We conducted a series of 7‐d toxicity tests with Ceriodaphnia dubia in dilutions of low‐hardness natural waters, which contained dissolved organic carbon (DOC) concentrations up to 10 mg/L. Stream waters were mixed with well water to achieve 2 target hardness levels (20 and 35 mg/L) and 4 DOC concentrations. Tests with aluminum (Al)‐spiked waters were conducted in a controlled CO2 atmosphere to maintain the pH at a range of 6.0 to 6.5. The results were used to estimate effect concentrations for survival and reproduction, expressed as total (unfiltered) Al concentrations. There were small differences in total‐Al thresholds between waters with 20 and 35 mg/L hardness, but effect concentrations for C. dubia survival (median lethal concentrations) and reproduction (effect concentrations, 20%) increased log‐linearly with increasing DOC concentrations in the range, 0.3 to 6 mg/L. Slopes of these regressions were similar to slopes from data used to revise the US Environmental Protection Agency water quality criterion for Al, but toxic effects in the present study occurred at total‐Al concentrations 8‐ to 10‐fold greater than toxicity values used for criteria development. This difference probably reflects the long equilibration (aging) times of Al test waters used in the present study (up to 192 h) compared with short (3‐h) equilibration times in other studies used for criteria development. These results confirm the importance of DOC as a control on Al toxicity in low‐hardness waters, but they also demonstrate that total‐Al concentrations are not predictive of Al toxicity, except under defined water quality (pH, hardness, DOC) and exposure conditions (e.g., aging of test waters).
","language":"English","publisher":"SETAC","doi":"10.1002/etc.4523","usgsCitation":"Besser, J.M., Cleveland, D.M., Ivey, C.D., and Blake, L., 2019, Toxicity of aluminum to Ceriodaphnia dubia in low-hardness waters as affected by natural dissolved organic matter: Environmental Toxicology and Chemistry, v. 38, no. 10, p. 2121-2127, https://doi.org/10.1002/etc.4523.","productDescription":"7 p.","startPage":"2121","endPage":"2127","ipdsId":"IP-103641","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437414,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99K901R","text":"USGS data release","linkHelpText":"Survival and growth of rainbow trout and warm water fishes exposed to selected contaminants"},{"id":437413,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6P1H","text":"USGS data release","linkHelpText":"Toxicity of aluminum to Ceriodaphnia dubia in natural waters as affected by hardness and dissolved organic matter"},{"id":367667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":771612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":771613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":771614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blake, Laura","contributorId":216576,"corporation":false,"usgs":false,"family":"Blake","given":"Laura","affiliations":[{"id":39479,"text":"U.S. Geological Survey, New England Water Science Center, Northborough, MA (Retired)","active":true,"usgs":false}],"preferred":false,"id":771615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203652,"text":"gip191 - 2019 - Coastal and marine science of the U.S. Geological Survey in Woods Hole, Massachusetts","interactions":[],"lastModifiedDate":"2019-07-01T11:00:27","indexId":"gip191","displayToPublicDate":"2019-06-21T09:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"191","displayTitle":"Coastal and Marine Science of the U.S. Geological Survey in Woods Hole, Massachusetts","title":"Coastal and marine science of the U.S. Geological Survey in Woods Hole, Massachusetts","docAbstract":"The U.S. Geological Survey (USGS) Woods Hole Coastal and Marine Science Center in Woods Hole, Massachusetts, is one of three centers serving the mission of the USGS Coastal and Marine Hazards and Resources Program (CMHRP). Since its authorization by Congress in 1962, the CMHRP has served as the primary Federal program for marine geology and physical science research and is responsible for the Nation’s entire coastal and marine landscape. The center’s staff of about 100 conducts scientific research in various locations throughout the United States to describe and understand the processes shaping coastal ecosystems, such as dunes, beaches, salt marshes, and lakes, and marine ecosystems, like the continental shelf and the deep sea. The center’s research products are used by other Federal agencies, State and local entities, private organizations, and the public to make informed decisions about the use, management, and protection of our coastal and marine resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip191","isbn":"978-1-4113-4309-2","collaboration":" ","usgsCitation":"Ernst, S., 2019, Coastal and marine science of the U.S. Geological Survey in Woods Hole, Massachusetts: U.S. Geological Survey General Information Product 191, 16 p., https://doi.org/10.3133/gip191.","productDescription":"16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-104389","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":364693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0191/coverthb.jpg"},{"id":364694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0191/gip191.pdf","text":"Report","size":"8.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 191"}],"country":"United States","state":"Massachsetts","city":"Woods Hole","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.65225005149841,\n 41.53251525939017\n ],\n [\n -70.65027594566345,\n 41.53251525939017\n ],\n [\n -70.65027594566345,\n 41.53384845596374\n ],\n [\n -70.65225005149841,\n 41.53384845596374\n ],\n [\n -70.65225005149841,\n 41.53251525939017\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
Information concerning the availability, use, and quality of water in Richland Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 41.73 million gallons per day (Mgal/d) of water were withdrawn in Richland Parish, including about 28.57 Mgal/d from groundwater sources and 13.17 Mgal/d from surface-water sources. Withdrawals for agricultural use, composed of general irrigation, rice irrigation, aquaculture, and livestock uses, accounted for about 88 percent (36.88 Mgal/d) of the total water withdrawn. Other categories of use included public supply, which accounted for about 10 percent (4.38 Mgal/d) of the total water withdrawn and rural domestic which accounted for about 1 percent (0.48 Mgal/d). Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicate that water withdrawals peaked in 1980 at more than 60 Mgal/d.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193005","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., 2019, Water resources of Richland Parish, Louisiana: U.S. Geological Survey Fact Sheet 2019–3005, 6 p., https://doi.org/10.3133/fs20193005.","productDescription":"Report: 6 p.; Data Release","onlineOnly":"N","ipdsId":"IP-081701","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":364648,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3005/coverthb.jpg"},{"id":364649,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3005/fs20193005.pdf","text":"Report","size":"723 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3005"},{"id":364650,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"}],"country":"United States","state":"Louisiana","county":"Richland 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Montane plant communities throughout the world have responded to changes in temperature regimes by shifting ranges upward in elevation, and made downslope movements to track shifts in climatic water balance. Organisms that cannot disperse or adapt biologically to projected climate scenarios in situ may decrease in distributional range and abundance over time. Restoration strategies will need to incorporate the habitat suitability of future predicted conditions to ensure long-term persistence. We propagated seedlings of three native Hawaiian montane plant species from high- (~2,500 m asl) and low-elevation (~1,900 m asl) sources, planted them in 8 common plots along a 500 m elevation gradient, and monitored microclimate at each plot for 20 weeks. We explored how temperature and precipitation influenced survival and growth differently among high- and low-elevation origin seedlings. Significantly more seedlings of only one species, Dodonaea viscosa, from high-elevation origin (75.2%) survived than seedlings from low-elevation origin (58.7%) across the entire elevation gradient. Origin also influenced survival in generalized linear mixed models that controlled for temperature, precipitation, and elevation in D. viscosa and Chenopodium oahuense. Survival increased with elevation and soil moisture for Sophora chrysophylla, while it decreased for the other two species. Responses to microclimate varied between the three montane plant species; there were no common patterns of growth or survival. Although limited in temporal scope, our experiment represents one of the few attempts to examine local adaptation to prospective climate scenarios and addresses challenges to restoration efforts within species’ current ranges.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0218516","usgsCitation":"Leopold, C., and Hess, S.C., 2019, Facilitating adaptation to climate change while restoring a montane plant community: PLoS ONE, v. 14, e0218516; 17 p., https://doi.org/10.1371/journal.pone.0218516.","productDescription":"e0218516; 17 p.","ipdsId":"IP-099400","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":467514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0218516","text":"Publisher Index Page"},{"id":364971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea Forest Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6227111816406,\n 19.796425363822532\n ],\n [\n -155.58013916015625,\n 19.755071768505005\n ],\n [\n -155.49087524414062,\n 19.703364698733452\n ],\n [\n -155.39886474609375,\n 19.73439094891939\n ],\n [\n -155.35491943359375,\n 19.826141627230633\n ],\n [\n -155.3631591796875,\n 19.898471023853403\n ],\n [\n -155.49087524414062,\n 19.93591434153325\n ],\n [\n -155.6227111816406,\n 19.796425363822532\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Leopold, Christina 0000-0003-0499-3196","orcid":"https://orcid.org/0000-0003-0499-3196","contributorId":178961,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","affiliations":[],"preferred":false,"id":764853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":764852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204098,"text":"70204098 - 2019 - Digital mapping of ecological land units using a nationally scalable modeling framework","interactions":[],"lastModifiedDate":"2019-07-05T15:40:57","indexId":"70204098","displayToPublicDate":"2019-06-20T15:37:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Digital mapping of ecological land units using a nationally scalable modeling framework","docAbstract":"Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.
","language":"English","publisher":"Alliance of Crop, Soil, and Environmental Science Societies (ACSESS)","doi":"10.2136/sssaj2018.09.0346","usgsCitation":"Maynard, J.J., Nauman, T.W., Salley, S.W., Bestelmeyer, B.T., Duniway, M.C., Talbot, C.J., and Brown, J.R., 2019, Digital mapping of ecological land units using a nationally scalable modeling framework, v. 83, no. 3, p. 666-686, https://doi.org/10.2136/sssaj2018.09.0346.","productDescription":"21 p.","startPage":"666","endPage":"686","ipdsId":"IP-102201","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":365309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chihuahuan Desert, Colorado Plateau","volume":"83","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maynard, Jonathan J.","contributorId":216782,"corporation":false,"usgs":false,"family":"Maynard","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[{"id":39514,"text":"USDA-Agricultural Resource Service, Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":765492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":765491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salley, Shawn W.","contributorId":216783,"corporation":false,"usgs":false,"family":"Salley","given":"Shawn","email":"","middleInitial":"W.","affiliations":[{"id":39514,"text":"USDA-Agricultural Resource Service, Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":765493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":765494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":765495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Curtis J.","contributorId":177878,"corporation":false,"usgs":false,"family":"Talbot","given":"Curtis","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Joel R.","contributorId":177880,"corporation":false,"usgs":false,"family":"Brown","given":"Joel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":765497,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203828,"text":"70203828 - 2019 - State of lake ecosystem conference sub Indicator: Prey fish","interactions":[],"lastModifiedDate":"2019-06-20T13:45:05","indexId":"70203828","displayToPublicDate":"2019-06-20T13:43:36","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"State of lake ecosystem conference sub Indicator: Prey fish","docAbstract":"Overall Assessment\nStatus: Fair\nTrends\n10-Year Trend: Unchanging\n\nLong-term Trend (1973-2017): Undetermined\n\nRationale: Great Lakes prey fish community status remains ”Fair” based on diversity and percent native species, but individual lake status varied. Both diversity and percent native metrics were classified as “Good” in Lake Superior, but “Poor” in Lake Ontario (Table 1). Lakes Huron and Michigan were both “Fair” (Table 1). In Lake Erie, diversity remained “Fair,” but the proportion native species shifted to “Poor,” resulting in an overall conservative classification of “Poor” (Table 1). Four of the five lakes had the same status as the previous reporting period, but Lake Erie shifted from “Fair” to “Poor.”\n\nAt the ten-year timescale, lake-specific trends were “Unchanging” in three lakes and “Deteriorating” in two lakes (Table 2). The trend for all lakes was therefore categorized as “Unchanging.” It is important to recognize six of the ten individual prey fish metrics did not trend up or down over the past ten years (Table 2). In Lake Erie, diversity and percent native were both “Deteriorating” and the Lake Michigan diversity was noted as “Deteriorating.” The only “Improving” trend was observed in the Lake Ontario where the percent of native species significantly increased from two to four percent of the total catch due to increased relative abundance of native Deepwater Sculpin (Weidel et al., 2017b).\n\nLong-term prey fish trends varied substantially with categorizations of “Improving,” “Deteriorating,” and\n\n“Undetermined,” and two lakes were “Unchanging” (Table 2). Because many of the long-term trends were in opposite directions, the overall classification for the long-term trend was “Undetermined.” In Lake Superior, both metrics have “Improving,” in Lake Michigan diversity is “Improving,” and in Lake Huron the percent native metric is “Improving” as non-native Alewife declined, and the relative importance of native Bloater increased. Alternatively, Lake Ontario long-term trends are “Deteriorating” as the proportion of Alewife in catches has increased. No long-term trends were detected in either of the Lake Erie metrics.\n\nPrey fish community changes are driven by changing ecosystem conditions including productivity changes, fluctuating predator composition and density, increasing water clarity, increasing water temperatures, and non-native species effects. While these driving factors are changing in similar directions across the region, because lakes are unique in their nutrient concentrations, morphometry, hydrology, and fish communities, the prey fish communities in each lake respond differently to changes in ecosystem drivers (Figure 1).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"State of the Great Lakes 2017 Technical Report","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Environment and Climate Change Canada, U.S. Environmental Protection Agency","usgsCitation":"Weidel, B., 2019, State of lake ecosystem conference sub Indicator: Prey fish, 9 p.","productDescription":"9 p.","startPage":"254","endPage":"262","ipdsId":"IP-101438","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":364842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364700,"type":{"id":15,"text":"Index Page"},"url":"https://binational.net/wp-content/uploads/2017/09/SOGL_2017_Technical_Report-EN.pdf"}],"country":"United States, Canada","geographicExtents":" {\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.0322265625,\n 41.21172151054787\n ],\n [\n -75.849609375,\n 41.21172151054787\n ],\n [\n -75.849609375,\n 49.1242192485914\n ],\n [\n -93.0322265625,\n 49.1242192485914\n ],\n [\n -93.0322265625,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":764314,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203905,"text":"70203905 - 2019 - Rapid broad-scale ecosystem changes and their consequences for biodiversity","interactions":[],"lastModifiedDate":"2019-06-25T08:10:11","indexId":"70203905","displayToPublicDate":"2019-06-20T13:30:32","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Rapid broad-scale ecosystem changes and their consequences for biodiversity","docAbstract":"Biodiversity contributes to and depends on ecosystem structure and associated function. Ecosystem structure, such as the amount and type of tree cover, influences fundamental abiotic variables such as near-ground incoming solar radiation (e.g., Royer et al. 2011), which in turn affects species and associated biodiversity (e.g., Trotter et al. 2008). In many systems, foundational, dominant, or keystone species (or species groups) are important in determining biodiversity, often because of their role in determining ecosystem structure. At spatial scales ranging from ecosystems to regions and larger, structural characteristics of vegetation or other structurally dominant organisms such as corals can influence species diversity, whether focused on alpha diversity (mean species diversity at the habitat level), beta diversity (differentiation among habitats), or gamma diversity (total species diversity across a landscape; Whittaker 1960). Climate change is projected to alter ecosystems at broad scales. In many cases, this will be due to extreme climate events such as droughts, floods and hurricanes, the effects of which can be rapid (IPCC 2012). Consequently, rapid broad-scale changes in ecosystems are of increasing concern. Climate change can directly affect species physiology, phenology, and distribution, as highlighted throughout this book (e.g. Citations to chapters in this volume to be added). Changes in one species can also affect other species (Cahill et al. 2013), particularly when dominant or co-dominant species that collectively provide habitat for other species are impacted (e.g. tree canopy architecture in many forest ecosystems; coral species via their reefs). Several rapid ecological changes have occurred at spatial scales that are sufficiently broad enough to represent biome changes (Gonzalez et al. 2010, Settele et al. 2014; Fig. 1 A). Rapid broad-scale changes differ from other patterns of vegetation dynamics in that they result in a “crash” in one or more populations (Breshears et al. 2008) over large areas of the affected region. Rapid broad-scale changes triggered by climate can include mega-fires; drought-triggered tree die-off and associated pest and pathogen outbreaks (Breshears et al. 2005, Safranyik et al. 2007); and hurricanes and wind-throw events (IPCC 2012, 2014). These rapid broad-scale changes can rapidly alter other factors such as resultant microclimate, which in turn can affect numerous other species and associated biodiversity (Royer et al. 2011; Fig. 1B). Many examples of broad-scale changes are documented in the paleoecology literature (Settele et al. 2014), although the temporal resolution at which those events can be resolved is relatively coarse (often centuries or longer). Such broad-scale changes documented in the paleoecology literature provide examples of types of change are likely to be of increasing concern in the future (Settele et al. 2014). Contemporary events have highlighted that broad-scale changes can occur rapidly (years or less; Breshears et al. 2005, Gonzalez et al. 2010, Settele et al. 2014). These rapid broad-scale changes will have important consequences for biodiversity beyond the direct impacts of climate change through the cascading effects associated with ecosystem structural and functional changes. The objective of this chapter is to alert readers to recent and projected rapid ecosystem changes and their potential consequences for biodiversity at ecosystem, landscape and regional scales.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biodiversity and climate change--Transforming the biosphere","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Yale University Press","usgsCitation":"Breshears, D.D., Field, J.P., Law, D.J., Villegas, J.C., Allen, C.D., Cobb, N.S., and Bradford, J.B., 2019, Rapid broad-scale ecosystem changes and their consequences for biodiversity, chap. of Biodiversity and climate change--Transforming the biosphere, p. 80-90.","productDescription":"11 p.","startPage":"80","endPage":"90","ipdsId":"IP-082686","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":364840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364830,"type":{"id":15,"text":"Index Page"},"url":"https://nau.pure.elsevier.com/en/publications/rapid-broad-scale-ecosystem-changes-and-their-consequences-for-bi"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":764670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, Jason P.","contributorId":216389,"corporation":false,"usgs":false,"family":"Field","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":764671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Law, Darin J.","contributorId":216390,"corporation":false,"usgs":false,"family":"Law","given":"Darin","email":"","middleInitial":"J.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":764672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villegas, Juan C.","contributorId":216391,"corporation":false,"usgs":false,"family":"Villegas","given":"Juan","email":"","middleInitial":"C.","affiliations":[{"id":39401,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA; Escuela Ambiental-Facultad de Ingenieria, Universidad de Antioquia, Medellin, Columbia","active":true,"usgs":false}],"preferred":false,"id":764673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":764675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cobb, Neil S.","contributorId":200776,"corporation":false,"usgs":false,"family":"Cobb","given":"Neil","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":764674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":764669,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203901,"text":"70203901 - 2019 - Determining Moho depth beneath sedimentary basins using regional Pn multiples","interactions":[],"lastModifiedDate":"2019-06-20T12:45:15","indexId":"70203901","displayToPublicDate":"2019-06-20T12:44:27","publicationYear":"2019","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":"Determining Moho depth beneath sedimentary basins using regional Pn multiples","docAbstract":"The study of the Moho beneath thick sedimentary basins involving natural earthquakes is challenging, as low‐velocity materials often cause strong reverberations that mask Moho signals. Here, we develop a method to determine the depth of the Moho by taking advantage of the presence of the sediments. The method utilizes the first Pn crustal multiple from regional earthquakes PnPn and its differential travel time with respect to Pn. PnPn is usually weak in amplitude; thus, it is difficult to identify in regions without a sedimentary cover. However, PnPn is significantly amplified in the presence of low‐velocity sediments because of an increase in the near‐surface P‐to‐P reflection coefficient. The arrival time, amplitude, and wave shape of PnPn, if normalized by the reference Pn, are insensitive to earthquake source parameters, such as focal mechanism and focal depth. We demonstrate the potential of this method using both 1D and 2D waveform simulations. Synthetic waveforms suggest that PmpPn and PnPmp (one Pn leg merges to PmP near the source or the receiver) largely contribute to the PnPn amplitudes, which depend on the near‐surface structure at their free‐surface P‐to‐P reflection points. We further validate the method with two field examples in the Imperial Valley; one is near the United States–Mexico border, and the other is in Oklahoma in the central United States. Both examples suggest that the method can be used to study the Moho either near the source or the receiver.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180325","usgsCitation":"Yu, C., Zhan, Z., Hauksson, E., Cochran, E.S., and Helmberger, D., 2019, Determining Moho depth beneath sedimentary basins using regional Pn multiples: Bulletin of the Seismological Society of America, v. 109, no. 3, p. 1171-1179, https://doi.org/10.1785/0120180325.","productDescription":"9 p.","startPage":"1171","endPage":"1179","ipdsId":"IP-103510","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":364837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Yu, C.","contributorId":216383,"corporation":false,"usgs":false,"family":"Yu","given":"C.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":764660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhan, Z.","contributorId":216384,"corporation":false,"usgs":false,"family":"Zhan","given":"Z.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":764661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hauksson, E.","contributorId":196003,"corporation":false,"usgs":false,"family":"Hauksson","given":"E.","affiliations":[],"preferred":false,"id":764662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":764659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Helmberger, D.","contributorId":216385,"corporation":false,"usgs":false,"family":"Helmberger","given":"D.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":764663,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203903,"text":"70203903 - 2019 - LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure","interactions":[],"lastModifiedDate":"2019-06-20T12:40:50","indexId":"70203903","displayToPublicDate":"2019-06-20T12:37:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure","docAbstract":"LANDFIRE (LF) National (2001) was the original product suite of the LANDFIRE program, which included Existing Vegetation Cover (EVC), Height (EVH), and Type (EVT). Subsequent refinements after feedback from data users resulted in updated products, referred to as LF 2001, that now served as LANDFIRE’s baseline datasets and are the basis for all subsequent LANDFIRE updates. These updates account for disturbances and vegetation transitions changes that may not represent current vegetation conditions. Therefore, in 2016 LANDFIRE initiated the Remap prototype to determine how to undertake a national-scale remap of the LANDFIRE primary vegetation datasets. EVC, EVH, and EVT were produced (circa 2015) via modeling for ecologically variable prototyping areas in the Pacific Northwest (NW) and Grand Canyon (GC). An error analysis within the GC suggested an overall accuracy of 52% (N = 800) for EVT, and a goodness of fit of 51% (N = 38) for percent cover (continuous EVC) and 53% (N = 38) for height (continuous EVH). The prototyping effort included a new 81-class map using the National Vegetation Classification (NVC) within the NW. This paper presents a narrative of the innovative methodologies in image processing and mapping used to create the new LANDFIRE vegetation products.","language":"English","publisher":"MDPI","doi":"10.3390/fire2020035","usgsCitation":"Picotte, J.J., Dockter, D., Long, J., Tolk, B.L., Davidson, A., and Peterson, B., 2019, LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure: Fire, v. 2, no. 2, p. 1-26, https://doi.org/10.3390/fire2020035.","productDescription":"26 p.","startPage":"1","endPage":"26","ipdsId":"IP-108452","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire2020035","text":"Publisher Index Page"},{"id":364836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364823,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2571-6255/2/2/35"}],"volume":"2","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":764692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dockter, Daryn 0000-0003-1914-8657","orcid":"https://orcid.org/0000-0003-1914-8657","contributorId":216392,"corporation":false,"usgs":false,"family":"Dockter","given":"Daryn","affiliations":[],"preferred":false,"id":764693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tolk, Brian L. 0000-0002-9060-0266 tolk@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":2992,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","email":"tolk@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davidson, Anne","contributorId":197967,"corporation":false,"usgs":false,"family":"Davidson","given":"Anne","email":"","affiliations":[],"preferred":false,"id":764696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203364,"text":"fs20193031 - 2019 - Assessment of undiscovered conventional oil and gas resources of the Grand Erg/Ahnet Province, Algeria, 2018","interactions":[],"lastModifiedDate":"2019-06-25T08:14:32","indexId":"fs20193031","displayToPublicDate":"2019-06-20T11:40:00","publicationYear":"2019","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":"2019-3031","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources of the Grand Erg/Ahnet Province, Algeria, 2018","title":"Assessment of undiscovered conventional oil and gas resources of the Grand Erg/Ahnet Province, Algeria, 2018","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 378 million barrels of oil and 7 trillion cubic feet of gas in the Grand Erg/Ahnet Province of Algeria.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193031","usgsCitation":"Schenk, C.J., Mercier, T.J., Tennyson, M.E., Finn, T.M., Le, P.A., Pitman, J.K., Drake, R.M., II, Brownfield, M.E., Gaswirth, S.B., and Leathers-Miller, H.M., 2019, Assessment of undiscovered conventional oil and gas resources of the Grand Erg/Ahnet Province, Algeria, 2018: U.S. Geological Survey Fact Sheet 2019–3031, 2 p., https://doi.org/10.3133/fs20193031.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-106641","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364818,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3031/fs20193031.pdf","text":"Report","size":"716 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3031"},{"id":364817,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3031/coverthb.jpg"}],"country":"Algeria","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[11.99951,23.47167],[8.57289,21.56566],[5.67757,19.60121],[4.26742,19.15527],[3.15813,19.05736],[3.14666,19.69358],[2.68359,19.85623],[2.06099,20.14223],[1.82323,20.61081],[-1.55005,22.79267],[-4.92334,24.97457],[-8.6844,27.39574],[-8.66512,27.58948],[-8.66559,27.65643],[-8.67412,28.84129],[-7.05923,29.57923],[-6.06063,29.7317],[-5.24213,30.00044],[-4.85965,30.50119],[-3.69044,30.89695],[-3.6475,31.63729],[-3.06898,31.7245],[-2.6166,32.09435],[-1.3079,32.26289],[-1.12455,32.65152],[-1.38805,32.86402],[-1.73345,33.91971],[-1.79299,34.52792],[-2.16991,35.1684],[-1.2086,35.71485],[-0.12745,35.88866],[0.50388,36.30127],[1.46692,36.60565],[3.1617,36.7839],[4.81576,36.86504],[5.32012,36.71652],[6.26182,37.11066],[7.33038,37.11838],[7.73708,36.88571],[8.42096,36.94643],[8.21782,36.43318],[8.37637,35.47988],[8.14098,34.65515],[7.52448,34.09738],[7.61264,33.34411],[8.43047,32.74834],[8.4391,32.50628],[9.0556,32.10269],[9.48214,30.30756],[9.80563,29.42464],[9.86,28.95999],[9.68388,28.14417],[9.75613,27.68826],[9.62906,27.14095],[9.71629,26.51221],[9.31941,26.09432],[9.91069,25.36545],[9.94826,24.93695],[10.30385,24.37931],[10.77136,24.56253],[11.56067,24.09791],[11.99951,23.47167]]]},\"properties\":{\"name\":\"Algeria\"}}]}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Birds select critical resources to meet needs that vary in response to spatial, temporal, and individual variation. As an example, perch or roost sites may be at locations that provide protection from predators, mobbing, or inclement weather. Applied to large, soaring predators, this theory suggests that they may select perch and roost sites near food resources or at sites where environmental updrafts develop. To test these theories, we characterized selection of nonflight locations throughout the annual cycle for Golden Eagles (Aquila chrysaetos) in eastern North America. We determined factors associated with selection of perching (daytime) and roosting (nighttime) sites by eagles by comparing land cover and topographic characteristics of GPS telemetry locations for eagles (used) with random (available) locations. We separately assessed selection for perch and roost sites during each of 4 seasons (winter, summer, and spring and fall migration). Golden Eagles showed different selection patterns for perching by season and age. Throughout the year, eagles selected perch sites on steep slopes. The direction these slopes faced differed among seasons, with eagles selecting south-facing slopes in summer and east-facing slopes during migration. Adults showed greater preferences for broadleaf forests in summer and for ridges in fall. Patterns of perch-site use were consistent with selection for sites that provide thermal protection and access to thermal updrafts. We found few patterns of selection for roosting sites. Our analysis provides insight into decision-making by a longdistance migrant across its annual cycle and throughout its geographic range, and thus into how resource selection changes seasonally.
The Mississippi River Valley alluvial aquifer (MRVA) caps a shallow system of aquifers and confining units in the Mississippi Alluvial Plain (MAP) that extends across 45,000 square miles of the midwestern and southern United States from Illinois to Louisiana. Irrigation water from the MRVA is required to sustain extensive crop production, which has resulted in groundwater-level declines since the late 1920s equal to nearly half of its thickness and in reduced baseflow of streams. Increased groundwater withdrawal for irrigation is expected to continue and threatens complete and irreversible aquifer dewatering (depletion). The exact amount of dewatering in the MRVA is uncertain because its vertical extent is poorly defined and the effects of groundwater withdrawal on the aquifer are not well understood. To provide stakeholders and managers with information and tools that promote understanding of the hydrogeologic framework of the MAP extent and its role in water-resource management, the U.S. Geological Survey (USGS) Water Availability and Use Science Program has funded a 5-year effort to assess groundwater availability and project future sustainability of water resources. Part of this study involves mapping the bottom altitude and thickness of the aquifer by using compilations of hydrogeologic data and applications of geostatistical analytics. Results of this mapping effort, presented here, are intended to enhance characterization of the shallow hydrogeologic framework and direct future airborne, ground-based, and waterborne geophysical surveys. Data used in support of the findings presented in this report are available as a USGS data release (https://doi.org/10.5066/P9D9XR5F).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3426","usgsCitation":"Torak, L.J., and Painter, J.A., 2019, Geostatistical estimation of the bottom altitude and thickness of the Mississippi River Valley alluvial aquifer: U.S. Geological Survey Scientific Investigations Map 3426, 2 sheets, https://doi.org/10.3133/sim3426.","productDescription":"2 Plates: 28 x 34 inches; Data Release","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-100531","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":364621,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D9XR5F","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Digital surfaces of the bottom altitude and thickness of the Mississippi River Valley alluvial aquifer and site data within the Mississippi Alluvial Plain project region"},{"id":364619,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3426/sim3426_sheet01.pdf","text":"Sheet 1","size":"1.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3426"},{"id":364620,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3426/sim3426_sheet02.pdf","text":"Sheet 2","size":"1.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3426"},{"id":364618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3426/coverthb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.054,30.4913 ], [ -94.054,38.5052 ], [ -86.5118,38.5052 ], [ -86.5118,30.4913 ], [ -94.054,30.4913 ] ] ] } } ] }","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road, Stephenson Center, Suite 129
Columbia, SC 29210
After 53 years of quiescence, Mount Agung awoke in August 2017, with intense seismicity, measurable ground deformation, and thermal anomalies in the summit crater. Although the seismic unrest peaked in late September and early October, the volcano did not start erupting until 21 November. The most intense explosive eruptions with accompanying rapid lava effusion occurred between 25 and 29 November. Smaller infrequent explosions and extrusions continue through the present (June 2019). The delay between intense unrest and eruption caused considerable challenges to emergency responders, local and national governmental agencies, and the population of Bali near the volcano, including over 140,000 evacuees. This paper provides an overview of the volcanic activity at Mount Agung from the viewpoint of the volcano observatory and other scientists responding to the volcanic crisis. We discuss the volcanic activity as well as key data streams used to track it. We provide evidence that magma intruded into the mid-crust in early 2017, and again in August of that year, prior to intrusion of an inferred dike between Mount Agung and Batur Caldera that initiated an earthquake swarm in late September. We summarize efforts to forecast the behavior of the volcano, to quantify exclusion zones for evacuations, and to work with emergency responders and other government agencies to make decisions during a complex and tense volcanic crisis.
1.Animal site fidelity structures space use, population demography and ultimately gene flow. Understanding the adaptive selection for site fidelity patterns provides a mechanistic understanding to both spatial and population processes. This can be achieved by linking space use with environmental variability (spatial and temporal) and demographic parameters. However, rarely is the environmental context that drives the selection for site fidelity behaviour fully considered.
2. We use ecological theory to understand whether the spatial and temporal variability in breeding site quality can explain the site fidelity behaviour and demographic patterns of Gunnison sage-grouse (Centrocercus minimus). We examined female site fidelity patterns across multiple spatial scales: proximity of consecutive year nest locations, space-use overlap within and across the breeding and brooding seasons, and fidelity to a breeding patch. We also examined the spatial and temporal variability in nest, chick, juvenile and adult survival.
3. We found Gunnison sage-grouse to be site faithful to their breeding patch, area of use within the patch and generally where they nest, suggesting an “Always Stay” site fidelity strategy. This is an optimal evolutionary strategy when site quality is unpredictable. Further, we found limited spatial variability in survival within age groups, suggesting little demographic benefit to moving among patches. We suggest Gunnison sage-grouse site fidelity is driven by the unpredictability of predation in a relatively homogeneous environment, the lack of benefits and likely costs to moving across landscape patches and leaving known lek and breeding/brooding areas.
4. Space use and demography are commonly studied separately. More so, site fidelity patterns are rarely framed in the context of ecological theory, beyond questions related to the win-stay:lose-switch rule. To move beyond describing patterns and understand the adaptive selection driving species movements and their demographic consequences require integrating movement, demography and environmental variability in a synthetic framework.
5. Site fidelity theory provides a coherent framework to simultaneously investigate the spatial and population ecology of animal populations. Using it to frame ecological questions will lead to a more mechanistic understanding of animal movement, spatial population structuring and meta-population dynamics.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.13390","usgsCitation":"Gerber, B.D., Hooten, M., Peck, C.P., Rice, M.B., Gammonley, J.H., Apa, A.D., and Davis, A.J., 2019, Extreme site fidelity as an optimal strategy in an unpredictable and homogeneous environment: Functional Ecology, v. 33, no. 9, p. 1695-1707, https://doi.org/10.1111/1365-2435.13390.","productDescription":"13 p.","startPage":"1695","endPage":"1707","ipdsId":"IP-093263","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467517,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.13390","text":"Publisher Index Page"},{"id":395249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Gunnison County, Saguache County","otherGeospatial":"Gunnison basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.1658935546875,\n 37.42252593456307\n ],\n [\n -104.732666015625,\n 37.42252593456307\n ],\n [\n -104.732666015625,\n 39.26203141523749\n ],\n [\n -108.1658935546875,\n 39.26203141523749\n ],\n [\n -108.1658935546875,\n 37.42252593456307\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"9","noUsgsAuthors":false,"publicationDate":"2019-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":832417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peck, Christopher P.","contributorId":198345,"corporation":false,"usgs":false,"family":"Peck","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":832418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gammonley, James H.","contributorId":272965,"corporation":false,"usgs":false,"family":"Gammonley","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":832420,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Apa, Anthony D.","contributorId":272966,"corporation":false,"usgs":false,"family":"Apa","given":"Anthony","email":"","middleInitial":"D.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":832421,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":832422,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203321,"text":"sir20195039 - 2019 - Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions","interactions":[],"lastModifiedDate":"2019-06-20T09:36:30","indexId":"sir20195039","displayToPublicDate":"2019-06-19T15:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5039","displayTitle":"Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions","title":"Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions","docAbstract":"A study was conducted by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of the Interior Southeast Climate Adaptation Science Center, to evaluate the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land-cover change for the period 1952–2099. The model simulations were used to compute the potential changes in hydrologic response and streamflow statistics across the Southeastern United States, using historical observations of climate and streamflow. Thirteen downscaled general circulation models with four representative concentration pathways were used to represent a range of potential future changes in climate (a total of 45 future simulations) from the Coupled Model Intercomparison Project Phase 5. The streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. An application of the Precipitation-Runoff Modeling System (included as part of the USGS National Hydrologic Model) was used to develop the hydrologic simulations. The results showed increases in air temperature across the study area, with the highest increases occurring in the northern part of the study area during July to September. The results showed a mix of increases and decreases in precipitation accumulation across the study area and across seasons, with decreases in precipitation accumulation across all seasons for the southwestern part of the study area. Actual evapotranspiration decreased for the southeastern part of the study area and increased for the northwestern part of the study area. The results showed general decreases in runoff across the study area, with increases in runoff in areas surrounding large metropolitan regions where potential future increases in impervious area occur. Results from a statistical analysis (Kolmogorov-Smirnov test) showed that the downscaled general circulation models generally have more skill in producing historical streamflow statistics in the duration and magnitude categories and less skill in producing historical streamflow statistics in the frequency, rate of change, and timing categories for this study area. The potential changes in the streamflow statistics and the results of the Kolmogorov-Smirnov test are available through the GCPO LCC Conservation Planning Atlas, an online science-based mapping platform built specifically for land managers and planners.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195039","collaboration":"Prepared in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative and the Department of the Interior Southeast Climate Adaptation Science Center","usgsCitation":"LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions: U.S. Geological Survey Scientific Investigations Report 2019–5039, 83 p., https://doi.org/10.3133/sir20195039.","productDescription":"Report: x, 83 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075743","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":364749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5039/coverthb.jpg"},{"id":364750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5039/sir20195039.pdf","text":"Report","size":"63.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5039"},{"id":364806,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X56PH","text":"USGS data release","description":"USGS data release","linkHelpText":"Model Input and Output for Hydrologic Simulations of the Southeastern United States for Historical and Future Conditions"}],"country":"United States","state":"Alabama, Arkansas, Florida, Georgia, Illinois, Kansas, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, Tennessee, Texas, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.515625,\n 40.51379915504413\n ],\n [\n -95.185546875,\n 38.89103282648846\n ],\n [\n -95.2734375,\n 37.37015718405753\n ],\n [\n -97.294921875,\n 35.96022296929667\n ],\n [\n -97.646484375,\n 35.17380831799959\n ],\n [\n -95.97656249999999,\n 33.578014746143985\n ],\n [\n -95.537109375,\n 32.32427558887655\n ],\n [\n -96.328125,\n 31.50362930577303\n ],\n [\n -97.734375,\n 30.977609093348686\n ],\n [\n -96.85546875,\n 30.600093873550072\n ],\n [\n -96.240234375,\n 28.536274512989916\n ],\n [\n -93.69140625,\n 29.38217507514529\n ],\n [\n -91.93359375,\n 29.305561325527698\n ],\n [\n -90.087890625,\n 29.075375179558346\n ],\n [\n -89.12109375,\n 29.075375179558346\n ],\n [\n -89.47265625,\n 29.916852233070173\n ],\n [\n -88.24218749999999,\n 30.372875188118016\n ],\n [\n -86.484375,\n 30.372875188118016\n ],\n [\n -85.166015625,\n 29.6880527498568\n ],\n [\n -84.0234375,\n 29.916852233070173\n ],\n [\n -82.880859375,\n 29.38217507514529\n ],\n [\n -81.9140625,\n 28.998531814051795\n ],\n [\n -82.44140625,\n 29.611670115197377\n ],\n [\n -81.474609375,\n 31.42866311735861\n ],\n [\n -83.49609375,\n 34.74161249883172\n ],\n [\n -81.9140625,\n 35.24561909420681\n ],\n [\n -81.9140625,\n 37.3002752813443\n ],\n [\n -85.95703125,\n 35.53222622770337\n ],\n [\n -88.41796875,\n 37.020098201368114\n ],\n [\n -89.82421875,\n 39.232253141714885\n ],\n [\n -91.7578125,\n 39.232253141714885\n ],\n [\n -93.515625,\n 40.51379915504413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
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720 Gracern Road
Stephenson Center, Suite 129
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The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, led hydrologic and hydraulic analyses within the Clear Fork Mohican River Basin in and near Bellville, Ohio. The analyses included the development of digital flood-inundation maps for an approximately 2.5-mile reach of the Clear Fork Mohican River and the development of a precipitation-runoff model for a portion of the Clear Fork Mohican River Basin.
Data collection for the study involved the installation and operation of 2 streamgages (Clear Fork Mohican River at Bellville, Ohio, and Cedar Fork above Bellville, Ohio); 1 lake-level gage (Clear Fork Reservoir near Lexington, Ohio); 2 precipitation gages (Clear Fork Reservoir near Lexington, Ohio, and Rain Gage at Cedar Fork above Bellville, Ohio); and 12 submersible pressure transducers on Clear Fork Mohican River and 4 of its tributaries. Data collection also included field surveys of hydraulic structures and channel cross sections.
Flood profiles were computed for the 2.5-mile reach of the Clear Fork Mohican River by means of a one-dimensional step-backwater model. The model was calibrated to 16 measured events and to a portion (stages 9 to 11 feet) of the current stage-streamflow relation at the USGS streamgage Clear Fork Mohican River at Bellville, Ohio, and to stage recorded at a submersible pressure transducer site near the downstream study limit. After calibration the step-backwater model was used to compute nine flood profiles for stages ranging from 9 to 17 feet. The flood profiles were then used in combination with a digital elevation model to delineate the area that would be inundated at each stage.
A precipitation-runoff model was developed and calibrated using data from the streamgage, precipitation gage, and 11 submersible pressure transducers. The modeling included data during 10 runoff events that were used for model calibration and validation, with focus on 6 events. The Nash-Sutcliffe model efficiency coefficients for six peak streamflow events ranged from 0.459 to 0.851.
The models produced by this study can be used to assess possible flood mitigation options and define flood hazard areas that could contribute to the protection of life and property. The availability of flood-inundation maps, internet information from USGS streamgages, and forecasted stages from the National Weather Service could provide emergency management personnel and residents with information on forecasting floods, appropriate flood response activities, and post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195017","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District and Richland County","usgsCitation":"Ostheimer, C.J., and Huitger, C.A., 2019, Development of a flood-inundation map library and precipitation-runoff modeling for the Clear Fork Mohican River in and near Bellville, Ohio: U.S. Geological Survey Scientific Investigations Report 2019–5017, 34 p., including 1 appendix, https://doi.org/10.3133/sir20195017.","productDescription":"Report, iv, 34 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-100979","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":364753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5017/coverthb.jpg"},{"id":364755,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95NMIDF","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data sets for flood-inundation maps in and near Bellville, Ohio"},{"id":364754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5017/sir20195017.pdf","text":"Report","size":"17.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5017"}],"country":"United States","state":"Ohio","county":"Richland County","city":"Bellville","otherGeospatial":"Clear Fork Mohican River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.39265441894531,\n 40.58475654701271\n ],\n [\n -82.40020751953125,\n 40.603526799885884\n ],\n [\n -82.52792358398436,\n 40.660847697284815\n ],\n [\n -82.57598876953125,\n 40.70875101828792\n ],\n [\n -82.62405395507812,\n 40.758700379161006\n ],\n [\n -82.68722534179688,\n 40.76182096906601\n ],\n [\n -82.72430419921875,\n 40.71916022743469\n ],\n [\n -82.71194458007812,\n 40.658764163202925\n ],\n [\n -82.49153137207031,\n 40.58345286156245\n ],\n [\n -82.41462707519531,\n 40.56937143958841\n ],\n [\n -82.39471435546875,\n 40.57328324298059\n ],\n [\n -82.39265441894531,\n 40.58475654701271\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Ste 100
Columbus, OH 43229
We tested extended‐spectrum β‐lactamase producing bacteria from wild gulls (Larusspp.) sampled in 2009 for the presence of mcr‐1. We report the detection of mcr‐1 and describe genome characteristics of four Escherichia coli and one Klebsiella pneumoniaeisolate from Spain and Portugal that also exhibited colistin resistance. Results represent the earliest evidence for colistin‐resistant bacteria in European wildlife.
","language":"English","publisher":"Wiley","doi":"10.1111/1758-2229.12779","usgsCitation":"Ahlstrom, C., Ramey, A.M., Woksepp, H., and Bonnedahl, J., 2019, Early emergence of mcr-1-positive Enterobacteriaceae in gulls from Spain and Portugal: Environmental Microbiology Reports, v. 11, no. 5, p. 669-671, https://doi.org/10.1111/1758-2229.12779.","productDescription":"3 p.","startPage":"669","endPage":"671","ipdsId":"IP-098161","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1758-2229.12779","text":"Publisher Index Page"},{"id":365395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Portugal, Spain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":765725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":765726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woksepp, Hanna","contributorId":207263,"corporation":false,"usgs":false,"family":"Woksepp","given":"Hanna","email":"","affiliations":[],"preferred":false,"id":765727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":765728,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204662,"text":"70204662 - 2019 - Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization","interactions":[],"lastModifiedDate":"2019-08-09T10:20:55","indexId":"70204662","displayToPublicDate":"2019-06-19T13:40:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization","docAbstract":"Kīlauea Volcano is underlain by a complex, laterally-extensive magmatic plumbing system. Although in recent decades it has mainly erupted through vents along the middle East Rift Zone and summit caldera, eruptions can occur anywhere along its two laterally extensive rift zones, as demonstrated by the dramatic eruptive activity of 2018. Forecasting eruptive activity requires an understanding of whether an episode of volcano-seismic unrest at Kīlauea or a similar volcano is caused directly at the edges of an active magmatic intrusion or reservoir, or in a volume of wall rock at a distance from the intrusion. Seismic unrest in Kīlauea’s Upper East Rift Zone (UERZ) has to date been interpreted as the result of either magma intrusion in this region of the volcano or of stresses due to seaward flank migration. However, recent observations suggest that UERZ seismicity may result from variable pressurization of Kīlauea’s summit magma system. We analyze seismic and deformation (multi-temporal InSAR and GPS) data during a period of variable summit deformation and UERZ seismicity in mid- to late-2007 and calculate Coulomb stress changes on UERZ faults due to modeled summit inflation or deflation. UERZ seismicity during our study period can be explained entirely by stresses arising from pressure changes within Kīlauea’s two summit reservoirs. Furthermore, a comparison of UERZ fault plane solutions (FPS) calculated for this study to published UERZ FPS for previous periods suggests the UERZ has undergone a transition from a mechanically-strong, discontinuous and immature magma transport system to a mature, mechanically-weak and fully-connected transport system over the course of the 1983-2018 eruption.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G46000.1","usgsCitation":"Wauthier, C., Roman, D.C., and Poland, M.P., 2019, Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization: Geology, 5 p., https://doi.org/10.1130/G46000.1.","productDescription":"5 p.","ipdsId":"IP-106972","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":366397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wauthier, Christelle","contributorId":176224,"corporation":false,"usgs":false,"family":"Wauthier","given":"Christelle","email":"","affiliations":[],"preferred":false,"id":767965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana C.","contributorId":176225,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":767966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":767964,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204754,"text":"70204754 - 2019 - Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall","interactions":[],"lastModifiedDate":"2019-08-29T12:08:30","indexId":"70204754","displayToPublicDate":"2019-06-19T10:43:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall","docAbstract":"Episodically to continuously active slow-moving landslides are driven by precipitation.\n Climate change, which is altering both the frequency and magnitude of precipitation world21\nwide, is therefore predicted to have a major impact on landslides. Here we examine the\n behavior of hundreds of slow-moving landslides in northern California in response to large\n changes in annual precipitation that occurred between 2016 and 2018. We quantify the\n landslide displacement using repeat-pass radar interferometry and pixel offset tracking\n techniques on a novel dataset from the airborne NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar. We found that 312 landslides were moving due to extreme\n rainfall during 2017, compared to 119 during 2016, which was the final year of a historic\n multi-year drought. However, with a return to below average rainfall in 2018, only 146\n landslides remained in motion. The increased number of landslides during 2017 was primarily accommodated by landslides that were smaller than the landslides that remained\n active between 2016 and 2018. Furthermore, by examining a subset of 51 landslides, we\nfound that 49 had increased velocities during 2017 when compared to 2016. Our results\nshow that slow-moving landslides are sensitive to large changes in annual precipitation,\n particularly the smaller and thinner landslides that likely experience larger basal pore\nwater pressure changes. Based on climate model predictions for the next century in California, which include increases in annual precipitation and increases in the frequency\n of dry-to-wet extremes, we hypothesize that there will be an overall increase in landslide\n activity.","language":"English","publisher":"Wiley","doi":"10.1029/2019JF005035","usgsCitation":"Handwerger, A.L., Fielding, E.J., Huang, M., Bennett, G.L., Liang, C., and Schulz, W.H., 2019, Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall: Journal of Geophysical Research: Earth Surface, v. 24, no. 7, p. 1782-1797, https://doi.org/10.1029/2019JF005035.","productDescription":"16 p.","startPage":"1782","endPage":"1797","ipdsId":"IP-108822","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467519,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019jf005035","text":"External Repository"},{"id":366567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Northern California Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.12628173828126,\n 40.686886382151116\n ],\n [\n -123.24737548828124,\n 39.614152077002664\n ],\n [\n -122.64587402343751,\n 39.743098286948275\n ],\n [\n -123.55499267578125,\n 40.79301881008675\n ],\n [\n -124.12628173828126,\n 40.686886382151116\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Handwerger, Alexander L.","contributorId":218095,"corporation":false,"usgs":false,"family":"Handwerger","given":"Alexander","email":"","middleInitial":"L.","affiliations":[{"id":39742,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.","active":true,"usgs":false}],"preferred":false,"id":768312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fielding, Eric J.","contributorId":218096,"corporation":false,"usgs":false,"family":"Fielding","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":39742,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.","active":true,"usgs":false}],"preferred":false,"id":768313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Mong-Han","contributorId":192699,"corporation":false,"usgs":false,"family":"Huang","given":"Mong-Han","email":"","affiliations":[],"preferred":false,"id":768314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Georgina L.","contributorId":218097,"corporation":false,"usgs":false,"family":"Bennett","given":"Georgina","email":"","middleInitial":"L.","affiliations":[{"id":39743,"text":"School of Environmental Sciences, University of East Anglia, Norwich, UK.","active":true,"usgs":false}],"preferred":false,"id":768315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liang, Cunren","contributorId":172629,"corporation":false,"usgs":false,"family":"Liang","given":"Cunren","email":"","affiliations":[],"preferred":false,"id":768316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":768317,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223130,"text":"70223130 - 2019 - Wildlife value orientation of landowners from five states in the upper midwest, USA","interactions":[],"lastModifiedDate":"2021-08-12T13:19:32.236053","indexId":"70223130","displayToPublicDate":"2019-06-19T08:16:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife value orientation of landowners from five states in the upper midwest, USA","docAbstract":"Five Upper Midwest states (Montana, North Dakota, South Dakota, Minnesota, Iowa) participated in a Plains and Prairie Landscape Conservation Cooperative (PPP-LCC) funded survey of landowners. All five surveys included a 13-item wildlife value orientation (WVO) scale to provide insight into how landowners in this region make land use decisions that affect wildlife habitat. Most landowners were utilitarian (59%), 11% were identified as mutualists, and pluralists and distanced landowners were 15% each. Pluralist and mutualist landowners placed more importance on wildlife considerations when making land use decisions compared to utilitarian and distanced landowners. However, landowners’ WVO was not related to their participation in United States Department of Agriculture (USDA) Farm Bill conservation programs. The proportion of WVO types among landowners varied considerably by age cohort. The proportion of utilitarians was highest for landowners born during the 1970s age cohorts and has since declined.
The United States’ supply of critical minerals has been a concern and a source of potential strategic vulnerabilities for U.S. economic and national security interests for decades (for example, see Strategic and Critical Minerals Stockpiling Act, 1939). More recently, with the rapid increase in the types of materials being used in advanced technologies (Fortier et al. 2018a), and geopolitical events surrounding the supply of rare earth elements (Ting and Seaman, 2013), among other developments, the critical minerals issue has again achieved a high level of visibility within the U.S. government (Executive Order 13817 (2017)).
","language":"English","publisher":"Society for Mining, Metallurgy & Exploration","usgsCitation":"Fortier, S.M., Hammarstrom, J.M., Ryker, S.J., Day, W.C., and Seal,, R., 2019, USGS critical minerals review: Mining Engineering, v. 71, no. 5, p. 35-47.","productDescription":"13 p.","startPage":"35","endPage":"47","ipdsId":"IP-107221","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":368760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368757,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=8926&page=35","linkFileType":{"id":5,"text":"html"}}],"volume":"71","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fortier, Steven M. 0000-0001-8123-5749","orcid":"https://orcid.org/0000-0001-8123-5749","contributorId":202406,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":774203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":774204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryker, Sarah J. 0000-0002-1004-5611 sryker@usgs.gov","orcid":"https://orcid.org/0000-0002-1004-5611","contributorId":4100,"corporation":false,"usgs":true,"family":"Ryker","given":"Sarah","email":"sryker@usgs.gov","middleInitial":"J.","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"preferred":true,"id":774205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":774206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":774207,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204102,"text":"70204102 - 2019 - Ten-million years of activity within the Eastern California Shear Zone from U-Pb dating of fault-zone opal","interactions":[],"lastModifiedDate":"2019-07-05T15:54:31","indexId":"70204102","displayToPublicDate":"2019-06-18T15:42:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ten-million years of activity within the Eastern California Shear Zone from U-Pb dating of fault-zone opal","docAbstract":"Reconstructions of long-term fault activity are essential for understanding both the mechanisms controlling fault behavior and accurate earthquake hazard assessments. Increasing evidence for temporal variations in strain accumulation suggests non-uniform strain rates over a range of historic to geologic timescales. The paucity of long-term records of fault activity has limited our ability to resolve these variations. We present a method for constraining long-term fault activity based on U-Pb dating of fault-related opal from secondary fault segments within the Eastern California Shear Zone (ECSZ). The presence of sheared and breccia-cemented opaline silica within well-exposed faults at near-surface conditions suggest that opal formation is associated with high-magnitude earthquakes capable of surface rupture (>6 M). Temporal constraints from sheared syntectonic opal (n=74) on related secondary faults from this study provide new insights on the timing of fault initiation, reactivation, and longevity. The oldest dates obtained indicate that ECSZ activity commenced at or before 10 Ma. Multiple deformation events dated within a single structure on episodically deposited and sheared opal (up to six generations), demonstrate that fault reactivation occurred over 105 year timescales (0.7-0.1 Ma). Relative probabilities of dated deformation events can be used to evaluate changes in fault activity in the past 2.5 Ma (n=60). This analysis indicates enhanced fault activity starting at 2 Ma and peaking around 1 Ma, possibly due to fault-interactions and distribution of deformation between the ECSZ and the San Andreas Fault.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2019.05.047","usgsCitation":"Nuriel, P., Miller, D., Schmidt, K.M., Coble, M.A., and Maher, K., 2019, Ten-million years of activity within the Eastern California Shear Zone from U-Pb dating of fault-zone opal: Earth and Planetary Science Letters, v. 521, p. 37-45, https://doi.org/10.1016/j.epsl.2019.05.047.","productDescription":"9 p.","startPage":"37","endPage":"45","ipdsId":"IP-076946","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2019.05.047","text":"Publisher Index Page"},{"id":365312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.7841796875,\n 32.91648534731439\n ],\n [\n -114.82910156249999,\n 32.91648534731439\n ],\n [\n -114.82910156249999,\n 34.84987503195418\n ],\n [\n -118.7841796875,\n 34.84987503195418\n ],\n [\n -118.7841796875,\n 32.91648534731439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"521","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nuriel, Perach","contributorId":201387,"corporation":false,"usgs":false,"family":"Nuriel","given":"Perach","email":"","affiliations":[],"preferred":false,"id":765517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coble, Matthew A.","contributorId":200372,"corporation":false,"usgs":false,"family":"Coble","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":765519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Kate","contributorId":190440,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","email":"","affiliations":[],"preferred":false,"id":765520,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203723,"text":"ofr20191067 - 2019 - Monitoring protocol development and assessment for narrowly endemic toads in Nevada, 2018","interactions":[],"lastModifiedDate":"2019-06-20T09:27:25","indexId":"ofr20191067","displayToPublicDate":"2019-06-18T15:33:07","publicationYear":"2019","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":"2019-1067","displayTitle":"Monitoring Protocol Development and Assessment for Narrowly Endemic Toads in Nevada, 2018","title":"Monitoring protocol development and assessment for narrowly endemic toads in Nevada, 2018","docAbstract":"Several species and subspecies of toads are endemic to small spring systems in the Great Basin, and their restricted ranges and habitat extent make them vulnerable to environmental perturbations. Very little is known about several of these toad populations, so a group of stakeholders including the U.S. Geological Survey, U.S. Fish and Wildlife Service, Bureau of Land Management, Nevada Department of Wildlife, the U.S. Navy, U.S. Forest Service, and Oregon State University met to discuss information needs on these populations and to develop a monitoring protocol that would detect population changes over time. In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey implemented the proposed survey protocol, a multi-state occupancy design, for three sites: Dixie Valley, Railroad Valley, and Hot Creek, to evaluate its ease of implementation and effectiveness. We found that the multi-state occupancy protocol worked well in the Dixie Valley and, with some refinement, would likely work well in the Railroad Valley. We suggest that capture-mark-recapture of adults might be a more effective approach at Hot Creek. For most life stages of most populations, detection probabilities were positively related to survey duration up to 20 minutes, and the best time of day to conduct surveys varied by life stage and population. We make population-specific suggestions for the number of surveys and their timing and duration. Annual surveys using the suggested survey protocols will likely allow estimation of trends in the proportion of area of each population existing in different population states (occupied, occupied with evidence of reproduction, and unoccupied) and in most cases can be readily implemented with minimal training or handling of toads.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191067","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Halstead, B.J., Kleeman, P.M., Duarte, A., Rose, J.P., Urquhart, K., Mellison, C., Guadalupe, K., Cota, M., Van Horne, R., Killion, A., and Ruehling, K., 2019, Monitoring protocol development and assessment for narrowly endemic toads in Nevada, 2018: U.S. Geological Survey Open-File Report 2019–1067, 28 p., https://doi.org/10.3133/ofr20191067.","productDescription":"Report: vi, 28 p.; Data release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-106829","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":364708,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1067/coverthb.jpg"},{"id":364707,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1067/ofr20191067.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1067"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Dixie Valeey, Great Basin Watershed, Hot Creek, Railroad Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.7080078125,\n 35.17380831799959\n ],\n [\n -114.93896484374999,\n 35.42486791930558\n ],\n [\n -114.85107421875,\n 35.871246850027966\n ],\n [\n -114.36767578124999,\n 36.4566360115962\n ],\n [\n -113.75244140624999,\n 36.87962060502676\n ],\n [\n -112.7197265625,\n 37.71859032558816\n ],\n [\n -111.51123046875,\n 39.45316112807394\n ],\n [\n -112.0166015625,\n 41.934976500546604\n ],\n [\n -112.5,\n 42.52069952914966\n ],\n [\n -113.9501953125,\n 42.61779143282346\n ],\n [\n -115.400390625,\n 42.09822241118974\n ],\n [\n -116.45507812500001,\n 41.672911819602085\n ],\n [\n -117.90527343750001,\n 42.293564192170095\n ],\n [\n -119.88281249999999,\n 42.58544425738491\n ],\n [\n -120.32226562500001,\n 41.705728515237524\n ],\n [\n -120.32226562500001,\n 40.613952441166596\n ],\n [\n -120.0146484375,\n 39.232253141714885\n ],\n [\n -119.794921875,\n 38.47939467327645\n ],\n [\n -118.43261718749999,\n 37.996162679728116\n ],\n [\n -117.46582031249999,\n 36.98500309285596\n ],\n [\n -116.8505859375,\n 36.20882309283712\n ],\n [\n -115.7080078125,\n 35.17380831799959\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819