029"},{"id":352135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71835Q9","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for turbidity, discharge, and suspended-sediment concentrations and loads, Duwamish River, Tukwila, Washington"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Green-Duwamish River, Lower Duwanish Waterway","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": 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98402</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Results<br></li><li>Summary<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishedDate":"2018-02-28","noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f4","contributors":{"authors":[{"text":"Senter, Craig A. 0000-0002-5479-3080 csenter@usgs.gov","orcid":"https://orcid.org/0000-0002-5479-3080","contributorId":150044,"corporation":false,"usgs":true,"family":"Senter","given":"Craig","email":"csenter@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Norman 0000-0001-6071-8741 npeterson@usgs.gov","orcid":"https://orcid.org/0000-0001-6071-8741","contributorId":177365,"corporation":false,"usgs":true,"family":"Peterson","given":"Norman","email":"npeterson@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderpool-Kimura, Ann M. 0000-0002-9382-2868 avander@usgs.gov","orcid":"https://orcid.org/0000-0002-9382-2868","contributorId":150042,"corporation":false,"usgs":true,"family":"Vanderpool-Kimura","given":"Ann","email":"avander@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, James R. 0000-0003-0535-4580 jforeman@usgs.gov","orcid":"https://orcid.org/0000-0003-0535-4580","contributorId":139319,"corporation":false,"usgs":true,"family":"Foreman","given":"James","email":"jforeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729816,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196033,"text":"70196033 - 2018 - Overcoming equifinality: Leveraging long time series for stream metabolism estimation","interactions":[],"lastModifiedDate":"2020-09-02T13:05:49.378881","indexId":"70196033","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Overcoming equifinality: Leveraging long time series for stream metabolism estimation","docAbstract":"<p><span>The foundational ecosystem processes of gross primary production (GPP) and ecosystem respiration (ER) cannot be measured directly but can be modeled in aquatic ecosystems from subdaily patterns of oxygen (O</span><sub>2</sub><span>) concentrations. Because rivers and streams constantly exchange O</span><sub>2</sub><span><span>&nbsp;</span>with the atmosphere, models must either use empirical estimates of the gas exchange rate coefficient (</span><i>K</i><sub>600</sub><span>) or solve for all three parameters (GPP, ER, and<span>&nbsp;</span></span><i>K</i><sub>600</sub><span>) simultaneously. Empirical measurements of<span>&nbsp;</span></span><i>K</i><sub>600</sub><span><span>&nbsp;</span>require substantial field work and can still be inaccurate. Three-parameter models have suffered from equifinality, where good fits to O</span><sub>2</sub><span><span>&nbsp;</span>data are achieved by many different parameter values, some unrealistic. We developed a new three-parameter, multiday model that ensures similar values for<span>&nbsp;</span></span><i>K</i><sub>600</sub><span><span>&nbsp;</span>among days with similar physical conditions (e.g., discharge). Our new model overcomes the equifinality problem by (1) flexibly relating<span>&nbsp;</span></span><i>K</i><sub>600</sub><span><span>&nbsp;</span>to discharge while permitting moderate daily deviations and (2) avoiding the oft-violated assumption that residuals in O</span><sub>2</sub><span><span>&nbsp;</span>predictions are uncorrelated. We implemented this hierarchical state-space model and several competitor models in an open-source R package,<span>&nbsp;</span></span><i>streamMetabolizer</i><span>. We then tested the models against both simulated and field data. Our new model reduces error by as much as 70% in daily estimates of<span>&nbsp;</span></span><i>K</i><sub>600</sub><span>, GPP, and ER. Further, accuracy benefits of multiday data sets require as few as 3&nbsp;days of data. This approach facilitates more accurate metabolism estimates for more streams and days, enabling researchers to better quantify carbon fluxes, compare streams by their metabolic regimes, and investigate controls on aquatic activity.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004140","usgsCitation":"Appling, A.P., Hall, R., Yackulic, C.B., and Arroita, M., 2018, Overcoming equifinality: Leveraging long time series for stream metabolism estimation: Journal of Geophysical Research: Biogeosciences, v. 123, no. 2, p. 624-645, https://doi.org/10.1002/2017JG004140.","productDescription":"22 p.","startPage":"624","endPage":"645","ipdsId":"IP-089889","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004140","text":"Publisher Index Page"},{"id":352520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0e6","contributors":{"authors":[{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":731078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Robert O. Jr.","contributorId":145459,"corporation":false,"usgs":false,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[{"id":16121,"text":"Uni. of Wyoming, Department of Zoology and Physiology","active":true,"usgs":false}],"preferred":false,"id":731079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":731080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arroita, Maite 0000-0001-8754-7604","orcid":"https://orcid.org/0000-0001-8754-7604","contributorId":203307,"corporation":false,"usgs":false,"family":"Arroita","given":"Maite","email":"","affiliations":[{"id":36597,"text":"Flathead Lake Biological Station, University of Montana; University of the Basque Country","active":true,"usgs":false}],"preferred":false,"id":731081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195695,"text":"70195695 - 2018 - Spatial and spectral interpolation of ground-motion intensity measure observations","interactions":[],"lastModifiedDate":"2018-08-08T15:52:47","indexId":"70195695","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and spectral interpolation of ground-motion intensity measure observations","docAbstract":"<p><span>Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlated, and correlated with each other at a given location, it is possible to apply the conditional multivariate normal (MVN) distribution to the problem of estimating unobserved IMs. In this article, we review the MVN and its application to general estimation problems, and then apply the MVN to the specific problem of ground‐motion IM interpolation. In particular, we present (1)&nbsp;a formulation of the MVN for the simultaneous interpolation of IMs across space and IM type (most commonly, spectral response at different oscillator periods) and (2)&nbsp;the inclusion of uncertain observation data in the MVN formulation. These techniques, in combination with modern empirical ground‐motion models and correlation functions, provide a flexible framework for estimating a variety of IMs at arbitrary locations.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170201","usgsCitation":"Worden, C., Thompson, E.M., Baker, J.W., Bradley, B.A., Luco, N., and Wald, D.J., 2018, Spatial and spectral interpolation of ground-motion intensity measure observations: Bulletin of the Seismological Society of America, v. 108, no. 2, p. 866-875, https://doi.org/10.1785/0120170201.","productDescription":"10 p.","startPage":"866","endPage":"875","ipdsId":"IP-092580","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-13","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f0","contributors":{"authors":[{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":729736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Jack W.","contributorId":115861,"corporation":false,"usgs":false,"family":"Baker","given":"Jack","email":"","middleInitial":"W.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":729737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Brendon A.","contributorId":202814,"corporation":false,"usgs":false,"family":"Bradley","given":"Brendon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":741992,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70195758,"text":"70195758 - 2018 - Regional climate response collaboratives: Multi-institutional support for climate resilience","interactions":[],"lastModifiedDate":"2018-07-03T11:35:20","indexId":"70195758","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Regional climate response collaboratives: Multi-institutional support for climate resilience","docAbstract":"<p><span>Federal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally-supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable research that informs climate-related decisions for stakeholders and ultimately enhances climate resilience at regional scales.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-17-0183.1","usgsCitation":"Averyt, K., Derner, J.D., Dilling, L., Guerrero, R., Joyce, L.A., McNeeley, S., McNie, E., Morisette, J.T., Ojima, D., O'Malley, R., Peck, D., Ray, A.J., Reeves, M., and Travis, W., 2018, Regional climate response collaboratives: Multi-institutional support for climate resilience: Bulletin of the American Meteorological Society, v. 99, p. 891-898, https://doi.org/10.1175/BAMS-D-17-0183.1.","productDescription":"8 p.","startPage":"891","endPage":"898","ipdsId":"IP-088689","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":468968,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholar.colorado.edu/downloads/cn69m5095","text":"External Repository"},{"id":352143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0e8","contributors":{"authors":[{"text":"Averyt, Kristen","contributorId":63331,"corporation":false,"usgs":true,"family":"Averyt","given":"Kristen","email":"","affiliations":[],"preferred":false,"id":729880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Derner, Justin D.","contributorId":169766,"corporation":false,"usgs":false,"family":"Derner","given":"Justin","email":"","middleInitial":"D.","affiliations":[{"id":25583,"text":"USDA-ARS Central Plains Experimental Range, Cheyenne, WY 82009","active":true,"usgs":false}],"preferred":false,"id":729881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dilling, Lisa","contributorId":202838,"corporation":false,"usgs":false,"family":"Dilling","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":729882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guerrero, Rafael","contributorId":202839,"corporation":false,"usgs":false,"family":"Guerrero","given":"Rafael","email":"","affiliations":[],"preferred":false,"id":729883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joyce, Linda A.","contributorId":106769,"corporation":false,"usgs":true,"family":"Joyce","given":"Linda","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNeeley, Shannon","contributorId":202840,"corporation":false,"usgs":false,"family":"McNeeley","given":"Shannon","affiliations":[],"preferred":false,"id":729885,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McNie, Elizabeth","contributorId":202841,"corporation":false,"usgs":false,"family":"McNie","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":729886,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":729887,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ojima, Dennis","contributorId":36166,"corporation":false,"usgs":true,"family":"Ojima","given":"Dennis","affiliations":[],"preferred":false,"id":729888,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"O'Malley, Robin romalley@usgs.gov","contributorId":3954,"corporation":false,"usgs":true,"family":"O'Malley","given":"Robin","email":"romalley@usgs.gov","affiliations":[],"preferred":true,"id":729889,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Peck, Dannele","contributorId":202842,"corporation":false,"usgs":false,"family":"Peck","given":"Dannele","affiliations":[],"preferred":false,"id":729890,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ray, Andrea J.","contributorId":196935,"corporation":false,"usgs":false,"family":"Ray","given":"Andrea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":729891,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Reeves, Matt","contributorId":202843,"corporation":false,"usgs":false,"family":"Reeves","given":"Matt","affiliations":[],"preferred":false,"id":729892,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Travis, William","contributorId":202844,"corporation":false,"usgs":false,"family":"Travis","given":"William","affiliations":[],"preferred":false,"id":729893,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70195753,"text":"70195753 - 2018 - The geochemistry of loess: Asian and North American deposits compared","interactions":[],"lastModifiedDate":"2018-02-28T11:10:32","indexId":"70195753","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2184,"text":"Journal of Asian Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The geochemistry of loess: Asian and North American deposits compared","docAbstract":"<p><span>Loess is widely distributed over Asia and North America and constitutes one of the most important surficial deposits that serve as terrestrial records of the Quaternary. The oldest Pleistocene loess in China is likely ∼2.6 Ma, thus spanning much or all of the Pleistocene. In North America, most loess is no older than the penultimate glacial period, with the exception of Alaska, where the record may go back to ∼3.0 Ma. On both continents, loess deposits date primarily to glacial periods, and interglacial or interstadial periods are represented by paleosols. Both glacial and non-glacial sources of silts that comprise the bulk of loess deposits are found on both continents. Although loess has been considered to be representative of the average upper continental crust, there are regionally distinctive compositions of loess in both Asia and North America. Loess deposits in Asia from Yakutia, Tajikistan, and China have compositionally distinct major element compositions, due to varying abundances of silicate minerals, carbonate minerals, and clay minerals. In North America, loess in the Mississippi River valley, the Great Plains, and Alaska are also distinguishable with regard to major element composition that reflects highly diverse source sediments. Trace element geochemistry (Sc-Th-Zr and the rare earth elements) also shows regional diversity of loess bodies, in both Asia and North America. On both continents, most loess bodies show significant contributions from later-cycle, altered sedimentary rocks, as opposed to direct derivation from igneous rocks. Further, some loess bodies have detectable contributions from mafic igneous rocks as well as major contributions from average, upper-crustal, felsic rocks. Intercalated paleosols in loess sections show geochemical compositions that differ significantly from the underlying loess parent materials. Ratios of soluble-to-insoluble elements show depletions in paleosols due to chemical weathering losses of calcite, dolomite, plagioclase, mica, apatite, and smectite. In Asia and North America, the last interglacial paleosol is more weathered than equivalent modern soils, which could be due either to a climate that was warmer and more humid, a longer period of pedogenesis, or both. In Asia, early Pleistocene loess and paleosols are both more weathered than those from the middle and late Pleistocene, forming prior to a mid-Pleistocene aridification of Asia from uplift of the Tibetan Plateau. Understanding the geochemistry of loess and paleosols can tell us much about past atmospheric circulation, past temperature and moisture regimes, and even tectonic processes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jseaes.2017.10.032","usgsCitation":"Muhs, D.R., 2018, The geochemistry of loess: Asian and North American deposits compared: Journal of Asian Earth Sciences, v. 155, p. 81-115, https://doi.org/10.1016/j.jseaes.2017.10.032.","productDescription":"35 p.","startPage":"81","endPage":"115","ipdsId":"IP-091000","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":461011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jseaes.2017.10.032","text":"Publisher Index Page"},{"id":352125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"155","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0ec","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":140288,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":729791,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70195754,"text":"70195754 - 2018 - Future southcentral US wildfire probability due to climate change","interactions":[],"lastModifiedDate":"2018-03-26T13:47:27","indexId":"70195754","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Future southcentral US wildfire probability due to climate change","docAbstract":"<p><span>Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160&nbsp;cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10584-018-2156-8","usgsCitation":"Stambaugh, M.C., Guyette, R.P., Stroh, E.D., Struckhoff, M.A., and Whittier, J.B., 2018, Future southcentral US wildfire probability due to climate change: Climate Change, v. 147, no. 3-4, p. 617-631, https://doi.org/10.1007/s10584-018-2156-8.","productDescription":"15 p.","startPage":"617","endPage":"631","ipdsId":"IP-088702","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":352124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"3-4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0ea","contributors":{"authors":[{"text":"Stambaugh, Michael C.","contributorId":202826,"corporation":false,"usgs":false,"family":"Stambaugh","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":729793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guyette, Richard P.","contributorId":176595,"corporation":false,"usgs":false,"family":"Guyette","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":729794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stroh, Esther D. 0000-0003-4291-4647 estroh@usgs.gov","orcid":"https://orcid.org/0000-0003-4291-4647","contributorId":2813,"corporation":false,"usgs":true,"family":"Stroh","given":"Esther","email":"estroh@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":729792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Struckhoff, Matthew A. 0000-0002-4911-9956 mstruckhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":2095,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","email":"mstruckhoff@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":729795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whittier, Joanna B.","contributorId":53151,"corporation":false,"usgs":false,"family":"Whittier","given":"Joanna","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":729801,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70195690,"text":"70195690 - 2018 - The evolution of a colluvial hollow to a fluvial channel with periodic steps following two transformational disturbances: A wildfire and a historic flood","interactions":[],"lastModifiedDate":"2018-03-26T13:48:15","indexId":"70195690","displayToPublicDate":"2018-02-28T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The evolution of a colluvial hollow to a fluvial channel with periodic steps following two transformational disturbances: A wildfire and a historic flood","docAbstract":"The transition of a colluvial hollow to a fluvial channel with discrete steps was observed after two landscape-scale disturbances. The first disturbance, a high-severity wildfire, changed the catchment hydrology to favor overland flow, which incised a colluvial hollow, creating a channel in the same location. This incised channel became armored with cobbles and boulders following repeated post-wildfire overland flow events. Three years after the fire, a record rainstorm produced regional flooding and generated sufficient fluvial erosion and sorting to produce a fluvial channel with periodically spaced steps. An analysis of the step spacing shows that after the flood, newly formed steps retained a similar spacing to the topographic roughness spacing in the original colluvial hollow (prior to channelization). This suggests that despite a distinct change in channel form roughness and bedform morphology, the endogenous roughness periodicity was conserved. Variations in sediment erodibility helped to create the emergent steps as the largest particles ( >D84) remained immobile, becoming step features, and downstream soil was easily winnowed away.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2018.01.003","usgsCitation":"Rengers, F.K., McGuire, L., Ebel, B.A., and Tucker, G.E., 2018, The evolution of a colluvial hollow to a fluvial channel with periodic steps following two transformational disturbances: A wildfire and a historic flood: Geomorphology, v. 309, p. 121-130, https://doi.org/10.1016/j.geomorph.2018.01.003.","productDescription":"10 p.","startPage":"121","endPage":"130","ipdsId":"IP-092542","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2018.01.003","text":"Publisher Index Page"},{"id":352119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"309","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0f2","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":729707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke","contributorId":197027,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","affiliations":[],"preferred":false,"id":729708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tucker, G. E.","contributorId":195335,"corporation":false,"usgs":false,"family":"Tucker","given":"G.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":729710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194062,"text":"fs20173085 - 2018 - Assessment of undiscovered continuous oil and gas resources in the Domanik-type formations of the Volga-Ural Region Province, Russia, 2017","interactions":[],"lastModifiedDate":"2018-02-27T16:24:12","indexId":"fs20173085","displayToPublicDate":"2018-02-27T12:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3085","title":"Assessment of undiscovered continuous oil and gas resources in the Domanik-type formations of the Volga-Ural Region Province, Russia, 2017","docAbstract":"<p>Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable continuous resources of 2.8 billion barrels of oil and 34 trillion cubic feet of gas in the Domanik-type formations of the Volga-Ural Region Province, Russia.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173085","usgsCitation":"Klett, T.R., Brownfield, M.E., Finn, T.M., Gaswirth, S.B., Le, P.A., Leathers-Miller, H.M., Marra, K.R., Mercier, T.J., Pitman, J.K., Schenk, C.J., Tennyson, M.E., and Woodall, C.A., 2018, Assessment of undiscovered continuous oil and gas resources in the Domanik-type formations of the Volga-Ural Region Province, Russia, 2017: U.S. Geological Survey Fact Sheet 2017–3085, 2 p., https://doi.org/10.3133/fs20173085.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-091632","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":352044,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3085/fs20173085.pdf","text":"Report","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3085"},{"id":352045,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20163082","text":"Fact Sheet 2016–3082: ","linkHelpText":"Assessment of Undiscovered Continuous Oil and Gas Resources in the Dnieper-Donets Basin and North Carpathian Basin Provinces, Ukraine, Romania, Moldova, and Poland, 2015"},{"id":352043,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3085/coverthb.jpg"},{"id":352046,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20163083","text":"Fact Sheet 2016–3083: ","linkHelpText":"Assessment of Undiscovered Continuous Oil and Shale-Gas Resources in the Bazhenov Formation of the West Siberian Basin Province, Russia, 2016"}],"country":"Russia","otherGeospatial":"Volga-Ural Region Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              41,\n              47\n            ],\n            [\n              60,\n              47\n            ],\n            [\n              60,\n              63\n            ],\n            [\n              41,\n              63\n            ],\n            [\n              41,\n              47\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"http://energy.usgs.gov/\" data-mce-href=\"http://energy.usgs.gov/\">Central Energy Resources Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-939<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Introduction</li><li>Geologic Model</li><li>Undiscovered Resources Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2018-02-27","noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5afee714e4b0da30c1bfc0fa","contributors":{"authors":[{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":140834,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":721957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science 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Kristen R. 0000-0001-8027-5255 kmarra@usgs.gov","orcid":"https://orcid.org/0000-0001-8027-5255","contributorId":4844,"corporation":false,"usgs":true,"family":"Marra","given":"Kristen","email":"kmarra@usgs.gov","middleInitial":"R.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":721964,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":721965,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":721966,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science 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