{"pageNumber":"223","pageRowStart":"5550","pageSize":"25","recordCount":41062,"records":[{"id":70225600,"text":"70225600 - 2021 - Climate change effects on North American fish and fisheries to inform adaptation strategies","interactions":[],"lastModifiedDate":"2021-10-27T12:25:27.099518","indexId":"70225600","displayToPublicDate":"2021-08-16T07:22:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Climate change effects on North American fish and fisheries to inform adaptation strategies","docAbstract":"

Climate change is a global persistent threat to fish and fish habitats throughout North America. Climate-induced modification of environmental regimes, including changes in streamflow, water temperature, salinity, storm surges, and habitat connectivity can change fish physiology, disrupt spawning cues, cause fish extinctions and invasions, and alter fish community structure. Reducing greenhouse emissions remains the primary mechanism to slow the pace of climate change, but local and regional management agencies and stakeholders have developed an arsenal of adaptation strategies to help partially mitigate the effects of climate change on fish. We summarize common stressors posed by climate change in North America, including (1) increased water temperature, (2) changes in precipitation, (3) sea level rise, and (4) ocean acidification, and present potential adaptation strategies that fishery professionals may apply to help vulnerable fish and fisheries cope with a changing climate. Although our adaptation strategies are primarily from North America, they have broader geographic applicability to fish and aquatic biota in other jurisdictions. These strategies provide opportunities for managers to mitigate the effects of climate change on fish and fish habitat while needed global policies to reduce greenhouse gas emissions emerge, which may offer more lasting solutions.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10668","usgsCitation":"Paukert, C.P., Olden, J., Lynch, A., Brashears, D., Chambers, R.C., Chu, C., Daly, M., Dibble, K.L., Falke, J.A., Issak, D., Jacobson, P.C., Jensen, O.P., and Munroe, D., 2021, Climate change effects on North American fish and fisheries to inform adaptation strategies: Fisheries Magazine, v. 9, no. 46, p. 449-464, https://doi.org/10.1002/fsh.10668.","productDescription":"16 p.","startPage":"449","endPage":"464","ipdsId":"IP-125386","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451161,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/fsh.10668","text":"External Repository"},{"id":391006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.1015625,\n 7.36246686553575\n ],\n [\n -81.9140625,\n 17.97873309555617\n ],\n [\n -78.3984375,\n 24.5271348225978\n ],\n [\n -56.6015625,\n 45.089035564831036\n ],\n [\n -54.140625,\n 53.9560855309879\n ],\n [\n -62.57812500000001,\n 64.01449619484472\n ],\n [\n -94.21875,\n 71.30079291637452\n ],\n [\n -135,\n 73.52839948765174\n ],\n [\n -163.4765625,\n 70.72897946208789\n ],\n [\n -168.046875,\n 65.5129625532949\n ],\n [\n -163.4765625,\n 58.07787626787517\n ],\n [\n -157.1484375,\n 54.77534585936447\n ],\n [\n -138.1640625,\n 51.39920565355378\n ],\n [\n -128.32031249999997,\n 41.244772343082076\n ],\n [\n -114.60937499999999,\n 23.241346102386135\n ],\n [\n -95.97656249999999,\n 11.178401873711785\n ],\n [\n -82.96875,\n 5.61598581915534\n ],\n [\n -79.1015625,\n 7.36246686553575\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"46","noUsgsAuthors":false,"publicationDate":"2021-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":825786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":825787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":216203,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":825788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brashears, Dave","contributorId":268062,"corporation":false,"usgs":false,"family":"Brashears","given":"Dave","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":825789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chambers, R. 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Phenology is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and natural resource management and decision-making.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2021.101400","usgsCitation":"Morisette, J., Duffy, K.A., Weltzin, J., Browning, D.M., Marsh, L.R., Friesz, A., Zachmann, L.J., Enns, K., Landau, V.A., Gerst, K.L., Crimmins, T.M., Jones, K.D., Chang, T., Miller, B.W., Maiersperger, T., and Richardson, A.D., 2021, PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data: Ecological Informatics, v. 65, 101400, 11 p., https://doi.org/10.1016/j.ecoinf.2021.101400.","productDescription":"101400, 11 p.","ipdsId":"IP-129986","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2021.101400","text":"Publisher Index 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In Yellowstone Lake, predation by invasive Lake Trout Salvelinus namaycush has caused significant abundance declines in native Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri. Lake Trout suppression has been ongoing since 1995; assessment and simulation modeling are used to measure suppression effectiveness and guide efforts. Lake Trout reproduction demographics are linked to these modeling efforts via quantification of the population stock–recruitment relationship. To improve estimation of this relationship for Lake Trout in Yellowstone Lake, we assessed reproduction demographics by quantifying spawning periodicity, size at maturity, and female fecundity. Histological assessment suggested that females with a gonadosomatic index (GSI) >3.0 and males with a GSI >1.0 were capable of spawning. Approximately 65% of mature females appeared to have spawned on an annual cycle. In 2015, the mean absolute and relative fecundities were 4,612 eggs and 1,535 eggs/kg, respectively; temporal differences in relative fecundity (1996, 2006, 2007, and 2015) were not statistically significant. Lake Trout population fecundity has declined from a peak in 2010 due to reduction in abundance of spawners. The estimated population fecundity of approximately 4.7 million eggs in 2020 represents an 81% decline from the mean estimate of previous samples and an 87% reduction from peak population fecundity. Despite declines in population fecundity, age-2 recruitment has increased in recent years; our results suggest these increases are not related to changes in reproductive demographics, but rather are related to increased prerecruitment survival. Our results provide information for understanding temporal variation in spawning stock biomass of Lake Trout in Yellowstone Lake and the capacity of the population to respond to suppression. When responding to an invasive species, fishery managers should recognize that population characteristics (e.g., reproduction demographics, population dynamics) in invaded systems may differ from those in the species’ native range; such differences can influence the effectiveness of management actions and policies.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10320","usgsCitation":"Heredia, N.A., Gresswell, R.E., Webb, M.A., Brenden, T., and Sandstrom, P., 2021, Invasive Lake Trout reproduction in Yellowstone Lake under an active suppression program: Transactions of the American Fisheries Society, v. 150, p. 637-650, https://doi.org/10.1002/tafs.10320.","productDescription":"14 p.","startPage":"637","endPage":"650","ipdsId":"IP-101302","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451168,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/17172","text":"External Repository"},{"id":410470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.17221715497779,\n 44.31593705993478\n ],\n [\n -110.2779915024647,\n 44.432370639062185\n ],\n [\n -110.26952955466584,\n 44.542541941218076\n ],\n [\n -110.35626451960522,\n 44.56515410795788\n ],\n [\n -110.44088399759472,\n 44.54404969234673\n ],\n [\n -110.42396010199703,\n 44.48823689405097\n ],\n [\n -110.50011763218768,\n 44.464085073466265\n ],\n [\n -110.55300480593115,\n 44.47767170254781\n ],\n [\n -110.58685259712706,\n 44.432370639062185\n ],\n [\n -110.55512029288099,\n 44.373426719559944\n ],\n [\n -110.50011763218768,\n 44.390057940650394\n ],\n [\n -110.48954019743901,\n 44.420284420344046\n ],\n [\n -110.43453753674571,\n 44.41726247520114\n ],\n [\n -110.41338266724834,\n 44.3885462066863\n ],\n [\n -110.44934594539359,\n 44.365865511810995\n ],\n [\n -110.39645877165013,\n 44.3643531531269\n ],\n [\n -110.36472646740405,\n 44.370402353594415\n ],\n [\n -110.36895744130373,\n 44.33409778013848\n ],\n [\n -110.34145611095684,\n 44.28414227119808\n ],\n [\n -110.30760831976093,\n 44.264451154612374\n ],\n [\n -110.29279991111306,\n 44.300798831687814\n ],\n [\n -110.3054928328116,\n 44.35225287805176\n ],\n [\n -110.28645345026354,\n 44.3719145560996\n ],\n [\n -110.28010698941453,\n 44.31290972662845\n ],\n [\n -110.23779725041976,\n 44.285656699181146\n ],\n [\n -110.17010166802795,\n 44.31442341280314\n ],\n [\n -110.17010166802795,\n 44.317450668023355\n ],\n [\n -110.17221715497779,\n 44.31593705993478\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"150","noUsgsAuthors":false,"publicationDate":"2021-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Heredia, Nicholas A.","contributorId":181858,"corporation":false,"usgs":false,"family":"Heredia","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":858987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Molly A.H.","contributorId":299904,"corporation":false,"usgs":false,"family":"Webb","given":"Molly","email":"","middleInitial":"A.H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":858989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenden, Travis O.","contributorId":276046,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis O.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":859012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Philip T.","contributorId":299906,"corporation":false,"usgs":false,"family":"Sandstrom","given":"Philip T.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":858992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226964,"text":"70226964 - 2021 - Invaders from islands: Thermal matching, potential or flexibility?","interactions":[],"lastModifiedDate":"2021-12-22T12:38:26.19629","indexId":"70226964","displayToPublicDate":"2021-08-14T06:35:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9963,"text":"Biological Journal of the Linnaean Society","active":true,"publicationSubtype":{"id":10}},"title":"Invaders from islands: Thermal matching, potential or flexibility?","docAbstract":"

Native-range thermal constraints may not reflect the geographical distributions of species introduced from native island ranges in part due to rapid physiological adaptation in species introduced to new environments. Correlative ecological niche models may thus underestimate potential invasive distributions of species from islands. The northern curly-tailed lizard (Leiocephalus carinatus) is established in Florida, including populations north of its native range. Competing hypotheses may explain this distribution: Thermal Matching (distribution reflects thermal conditions of the native range), Thermal Potential (species tolerates thermal extremes absent in the native range) and/or Thermal Flexibility (thermal tolerance reflects local thermal extremes). We rejected the Thermal Matching hypothesis by comparing ecological niche models developed from native vs. native plus invasive distributions; L. carinatus exists in areas of low suitability in Florida as predicted by the native-distribution model. We then compared critical thermal limits of L. carinatus from two non-native populations to evaluate the Thermal Potential and Flexibility hypotheses: one matching native range latitudes, and another 160 km north of the native range that experiences more frequent cold weather events. Critical thermal minima in the northern population were lower than in the south, supporting the Thermal Flexibility hypothesis, whereas critical thermal maxima did not differ.

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Florida","active":true,"usgs":false}],"preferred":false,"id":828961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":828962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guralnick, Robert P.","contributorId":146671,"corporation":false,"usgs":false,"family":"Guralnick","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":828963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828964,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Emily N.","contributorId":270300,"corporation":false,"usgs":false,"family":"Taylor","given":"Emily N.","affiliations":[{"id":56144,"text":"Cal Poly State U.","active":true,"usgs":false}],"preferred":false,"id":828965,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227641,"text":"70227641 - 2021 - Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data","interactions":[],"lastModifiedDate":"2022-01-24T15:02:28.871949","indexId":"70227641","displayToPublicDate":"2021-08-13T08:59:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data","docAbstract":"

Kansas is one of the most productive agricultural states in the United States, where agricultural irrigation is a primary user of underground and surface water. Because of low precipitation and declining groundwater levels in western and central Kansas, sustainable management of irrigation water resources is a critical issue in the agricultural productivity of the state. The objective of this study is to analyze and characterize the water use and water balance in the croplands of Kansas using satellite observations, meteorological data, and in situ irrigation water use records. We used actual evapotranspiration (ETa), precipitation, soil moisture, and irrigation water use to calculate water balance for Kansas in 2015 at scales of counties, climatic divisions, and groundwater management districts (GMD). The Operational Simplified Surface Energy Balance model was implemented to estimate 30-m resolution ETa. Results showed that the seasonal (May – September) precipitation, soil water storage change, and ETa are 528 mm, 80 mm, and 555 mm, respectively, on average of all croplands in the state. The annual net irrigation water consumption was 293 mm for irrigated croplands, indicating that irrigation water constitutes an substantial portion of the water supply in the state. The total volumetric irrigation water use was 3.24 km3 for all croplands within five GMDs in western and south-central Kansas, while only 0.38 km3 was outside of GMDs. The multiple regression models of ETa against precipitation and irrigation water use were statistically significant with R2 values of 0.71 and 0.87, respectively, at county and climate division scales. Regression models also indicated a higher rate of ETa response to irrigation water use than that to precipitation. Our study demonstrated the spatial patterns of crop water use and water balance in Kansas, which could provide useful information for management of irrigation agriculture and water resources for the state.

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0000-0002-9602-321X","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":199093,"corporation":false,"usgs":false,"family":"Friedrichs","given":"MacKenzie","affiliations":[],"preferred":false,"id":831482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":181608,"corporation":false,"usgs":false,"family":"Schauer","given":"Matthew","affiliations":[],"preferred":false,"id":831483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boiko, Olena 0000-0002-2007-7852","orcid":"https://orcid.org/0000-0002-2007-7852","contributorId":272079,"corporation":false,"usgs":false,"family":"Boiko","given":"Olena","email":"","affiliations":[{"id":56343,"text":"KBR, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":831484,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227097,"text":"70227097 - 2021 - Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records","interactions":[],"lastModifiedDate":"2021-12-29T14:33:21.49436","indexId":"70227097","displayToPublicDate":"2021-08-13T08:29:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records","docAbstract":"

The geographic distribution of a species is a fundamental component in understanding its ecology and is necessary for forming effective conservation plans. For rare and elusive species of conservation concern, accurate maps of predicted occurrence are particularly problematic and often highly subjective. Spilogale putorius (Eastern Spotted Skunk) populations have experienced large declines since the 1940s. Their elusive behavior and perceived rarity result in low detection probability when using conventional methods for sampling small mammals. Low detection probability often causes uncertainty as to where Eastern Spotted Skunks could be a management concern. We modeled the distribution of predicted occurrence of Eastern Spotted Skunks using verifiable occurrence and non-detection records obtained throughout Virginia from 2010 to 2020. Occurrence data consisted of trapping records reported to the Virginia Department of Wildlife Resources, incidental photo-verified reports of sightings and road-killed animals, and remote-camera detections. Non-detections were presumed at baited remote-camera locations following intense survey efforts. We fit predicted occurrence models using generalized linear modeling in an information-theoretic framework using the package ‘stats’ in Program R. Our results incidated a greater probability of presence from the Blue Ridge westward, increasing with slope steepness along northeastern- to southeastern-facing slopes and decreasing with slope steepness along southeastern- to southwestern-facing slopes. Emergent rock outcrops prominent along northeastern slopes offer ample protective rocky cover, whereas mixed Quercus spp. (oak), Kalmia latifolia (Mountain Laurel), and Rhododendron maximum (Rosebay Rhododendron) forest communities along southern-facing slopes provide suitable areas of cover, both of which are critical for spotted skunk survival and reproductive success. Our analysis provides insight into the relationships between landscape features and Eastern Spotted Skunk distributions across Virginia. Understanding these relationships is critical for the effective management and conservation of this vulnerable species.

","language":"English","publisher":"BioOne","doi":"10.1656/058.020.0sp1105","usgsCitation":"Thorne, E.D., and Ford, W., 2021, Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records: Southeastern Naturalist, v. 20, no. 11, p. 39-51, https://doi.org/10.1656/058.020.0sp1105.","productDescription":"13 p.","startPage":"39","endPage":"51","ipdsId":"IP-123161","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451186,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111969","text":"External Repository"},{"id":393575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.13330078125,\n 36.31512514748051\n ],\n [\n -74.20166015624999,\n 36.31512514748051\n ],\n [\n -74.20166015624999,\n 40.027614437486655\n ],\n [\n -84.13330078125,\n 40.027614437486655\n ],\n [\n -84.13330078125,\n 36.31512514748051\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thorne, Emily D.","contributorId":270628,"corporation":false,"usgs":false,"family":"Thorne","given":"Emily","email":"","middleInitial":"D.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":829625,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228894,"text":"70228894 - 2021 - Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway","interactions":[],"lastModifiedDate":"2022-02-23T13:28:46.986794","indexId":"70228894","displayToPublicDate":"2021-08-13T07:21:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway","docAbstract":"

On the wintering grounds, wetland selection by waterfowl is influenced by spatiotemporal resource distribution. The ring-necked duck (Aythya collaris) winters in the southeastern United States where a disproportionate amount of Atlantic Flyway ring-necked duck harvest occurs. We quantified female ring-necked duck selection for wetland characteristics during and after the 2017–2018 and 2018–2019 waterfowl hunting seasons using discrete choice modeling under a Bayesian framework. Relative probability of selection was primarily influenced by characteristics at the local wetland scale. Relative probability of selection was higher for flooded agriculture and vegetated wetlands than open water and was positively influenced by wetland area during the winter. After the hunting season, the relative probability of selection decreased for flooded agriculture but increased for vegetated wetlands, and the effect of wetland area decreased in magnitude. We attribute changes in selection during and after the hunting season to dietary shifts related to migratory preparation, resource depletion, and reproductive pairing. Understanding the wetland characteristics that wintering waterfowl select, and the spatial scale at which selection occurs, is important for informing effective wetland management and waterfowl harvest practices.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-021-01485-8","usgsCitation":"Mezebish, T.D., Chandler, R., Olsen, G.H., Goodman, M., Rohwer, F., Meng, N.J., and McConnell, M.D., 2021, Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway: Wetlands, v. 41, 84, 13 p., https://doi.org/10.1007/s13157-021-01485-8.","productDescription":"84, 13 p.","ipdsId":"IP-130253","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":396335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.73754882812499,\n 29.99300228455108\n ],\n [\n -81.59545898437499,\n 29.99300228455108\n ],\n [\n -81.59545898437499,\n 31.062345409804433\n ],\n [\n -84.73754882812499,\n 31.062345409804433\n ],\n [\n -84.73754882812499,\n 29.99300228455108\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2021-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Mezebish, Tori D.","contributorId":239496,"corporation":false,"usgs":false,"family":"Mezebish","given":"Tori","email":"","middleInitial":"D.","affiliations":[{"id":27618,"text":"University of Georgia, Warnell School of Forestry and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":835802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard rchandler@usgs.gov","contributorId":2511,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":835838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodman, Michele","contributorId":239497,"corporation":false,"usgs":false,"family":"Goodman","given":"Michele","email":"","affiliations":[{"id":47893,"text":"Elmwood Park Zoo, Norristown, Pennyslvania","active":true,"usgs":false}],"preferred":false,"id":835804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohwer, Frank C.","contributorId":239498,"corporation":false,"usgs":false,"family":"Rohwer","given":"Frank C.","affiliations":[{"id":47894,"text":"Delta Waterfowl, Bismark North Dakota","active":true,"usgs":false}],"preferred":false,"id":835805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meng, Nicholas J.","contributorId":264806,"corporation":false,"usgs":false,"family":"Meng","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":54559,"text":"Warnell School of Forestry and Natural Resources, University of Georgia,","active":true,"usgs":false}],"preferred":false,"id":835839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McConnell, Mark D.","contributorId":239499,"corporation":false,"usgs":false,"family":"McConnell","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":47895,"text":"College of Forest Resources, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":835806,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223230,"text":"70223230 - 2021 - Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model","interactions":[],"lastModifiedDate":"2021-08-18T12:22:11.267846","indexId":"70223230","displayToPublicDate":"2021-08-13T07:19:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model","docAbstract":"

Visual encounter distance models are important tools for predicting how light and water clarity mediate visual predator-prey interactions that affect the structure and function of aquatic ecosystems at multiple spatial, temporal, and organizational scales. The two main varieties of visual encounter distance models, mechanistic and empirical, are used for similar purposes but take fundamentally different approaches to model development and have different strengths and weaknesses in terms of predictive accuracy, physical and biological interpretability of parameters, ability to incorporate outside information, and utility for knowledge transfer. To overcome weaknesses of existing mechanistic and empirical models and bridge the gap between approaches, we developed a generalized visual reaction distance model that relaxes assumptions of a widely-used mechanistic model that are violated in real predator-prey interactions. We compared the performance of the generalized visual reaction distance model to a widely used mechanistic model and an empirical visual encounter distance model by fitting models to data from four predator-prey experiments. The generalized visual reaction distance model substantially outperformed the other models in all cases based on fit to reaction distance data and presents an attractive alternative to prior models based on comparatively high predictive accuracy, use of interpretable parameters, and ability to incorporate outside information—characteristics that facilitate knowledge transfer.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109688","usgsCitation":"Rohan, S.K., Beauchamp, D., Essington, T.E., and Hansen, A.G., 2021, Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model: Ecological Modelling, v. 457, 109688, 13 p., https://doi.org/10.1016/j.ecolmodel.2021.109688.","productDescription":"109688, 13 p.","ipdsId":"IP-118285","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":451195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109688","text":"Publisher Index Page"},{"id":388085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"457","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rohan, Sean K.","contributorId":260255,"corporation":false,"usgs":false,"family":"Rohan","given":"Sean","email":"","middleInitial":"K.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":821471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essington, Timothy E.","contributorId":95826,"corporation":false,"usgs":false,"family":"Essington","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":821473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":821474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","interactions":[{"subject":{"id":70202002,"text":"70202002 - 2021 - Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA","indexId":"70202002","publicationYear":"2021","noYear":false,"chapter":"10","title":"Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":1},{"subject":{"id":70204951,"text":"70204951 - 2021 - Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California","indexId":"70204951","publicationYear":"2021","noYear":false,"chapter":"8","title":"Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":2},{"subject":{"id":70214977,"text":"70214977 - 2019 - Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California","indexId":"70214977","publicationYear":"2019","noYear":false,"chapter":"19","title":"Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":3}],"lastModifiedDate":"2021-11-08T15:31:24.702283","indexId":"70225733","displayToPublicDate":"2021-08-12T08:42:20","publicationYear":"2021","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"From saline to freshwater: The diversity of western lakes in space and time","docAbstract":"

Beginning with the nineteenth-century territorial surveys, the lakes and lacustrine deposits in what is now the western United States were recognized for their economic value to the expanding nation. In the latter half of the twentieth century, these systems have been acknowledged as outstanding examples of depositional systems serving as models for energy exploration and environmental analysis, many with global applications in the twenty-first century. The localities presented in this volume extend from exposures of the Eocene Green River Formation in Utah and Florissant Formation in Colorado, through the Pleistocene and Holocene lakes of the Great Basin to lakes along the California and Oregon coast. The chapters explore environmental variability, sedimentary processes, fire history, the impact of lakes on crustal flexure, and abrupt climate events in arid regions, often through the application of new tools and proxies.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/SPE536","usgsCitation":"2021, From saline to freshwater: The diversity of western lakes in space and time, v. 536, xii, 506 p., https://doi.org/10.1130/SPE536.","productDescription":"xii, 506 p.","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":391468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"536","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":826440,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826441,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":70223202,"text":"70223202 - 2021 - Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2021-09-14T16:54:11.190706","indexId":"70223202","displayToPublicDate":"2021-08-12T08:03:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico","docAbstract":"

Flows into and out of the Gulf of Mexico (GoM) are integral to North Atlantic ocean circulation, and help facilitate poleward heat transport in the Western Hemisphere. The GoM also serves as a key source of moisture for much of North America. Modern patterns of sea-surface temperature (SST) and salinity in the GoM are influenced by the Loop Current, its eddy-shedding dynamics, and the ensuing interplay with coastal processes. Here we present sub-centennial-scale records of SST and stable oxygen isotope composition of seawater (\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0001\"18Osw; a proxy for salinity) over the past 11,700 years using planktic foraminiferal geochemistry in sediments from the Garrison Basin, northwestern GoM. We measured \"urn:x-wiley:25724517:media:palo21077:palo21077-math-0002\"O and magnesium-to-calcium ratios in tests of Globigerinoides ruber (white) to generate quantitative estimates of past sea-surface conditions. Our results replicate and extend late Holocene reconstructions from the Garrison Basin, using which we then create composites of SST and \"urn:x-wiley:25724517:media:palo21077:palo21077-math-0003\"18Osw. We find considerable centennial and millennial-scale variability in both SST and \"urn:x-wiley:25724517:media:palo21077:palo21077-math-0004\"18Osw, although their evolution over the Holocene is distinct. Whereas mean-annual SSTs display pronounced millennial-scale variability, \"urn:x-wiley:25724517:media:palo21077:palo21077-math-0005\"18Osw exhibits a secular trend spanning multiple millennia and points to increasing northwestern GoM surface salinity since the early Holocene. We then synthesize available Holocene records from across the GoM, and alongside the Garrison Basin composite, uncover substantial, yet regionally consistent, spatiotemporal variability. Finally, we discuss the role of the Loop Current and coastal influx of freshwater in imposing these heterogeneities. We conclude that dynamic surface-ocean changes occurred across the GoM over the Holocene.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021PA004221","usgsCitation":"Thiumalai, K., Richey, J.N., and Quinn, T.M., 2021, Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico: Paleoceanography and Paleoclimatology, v. 36, no. 8, e2021PA004221, 16 p., https://doi.org/10.1029/2021PA004221.","productDescription":"e2021PA004221, 16 p.","ipdsId":"IP-120738","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436244,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q5L9VU","text":"USGS data release","linkHelpText":"Radiocarbon Dates and Foraminiferal Geochemistry Data for Sediment Core Collected from Garrison Basin, Gulf of Mexico"},{"id":388097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.07861328125,\n 27.00040800352175\n ],\n [\n -83.60595703125,\n 29.611670115197377\n ],\n [\n -86.37451171875,\n 29.859701442126756\n ],\n [\n -88.9453125,\n 29.76437737516313\n ],\n [\n -88.92333984375,\n 28.671310915880834\n ],\n [\n -91.91162109375,\n 29.286398892934763\n ],\n [\n -95.07568359375,\n 29.017748018496047\n ],\n [\n -97.09716796875,\n 27.11781284232125\n ],\n [\n -96.94335937499999,\n 24.647017162630366\n ],\n [\n -97.18505859374999,\n 21.922663209325922\n ],\n [\n -95.3173828125,\n 20.838277806058933\n ],\n [\n -81.54052734375,\n 24.307053283225915\n ],\n [\n -83.07861328125,\n 27.00040800352175\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Thiumalai, Kaustubh 0000-0002-7875-4182","orcid":"https://orcid.org/0000-0002-7875-4182","contributorId":264344,"corporation":false,"usgs":false,"family":"Thiumalai","given":"Kaustubh","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":821389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quinn, Terrence M.","contributorId":82949,"corporation":false,"usgs":false,"family":"Quinn","given":"Terrence","email":"","middleInitial":"M.","affiliations":[{"id":6732,"text":"Geological Sciences, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":821391,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224645,"text":"70224645 - 2021 - Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes","interactions":[],"lastModifiedDate":"2021-10-01T12:32:21.081687","indexId":"70224645","displayToPublicDate":"2021-08-12T07:30:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes","docAbstract":"

Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush (Artemisia tridentata) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3695","usgsCitation":"Schlaepfer, D.R., Bradford, J., Lauenroth, W.K., and Shriver, R.K., 2021, Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes: Ecosphere, v. 12, no. 8, e03695, 26 p., https://doi.org/10.1002/ecs2.3695.","productDescription":"e03695, 26 p.","ipdsId":"IP-126859","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451203,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3695","text":"Publisher Index Page"},{"id":436245,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MB2QB8","text":"USGS data release","linkHelpText":"Simulated rangewide big sagebrush regeneration estimates and relationships with abiotic variables as function of soils under historical and future climate projections"},{"id":390101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.68359374999999,\n 28.536274512989916\n ],\n [\n -100.546875,\n 28.536274512989916\n ],\n [\n -100.546875,\n 49.724479188712984\n ],\n [\n -125.68359374999999,\n 49.724479188712984\n ],\n [\n -125.68359374999999,\n 28.536274512989916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":824526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":824527,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230438,"text":"70230438 - 2021 - Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River","interactions":[],"lastModifiedDate":"2022-04-13T12:17:55.623098","indexId":"70230438","displayToPublicDate":"2021-08-12T07:14:28","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River","docAbstract":"

Lake Coyote, California, which formed in one of five basins along the Mojave River, acted both as a part of the Lake Manix basin and, after the formation of Afton Canyon and draining of Lake Manix ca. 24.5 calibrated (cal) ka, a side basin that was filled episodically for the next 10,000 yr. As such, its record of lake level is an important counterpart to the record of the other terminal basin, Lake Mojave, following the draining of Lake Manix. We studied lake and fluvial deposits and their geomorphology and identified five principal periods of recurring lakes in the Coyote basin by dating mollusks. Several of these periods in detail consist of multiple lake-rise pulses, for which we identified specific fluvial deposits that represent the Mojave River entering the basin. The pulsed record of rapid lake rise and decline is interpreted as switching of the Mojave River between Lake Coyote and Lake Mojave. A composite lake record for both basins shows nearly continuous lake maintenance by the Mojave River from 24.5 cal ka to ca. 14 cal ka. One potential gap in the lake record, ca. 22.7–21.8 cal ka, may indicate either temporary river routing to yet another basin or a dry climatic period. The Mojave River discharge was sufficient to maintain at least one terminal lake throughout most of the Last Glacial Maximum and deglacial periods, indicating that paleoclimate was moist and/or cool well into the Bølling-Allerød and that the lake records may not be sensitive to variations from moderate to high discharge. Nuances of lake-level changes in both the Coyote and Mojave basins are difficult to interpret as paleoclimatic events because the current chronologic control on lake levels from nearshore deposits does not provide the necessary precision.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From Saline to Freshwater: The Diversity of Western Lakes in Space and Time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2536(12)","usgsCitation":"Miller, D., Dudash, S.L., and McGeehin, J., 2021, Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River, chap. of From Saline to Freshwater: The Diversity of Western Lakes in Space and Time, v. 536, p. 201-220, https://doi.org/10.1130/2018.2536(12).","productDescription":"20 p.","startPage":"201","endPage":"220","ipdsId":"IP-087116","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":398633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lake Coyote","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.10302734374999,\n 34.08906131584994\n ],\n [\n -114.76318359375,\n 34.08906131584994\n ],\n [\n -114.76318359375,\n 36.19109202182454\n ],\n [\n -118.10302734374999,\n 36.19109202182454\n ],\n [\n -118.10302734374999,\n 34.08906131584994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"536","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":840431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudash, Stephanie L. 0000-0001-8728-5915 sdudash@usgs.gov","orcid":"https://orcid.org/0000-0001-8728-5915","contributorId":5911,"corporation":false,"usgs":true,"family":"Dudash","given":"Stephanie","email":"sdudash@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGeehin, John P.","contributorId":290192,"corporation":false,"usgs":false,"family":"McGeehin","given":"John P.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":840433,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229486,"text":"70229486 - 2021 - Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities","interactions":[],"lastModifiedDate":"2022-03-09T13:10:17.276921","indexId":"70229486","displayToPublicDate":"2021-08-12T07:06:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities","docAbstract":"

The eastern oyster, Crassostrea virginica, provides critical ecosystem services and supports valuable fishery and aquaculture industries in northern Gulf of Mexico (nGoM) subtropical estuaries where it is grown subtidally. Its upper critical thermal limit is not well defined, especially when combined with extreme salinities. The cumulative mortalities of the progenies of wild C. virginica from four nGoM estuaries differing in mean annual salinity, acclimated to low (4.0), moderate (20.0), and high (36.0) salinities at 28.9 °C (84 °F) and exposed to increasing target temperatures of 33.3 °C (92 °F), 35.6 °C (96 °F) or 37.8 °C (100 °F), were measured over a three-week period. Oysters of all stocks were the most sensitive to increasing temperatures at low salinity, dying quicker (i.e., lower median lethal time, LT50) than at the moderate and high salinities and resulting in high cumulative mortalities at all target temperatures. Oysters of all stocks at moderate salinity died the slowest with high cumulative mortalities only at the two highest temperatures. The F1 oysters from the more southern and hypersaline Upper Laguna Madre estuary were generally more tolerant to prolonged higher temperatures (higher LT50) than stocks originating from lower salinity estuaries, most notably at the highest salinity. Using the measured temperatures oysters were exposed to, 3-day median lethal Celsius degrees (LD50) were estimated for each stock at each salinity. The lowest 3-day LD50 (35.1–36.0 °C) for all stocks was calculated at a salinity of 4.0, while the highest 3-day LD50 (40.1–44.0 °C) was calculated at a salinity of 20.0.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2021.103072","usgsCitation":"Marshall, D., Coxe, N., La Peyre, M., Walton, W., Rikard, F.S., Beseres Pollack, J., Kelly, M., and La Peyre, J., 2021, Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities: Journal of Thermal Biology, v. 100, 103072, 7 p., https://doi.org/10.1016/j.jtherbio.2021.103072.","productDescription":"103072, 7 p.","ipdsId":"IP-126113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451207,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.lsu.edu/biosci_pubs/3821","text":"Publisher Index Page"},{"id":396900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Texas","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.91015624999999,\n 26.03704188651584\n ],\n [\n -90.52734374999999,\n 26.03704188651584\n ],\n [\n -90.52734374999999,\n 30.826780904779774\n ],\n [\n -97.91015624999999,\n 30.826780904779774\n ],\n [\n -97.91015624999999,\n 26.03704188651584\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, D.A.","contributorId":287622,"corporation":false,"usgs":false,"family":"Marshall","given":"D.A.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coxe, N.C.","contributorId":288255,"corporation":false,"usgs":false,"family":"Coxe","given":"N.C.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walton, W.C.","contributorId":287624,"corporation":false,"usgs":false,"family":"Walton","given":"W.C.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":837593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rikard, F. Scott","contributorId":288303,"corporation":false,"usgs":false,"family":"Rikard","given":"F.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":837656,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beseres Pollack, J.","contributorId":288257,"corporation":false,"usgs":false,"family":"Beseres Pollack","given":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":837594,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, M.A.","contributorId":221161,"corporation":false,"usgs":false,"family":"Kelly","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":837595,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"La Peyre, J.F.","contributorId":274908,"corporation":false,"usgs":false,"family":"La Peyre","given":"J.F.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837596,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222521,"text":"sir20215052 - 2021 - American and Sacramento Rivers, California, erodibility measurements and model","interactions":[],"lastModifiedDate":"2021-08-11T17:57:23.670031","indexId":"sir20215052","displayToPublicDate":"2021-08-11T08:55:06","publicationYear":"2021","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":"2021-5052","displayTitle":"American and Sacramento Rivers, California, Erodibility Measurements and Model","title":"American and Sacramento Rivers, California, erodibility measurements and model","docAbstract":"

Executive Summary 

A previous report by the authors described sediment sampling and drilling by the U.S. Geological Survey (USGS) beside the American and Sacramento Rivers near Sacramento, California, in support of a U.S. Army Corps of Engineers project focused on regional flood control. The drilling was performed to define lithology, extract samples for laboratory testing, and perform borehole erosion tests (BETs). The U.S. Department of Agriculture (USDA) performed jet erodibility tests (JETs) near each drilling site, and a team from Texas A&M University performed laboratory tests with an erosion function apparatus (EFA). Collectively, the effort was intended to reveal spatial variations in sediment erodibility and provide data for use in a model to simulate morphological response to a major flood. The data collected by the USGS are available in a public data release.

This report, developed in cooperation with the U.S. Army Corps of Engineers, provides comparisons of the three types of measurements of the erodibility of riverbed sediments. The BET is performed in the field and reveals erodibility of sediments below the bed surface. The JET is likewise performed in the field but reveals only erodibility of exposed sediments. The EFA test is done in the laboratory and was performed on soils extracted from different depths beneath the bed surface, in many cases reconstituted for laboratory testing. Tests were performed at nominally similar locations but differed by meters to tens of meters in horizontal locations.

The comparison was undertaken to investigate differences among results obtained by the individual measurement approaches and to elucidate pros and cons of each method. The critical shear stress to initiate erosion and the rate of change of erosion rate per unit increase of excess shear stress, sometimes referred to as the erosion coefficient, served as the primary basis for comparison. The three test methods in some cases resulted in order of magnitude differences in estimates of these parameters. Some differences could be attributed to variances in site location or result from testing surface sediment versus a deeper layer, but systematic differences are also evident in the results. The tests performed in the laboratory using the EFA resulted in much lower values of critical shear stress and much higher values of the erosion coefficient compared to the JET tests performed by the USDA team on surface sediments. Critical shear stress was poorly resolved in the BET results because of the limited number of results per site, but the erosion coefficients derived from BET results were systematically lower than those obtained using the EFA.

A new, simplified approach is also proposed to estimate the increase in channel cross-sectional area during a large flood, given data describing the initial river cross section, riverbed erodibility parameters, and peak flood discharge and duration. The model runs until the cross section erodes to an equilibrium condition or the flood ends. Output describes the area of the cross section at the end of the simulation and the time required to reach equilibrium if it was reached within the simulated period. The model assumes unique, constant values for both the critical shear stress and the erosion coefficient and represents the fluid mechanics in a simplified way, making it of limited value for quantitative predictions. It does, however, provide an indication of which cross sections are most likely to undergo the greatest change in the design event and can be used to investigate sensitivity of erosion predictions to variability in sediment erodibility measurements.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215052","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","programNote":"Cooperative Research Units","usgsCitation":"Work, P., and Livsey, D., 2021, American and Sacramento Rivers, California, erodibility measurements and model: U.S. Geological Survey Scientific Investigations Report 2021–5052, 30 p., https://doi.org/10.3133/sir20215052.","productDescription":"Report: vii, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-122004","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":387634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5052/covrthb.jpg"},{"id":387637,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5052/images"},{"id":387635,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5052/sir20215052.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387636,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5052/sir20215052.xml"},{"id":387638,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96MCT2Q","linkHelpText":"Borehole Erosion Test data, Lower American and Sacramento Rivers, California, 2019 (ver. 4.0, July 2021)"}],"country":"United States","state":"California","otherGeospatial":"American River, Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.58981323242188,\n 38.41378642476067\n ],\n [\n -121.34124755859375,\n 38.41378642476067\n ],\n [\n -121.34124755859375,\n 38.60292007223949\n ],\n [\n -121.58981323242188,\n 38.60292007223949\n ],\n [\n -121.58981323242188,\n 38.41378642476067\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-08-11","noUsgsAuthors":false,"publicationDate":"2021-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Livsey, Daniel N. 0000-0002-2028-6128 dlivsey@usgs.gov","orcid":"https://orcid.org/0000-0002-2028-6128","contributorId":181870,"corporation":false,"usgs":true,"family":"Livsey","given":"Daniel","email":"dlivsey@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227258,"text":"70227258 - 2021 - The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate","interactions":[],"lastModifiedDate":"2022-01-05T13:12:29.380875","indexId":"70227258","displayToPublicDate":"2021-08-11T07:09:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate","docAbstract":"

Modeling studies project that in the future surface waters in the northeast US will continue to recover from acidification over decades following reductions in atmospheric sulfur dioxide and nitrogen oxides emissions. However, these studies generally assume stationary climatic conditions over the simulation period and ignore the linkages between soil and surface water recovery from acid deposition and changing climate, despite fundamental impacts to watershed processes and comparable time scales for both phenomena. In this study, the integrated biogeochemical model PnET-BGC was applied to two montane forest watersheds in the Adirondack region of New York, USA to evaluate the recovery of surface waters from historical acidification in response to possible future changes in climate and atmospheric sulfur and nitrogen deposition. Statistically downscaled climate scenarios on average project warmer temperatures and greater precipitation for the Adirondack by the end of the century. Model simulations suggest under constant climate, acid-sensitive Buck Creek would gain 12.8 μeq L−1 of acid neutralizing capacity (ANC) by 2100 from large reductions in deposition, whereas acid insensitive Archer Creek is projected to gain 7.9 μeq L−1 of ANC. However, climate change could limit those improvements in acid-base status. Under climate change, a negative offset relative to the ANC increases with no climate change are projected for both streams by 2100. In acid-insensitive Archer Creek the negative offset (−8.5 μeq L−1) was large enough that ANC is projected to decrease by −0.6 μeq L−1, whereas in acid-sensitive Buck Creek, the negative offset (−0.4 μeq L−1) resulted in a slight decline of the projected future ANC increase to 12.4 μeq L−1. Calculated target loads for 2150 for both sites decreased when future climate change was considered in model simulations, which suggests further reductions in acid deposition may be necessary to restore ecosystem structure and function under a changing climate.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.149626","usgsCitation":"Shao, S., Burns, D., Shen, H., Chen, Y., Russell, A.G., and Driscoll, C., 2021, The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate: Science of the Total Environment, v. 800, 149626, 13 p., https://doi.org/10.1016/j.scitotenv.2021.149626.","productDescription":"149626, 13 p.","ipdsId":"IP-128626","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":393906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.443115234375,\n 42.76314586689494\n ],\n [\n -73.201904296875,\n 42.76314586689494\n ],\n [\n -73.201904296875,\n 45.081278612418764\n ],\n [\n -75.443115234375,\n 45.081278612418764\n ],\n [\n -75.443115234375,\n 42.76314586689494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"800","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shao, Shuai","contributorId":222597,"corporation":false,"usgs":false,"family":"Shao","given":"Shuai","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":830149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shen, Huizhong 0000-0003-1335-8477","orcid":"https://orcid.org/0000-0003-1335-8477","contributorId":270927,"corporation":false,"usgs":false,"family":"Shen","given":"Huizhong","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Yilin 0000-0001-5532-4115","orcid":"https://orcid.org/0000-0001-5532-4115","contributorId":270928,"corporation":false,"usgs":false,"family":"Chen","given":"Yilin","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Armistead G 0000-0003-2027-8870","orcid":"https://orcid.org/0000-0003-2027-8870","contributorId":270929,"corporation":false,"usgs":false,"family":"Russell","given":"Armistead","email":"","middleInitial":"G","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830153,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":830154,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226570,"text":"70226570 - 2021 - Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream","interactions":[],"lastModifiedDate":"2021-11-29T12:54:51.469752","indexId":"70226570","displayToPublicDate":"2021-08-10T06:53:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream","docAbstract":"

Evolving complex mixtures of pharmaceuticals and transformation products in effluent-dominated streams pose potential impacts to aquatic species; thus, understanding the attenuation dynamics in the field and characterizing the prominent attenuation mechanisms of pharmaceuticals and their transformation products (TPs) is critical for hazard assessments. Herein, we determined the attenuation dynamics and the associated prominent mechanisms of pharmaceuticals and their corresponding TPs via a combined long-term field study and controlled laboratory experiments. For the field study, we quantified spatiotemporal exposure concentrations of five pharmaceuticals and six associated TPs in a small, temperate-region effluent-dominated stream during baseflow conditions where the wastewater plant was the main source of pharmaceuticals. We selected four sites (upstream, at, and two progressively downstream from effluent discharge) and collected water samples at 16 time points (64 samples in total, approximately twice monthly, depending on flows) for 1 year. Concurrently, we conducted photolysis, sorption, and biodegradation batch tests under controlled conditions to determine the major attenuation mechanisms. We observed 10-fold greater attenuation rates in the field compared to batch tests, demonstrating that connecting laboratory batch tests with field measurements to enhance predictive power is a critical need. Batch systems alone, often used for assessment, are useful for determining fate processes but poorly approximate in-stream attenuation kinetics. Sorption was the dominant attenuation process (t1/2<7.7 d) for 5 of 11 compounds in the batch tests, while the other compounds (n = 6) persisted in the batch tests and along the 5.1 km stream reach. In-stream parent-to-product transformation was minimal. Differential attenuation contributed to the evolving pharmaceutical mixture and created changing exposure conditions with concomitant implications for aquatic and terrestrial biota. Tandem field and laboratory characterization can better inform modeling efforts for transport and risk assessments.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117537","usgsCitation":"Zhi, H., Mianecki, A.L., Kolpin, D., Klaper, R.D., Iwanowicz, L., and LeFevre, G.H., 2021, Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream: Water Research, v. 203, 117537, 10 p., https://doi.org/10.1016/j.watres.2021.117537.","productDescription":"117537, 10 p.","ipdsId":"IP-124512","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":451233,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12424012/","text":"Publisher Index Page"},{"id":392181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"203","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhi, Hui","contributorId":225502,"corporation":false,"usgs":false,"family":"Zhi","given":"Hui","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":827369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mianecki, Alyssa L","contributorId":269532,"corporation":false,"usgs":false,"family":"Mianecki","given":"Alyssa","email":"","middleInitial":"L","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":827370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":827372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":827373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":827374,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222679,"text":"ofr20211030D - 2021 - System characterization report on Planet’s Dove-R","interactions":[{"subject":{"id":70222679,"text":"ofr20211030D - 2021 - System characterization report on Planet’s Dove-R","indexId":"ofr20211030D","publicationYear":"2021","noYear":false,"chapter":"D","displayTitle":"System Characterization Report on Planet’s Dove-R","title":"System characterization report on Planet’s Dove-R"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2021-08-25T20:34:50.342041","indexId":"ofr20211030D","displayToPublicDate":"2021-08-09T14:39:33","publicationYear":"2021","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":"2021-1030","chapter":"D","displayTitle":"System Characterization Report on Planet’s Dove-R","title":"System characterization report on Planet’s Dove-R","docAbstract":"

Executive Summary

This report addresses system characterization of Planet’s Dove-R and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.

Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.com/.

The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Dove-R has an interior geometric performance in the range of −0.306 (−0.102 pixel) to 0.286 m (0.095 pixel) in easting and 0.090 (0.030 pixel) to 1.084 m (0.361 pixel) in northing in band-to-band registration, an exterior geometric performance of −5.10 m (−0.51 pixel) in easting and 3.30 m (0.33 pixel) in northing offset in comparison to Sentinel-2, a radiometric performance in the range of −0.023 to −0.008 in offset and 0.948 to 1.077 in slope, and a spatial performance in the range of 2.96 to 3.15 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.003.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030D","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2021, System characterization report on Planet’s Dove-R, chap. D of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 34 p., https://doi.org/10.3133/ofr20211030D.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-126678","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387784,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/d/ofr20211030d.pdf","text":"Report","size":"3.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030D"},{"id":387783,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/d/coverthb.jpg"}],"contact":"

Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-08-09","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":820804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":820805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820807,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223380,"text":"70223380 - 2021 - Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates","interactions":[],"lastModifiedDate":"2021-08-25T13:01:10.970191","indexId":"70223380","displayToPublicDate":"2021-08-09T07:59:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates","docAbstract":"

Accurate population estimates are essential for monitoring and managing wildlife populations. Mark–recapture sampling methods have regularly been used to estimate population parameters for rare and cryptic species, including the federally listed Mojave desert tortoise (Gopherus agassizii); however, the methods employed are often plagued by violations of statistical assumptions, which have the potential to bias density estimates. By incorporating spatial information into conventional density estimation models, spatial capture–recapture (SCR) models can account for common assumption violations such as spatially heterogeneous detection probabilities and temporary emigration when animals leave plots during a survey. We conducted mark–recapture surveys at 10 1-km2 plots in and adjacent to the Ivanpah Valley of California and Nevada from 2015 to 2019. Locality data were collected concurrently using radio-telemetry and GPS data loggers. GPS data demonstrated that desert tortoises frequently exhibited temporary emigration outside a plot during the survey periods, thereby complicating standard approaches for closed-model density estimation. We integrated mark–recapture survey data for subadults and adults at each plot with corresponding spatial capture locations and supplementary spatial data using a modified SCR model fitted in a Bayesian framework. We compared density estimates modeled with conventional non-spatial methods, as well as three SCR models based on symmetrical usage areas described by various levels and types of supplementary spatial data. The conventional model consistently resulted in inflated estimates of density while the SCR models allowed us to generate spatially corrected estimates for a species where detectability and densities are low. However, we found that if not properly specified, the temporal scale of supplementary data may result in an unintended source of bias in parameter estimates. Integrating spatial data over a larger temporal scale than mark–recapture surveys were conducted resulted in higher detection probabilities and lower density estimates, due to an overestimation of space use. Our results not only demonstrate the importance of accounting for spatial information but also the value of understanding the potential for bias when integrating multiple data sets at different temporal resolutions. The methods presented can be used to enhance monitoring efforts for the Mojave desert tortoise and other species where mark–recapture methods are used.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3689","usgsCitation":"Mitchell, C.I., Shoemaker, K.T., Esque, T., Vandergast, A.G., Hromada, S.J., Dutcher, K.E., Heaton, J.S., and Nussear, K.E., 2021, Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates: Ecosphere, v. 12, no. 8, e03689, 23 p., https://doi.org/10.1002/ecs2.3689.","productDescription":"e03689, 23 p.","ipdsId":"IP-127713","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3689","text":"Publisher Index Page"},{"id":388475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.587158203125,\n 35.092945313732635\n ],\n [\n -114.730224609375,\n 35.092945313732635\n ],\n [\n -114.730224609375,\n 35.782170703266075\n ],\n [\n -115.587158203125,\n 35.782170703266075\n ],\n [\n -115.587158203125,\n 35.092945313732635\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Corey I","contributorId":245149,"corporation":false,"usgs":false,"family":"Mitchell","given":"Corey","email":"","middleInitial":"I","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoemaker, Kevin T. 0000-0002-3789-3856","orcid":"https://orcid.org/0000-0002-3789-3856","contributorId":255290,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin","email":"","middleInitial":"T.","affiliations":[{"id":51513,"text":"Department of Natural Resources and Environmental Science, University of Nevada, Reno. 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":821892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dutcher, Kirsten E.","contributorId":221063,"corporation":false,"usgs":false,"family":"Dutcher","given":"Kirsten","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821896,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaton, Jill S.","contributorId":175155,"corporation":false,"usgs":false,"family":"Heaton","given":"Jill","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":821897,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Kenneth E.","contributorId":117361,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821898,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223216,"text":"70223216 - 2021 - Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes","interactions":[],"lastModifiedDate":"2021-08-18T12:54:03.5729","indexId":"70223216","displayToPublicDate":"2021-08-09T07:50:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes","docAbstract":"

Sub-centennial oxygen (δ18O) isotopes of ostracod and authigenic calcite from Squanga Lake provides evidence of hydroclimatic extremes and a series of post-glacial climate system reorganizations for the interior region of northwest Canada. Authigenic calcite δ18O values range from −16‰ to −21‰ and are presently similar to modern lake water and annual precipitation values. Ostracod δ18O record near identical trends with calcite, offset by +1.7 ± 0.6‰. At 11 ka BP (kaBP = thousands of years before 1950), higher δ18O values reflect decreased precipitation−evaporation (P−E) balance from residual ice sheet influences on moisture availability. A trend to lower δ18O values until ∼8 ka BP reflects a shift to wetter conditions, and reorganization of atmospheric circulation. The last millennium and modern era are relatively dry, though not as dry as the early Holocene extreme. North Pacific climate dynamics remained an important driver of P−E balance in northwest Canada throughout the Holocene.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL092948","usgsCitation":"Lasher, G.E., Abbott, M.B., Anderson, L., Yasarer, L., Rosenheimer, M., and Finney, B., 2021, Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes: Geophysical Research Letters, v. 48, no. 16, e2021GL092948, 9 p., https://doi.org/10.1029/2021GL092948.","productDescription":"e2021GL092948, 9 p.","ipdsId":"IP-126880","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499920,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/63019564c9524c3bb5db5f48dbd19357","text":"External Repository"},{"id":388093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Yukon Territory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.80078125,\n 60.37042901631508\n ],\n [\n -139.482421875,\n 60.108670463036\n ],\n [\n -123.662109375,\n 59.84481485969105\n ],\n [\n -124.71679687499999,\n 61.01572481397616\n ],\n [\n -126.65039062499999,\n 60.88770004207789\n ],\n [\n -126.91406249999999,\n 61.48075950007598\n ],\n [\n -129.111328125,\n 62.2679226294176\n ],\n [\n -129.990234375,\n 63.78248603116502\n ],\n [\n -132.099609375,\n 64.84893726357947\n ],\n [\n -132.1875,\n 65.5129625532949\n ],\n [\n -132.890625,\n 66.01801815922045\n ],\n [\n -133.505859375,\n 66.12496236487968\n ],\n [\n -133.9453125,\n 66.99884379185184\n ],\n [\n -135.35156249999997,\n 67.06743335108298\n ],\n [\n -136.93359375,\n 68.84766505841037\n ],\n [\n -140.44921875,\n 69.65708627301174\n ],\n [\n -141.240234375,\n 69.68761843185617\n ],\n [\n -140.80078125,\n 60.37042901631508\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lasher, G. Everett","contributorId":264355,"corporation":false,"usgs":false,"family":"Lasher","given":"G.","email":"","middleInitial":"Everett","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":821411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Mark B.","contributorId":264356,"corporation":false,"usgs":false,"family":"Abbott","given":"Mark","email":"","middleInitial":"B.","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":821412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":821413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yasarer, Lindsey","contributorId":264359,"corporation":false,"usgs":false,"family":"Yasarer","given":"Lindsey","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":821414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenheimer, Michael","contributorId":264361,"corporation":false,"usgs":false,"family":"Rosenheimer","given":"Michael","email":"","affiliations":[{"id":54449,"text":"RIZZO International, Inc.","active":true,"usgs":false}],"preferred":false,"id":821415,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finney, Bruce P.","contributorId":264362,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce P.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":821416,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223920,"text":"70223920 - 2021 - Hawai‘i forest review: Synthesizing the ecology, evolution, and conservation of a model system","interactions":[],"lastModifiedDate":"2021-09-14T12:02:07.510361","indexId":"70223920","displayToPublicDate":"2021-08-08T06:56:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3033,"text":"Perspectives in Plant Ecology, Evolution and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Hawai‘i forest review: Synthesizing the ecology, evolution, and conservation of a model system","docAbstract":"

As the most remote archipelago in the world, the Hawaiian Islands are home to a highly endemic and disharmonic biota that has fascinated biologists for centuries. Forests are the dominant terrestrial biome in Hawai‘i, spanning complex, heterogeneous climates across substrates that vary tremendously in age, soil structure, and nutrient availability. Species richness is low in Hawaiian forests compared to other tropical forests, as a consequence of dispersal limitation from continents and adaptive radiations in only some lineages, and forests are dominated by the widespread Metrosideros species complex. Low species richness provides a relatively tractable model system for studies of community assembly, local adaptation, and species interactions. Moreover, Hawaiian forests provide insights into predicted patterns of evolution on islands, revealing that while some evidence supports “island syndromes,” there are exceptions to them all. For example, Hawaiian plants are not as a whole less defended against herbivores, less dispersible, more conservative in resource use, or more slow-growing than their continental relatives. Clearly, more work is needed to understand the drivers, sources, and constraints on phenotypic variation among Hawaiian species, including both widespread and rare species, and to understand the role of this variation for ecological and evolutionary processes, which will further contribute to conservation of this unique biota. Today, Hawaiian forests are among the most threatened globally. Resource management failures – the proliferation of non-native species in particular – have led to devastating declines in native taxa and resulted in dominance by novel species assemblages. Conservation and restoration of Hawaiian forests now rely on managing threats including climate change, ongoing species introductions, novel pathogens, lost mutualists, and altered ecosystem dynamics through the use of diverse tools and strategies grounded in basic ecological, evolutionary, and biocultural principles. The future of Hawaiian forests thus depends on the synthesis of ecological and evolutionary research, which will continue to inform future conservation and restoration practices.

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Paul","contributorId":265727,"corporation":false,"usgs":false,"family":"Krushelnycky","given":"Paul","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":823266,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kawelo, Kapua","contributorId":265728,"corporation":false,"usgs":false,"family":"Kawelo","given":"Kapua","email":"","affiliations":[{"id":54778,"text":"DOD/Army","active":true,"usgs":false}],"preferred":false,"id":823267,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Feliciano, Kealoha","contributorId":265730,"corporation":false,"usgs":false,"family":"Feliciano","given":"Kealoha","email":"","affiliations":[{"id":54779,"text":"German Center for Integrative Biodiversity","active":true,"usgs":false}],"preferred":false,"id":823268,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bennett, Gordon","contributorId":265732,"corporation":false,"usgs":false,"family":"Bennett","given":"Gordon","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":823269,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Knight, Tiffany","contributorId":265733,"corporation":false,"usgs":false,"family":"Knight","given":"Tiffany","affiliations":[{"id":54779,"text":"German Center for Integrative Biodiversity","active":true,"usgs":false}],"preferred":false,"id":823270,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70228848,"text":"70228848 - 2021 - Improving evaluation of nonlethal tools for carnivore management and conservation: Evaluating fladry to protect an endangered species from a generalist mesocarnivore","interactions":[],"lastModifiedDate":"2022-02-23T16:03:34.053149","indexId":"70228848","displayToPublicDate":"2021-08-07T09:54:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Improving evaluation of nonlethal tools for carnivore management and conservation: Evaluating fladry to protect an endangered species from a generalist mesocarnivore","docAbstract":"

Carnivore conservation and management are global research priorities focused on reversing population declines of imperiled species and identifying more effective and humane management of generalist carnivores with thriving populations. Nonlethal methods to mitigate conflict are increasingly used to advance conservation objectives; however, there is limited knowledge about the effectiveness of many nonlethal methods. We tested a nonlethal tool (fladry), that serves as a barrier to deter wolves Canis lupus and coyotes Canis latrans, for its efficacy at preventing coyotes from using prairie dog Cynomys ludovicianus colonies, the primary prey for critically endangered black-footed ferrets Mustela nigripes. We used camera trap data and an occupancy approach to evaluate the tool’s efficacy. We measured coyote response to fladry at both a coarse monthly scale (via use, attraction and avoidance probabilities) and a fine scale (via daily activity). Overall, use of areas inside exclosures declined by 60% after 60 days of fladry application and coyotes avoided some previously used areas both within and outside exclosures. Interestingly, coyotes were attracted to previously unused areas surrounding exclosures and increased activity around the periphery of fladry exclosures by 170% immediately after fladry installation, suggesting coyotes actively explored these areas and may have responded to fladry in a way that is counterintuitive to management expectations. Occupancy models provided more robust evaluation of fladry and revealed important behavioral responses relative to other common evaluation techniques (i.e. time until first detected crossing). Our results have implications for future development and evaluation of nonlethal tools for carnivore conservation and management globally.

","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12726","usgsCitation":"Windell, R., Bailey, L., Young, J.K., Livieri, T.M., Eads, D.A., and Breck, S., 2021, Improving evaluation of nonlethal tools for carnivore management and conservation: Evaluating fladry to protect an endangered species from a generalist mesocarnivore: Animal Conservation, v. 25, no. 1, p. 125-136, https://doi.org/10.1111/acv.12726.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-117480","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park, Buffalo Gap National Grasslands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-07","publicationStatus":"PW","contributors":{"editors":[{"text":"Penteriani, Vincenzo","contributorId":280007,"corporation":false,"usgs":false,"family":"Penteriani","given":"Vincenzo","email":"","affiliations":[],"preferred":false,"id":835841,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Ordiz, Andrés","contributorId":280008,"corporation":false,"usgs":false,"family":"Ordiz","given":"Andrés","affiliations":[],"preferred":false,"id":835842,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Windell, Rebecca","contributorId":279885,"corporation":false,"usgs":false,"family":"Windell","given":"Rebecca","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Julie K.","contributorId":196299,"corporation":false,"usgs":false,"family":"Young","given":"Julie","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":835694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livieri, Travis M.","contributorId":198977,"corporation":false,"usgs":false,"family":"Livieri","given":"Travis","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":835696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breck, Stewart","contributorId":199403,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart","affiliations":[],"preferred":false,"id":835697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230796,"text":"70230796 - 2021 - Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products","interactions":[],"lastModifiedDate":"2022-04-26T15:52:18.27322","indexId":"70230796","displayToPublicDate":"2021-08-06T10:47:56","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products","docAbstract":"

In late 2020 the U.S. Geological Survey (USGS) began the distribution of Landsat products associated with their collection 2 reprocessing of the archive. Several changes were implemented within the Landsat Product Generation System (LPGS) and the calibration parameters applied to the Landsat imagery for the collection 2 processing. When comparing between collection 1 and collection 2 products, radiometric and geometric differences will be present. One of the most substantial changes between the two collections was an adjustment to the ground control which made the control more accurate from an absolute and relative perspective. Some of the other changes associated with collection 2 processing were to the Digital Elevation Model (DEM) used in terrain correction, the Thermal Infrared Sensor (TIRS) relative gains, TIRS absolute calibration, Operational Land Imagery (OLI) absolute gain model, OLI relative gain, and OLI bias calculation to name a few. Although these changes also have an effect on the differences between the product associated with these two collections, the change in the ground control, although typically less than one 30-meter multispectral pixel in magnitude, will have the largest effect on the differences between the products. This change in ground control is also a spatially dynamic change that although is low in spatial frequency, is nonlinear and is not a change that can be modeled on a global or even on a local Worldwide Reference System-2 (WRS-2) path and row scale. The effects of these ground control changes will be discussed and demonstrated within this paper along with examples showing their effect on specific datasets. This paper demonstrates some of these geometric differences associated with the ground control through both the registration statistics created during product generation and through an example comparison of a set of collection 1 and collection 2 products.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings volume 11829, Earth Observing Systems XXVI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPIE Optical Engineering + Applications","conferenceDate":"Aug 1-5, 2021","conferenceLocation":"San Diego, CA","language":"English","doi":"10.1117/12.2596204","usgsCitation":"Choate, M.J., Rengarajan, R., Micijevic, E., and Lubke, M., 2021, Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products, in Proceedings volume 11829, Earth Observing Systems XXVI, v. 11829, San Diego, CA, Aug 1-5, 2021, 118290H, 11 p., https://doi.org/10.1117/12.2596204.","productDescription":"118290H, 11 p.","ipdsId":"IP-131285","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":399676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":841371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":841372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Micijevic, Esad 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":290334,"corporation":false,"usgs":false,"family":"Micijevic","given":"Esad","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":841374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubke, Mark 0000-0002-7257-2337","orcid":"https://orcid.org/0000-0002-7257-2337","contributorId":261911,"corporation":false,"usgs":false,"family":"Lubke","given":"Mark","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":841373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226639,"text":"70226639 - 2021 - Brown treesnake mortality after aerial application of toxic baits","interactions":[],"lastModifiedDate":"2021-12-01T13:31:25.091333","indexId":"70226639","displayToPublicDate":"2021-08-06T07:29:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Brown treesnake mortality after aerial application of toxic baits","docAbstract":"

Quantitative evaluation of control tools for managing invasive species is necessary to assess overall effectiveness and individual variation in treatment susceptibility. Invasive brown treesnakes (Boiga irregularis) on Guam have caused severe ecological and economic effects, pose a risk of accidental introduction to other islands, and are the greatest impediment to the reestablishment of extirpated native fauna. An aerial delivery system for rodent-based toxic baits can reduce brown treesnake abundance and heterogeneity among individuals may influence bait attraction or toxicant susceptibility. Previous baiting trials have either been simulated aerial treatments or relied on slightly different bait capsule compositions and the results of aerial delivery of toxic baits under operational conditions may not be directly comparable. We monitored 30 radio-tagged adult snakes (990–1,265 mm snout-vent length) during an aerial baiting operation in a 55-ha area using transmitters equipped with accelerometers and receivers programed to display a status code indicating mortality if a snake failed to move for >24 hours. We used known-fate models to estimate mortality and evaluate a priori hypotheses explaining differences in mortality based on size, sex, and treatment effects. Eleven radio-tagged snakes died in the aerial baiting treatment period (0.37, 95% CI = 0.21–0.55) and no individuals (0.00, 95% CI = 0.00–0.04) died during the non-treatment period. Our data provide strong evidence for an additive size-based treatment effect on mortality, with smaller adults (0.59, 95% CI = 0.35–0.80) exhibiting higher mortality than larger snakes (0.14, 95% CI = 0.02–0.37) but did not support a sex effect on mortality. The high mortality of snakes during the treatment period indicates that aerial baiting can reduce brown treesnake abundance, but further refinement or use in combination with other removal tools may be necessary to overcome size-based differences in susceptibility and achieve eradication.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22108","usgsCitation":"Goetz, S.M., Hileman, E., Nafus, M.G., Yackel Adams, A.A., Bryant, A.R., Reed, R., and Siers, S.R., 2021, Brown treesnake mortality after aerial application of toxic baits: Journal of Wildlife Management, v. 85, no. 7, p. 1507-1514, https://doi.org/10.1002/jwmg.22108.","productDescription":"8 p.","startPage":"1507","endPage":"1514","ipdsId":"IP-120449","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22108","text":"Publisher Index Page"},{"id":392302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.6075439453125,\n 13.210534384132375\n ],\n [\n 144.964599609375,\n 13.210534384132375\n ],\n [\n 144.964599609375,\n 13.680681930380013\n ],\n [\n 144.6075439453125,\n 13.680681930380013\n ],\n [\n 144.6075439453125,\n 13.210534384132375\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Goetz, Scott Michael 0000-0002-8705-5316","orcid":"https://orcid.org/0000-0002-8705-5316","contributorId":228868,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hileman, Eric T.","contributorId":257493,"corporation":false,"usgs":false,"family":"Hileman","given":"Eric T.","affiliations":[],"preferred":false,"id":827564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bryant, Amanda R","contributorId":269622,"corporation":false,"usgs":false,"family":"Bryant","given":"Amanda","email":"","middleInitial":"R","affiliations":[{"id":56015,"text":"Cherokee Nation Technologies, U.S. Geological Survey Brown Treesnake Project, Yigo, GU 96929, USA","active":true,"usgs":false}],"preferred":false,"id":827567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":827568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siers, Shane R.","contributorId":152305,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":827569,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264024,"text":"70264024 - 2021 - Improving inferences about private land conservation by accounting for incomplete reporting","interactions":[],"lastModifiedDate":"2025-03-05T16:08:45.128462","indexId":"70264024","displayToPublicDate":"2021-08-06T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Improving inferences about private land conservation by accounting for incomplete reporting","docAbstract":"

Private lands provide key habitat for imperiled species and are core components of function protected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social-ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13673","usgsCitation":"Williamson, M., Dickson, B., Hooten, M., Graves, R., Lubell, M., and Schwartz, M., 2021, Improving inferences about private land conservation by accounting for incomplete reporting: Conservation Biology, v. 35, no. 4, p. 1174-1185, https://doi.org/10.1111/cobi.13673.","productDescription":"12 p.","startPage":"1174","endPage":"1185","ipdsId":"IP-113790","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, 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A.","contributorId":351798,"corporation":false,"usgs":false,"family":"Graves","given":"Rose A.","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":929512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lubell, Mark N.","contributorId":351799,"corporation":false,"usgs":false,"family":"Lubell","given":"Mark N.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Mark W.","contributorId":351800,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark W.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929514,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222458,"text":"ofr20211073 - 2021 - Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","interactions":[],"lastModifiedDate":"2021-08-06T21:38:29.620031","indexId":"ofr20211073","displayToPublicDate":"2021-08-05T15:00:00","publicationYear":"2021","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":"2021-1073","displayTitle":"Reconnaissance Study of the Major and Trace Element Content of Bauxite Deposits in the Arkansas Bauxite Region, Saline and Pulaski Counties, Central Arkansas","title":"Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","docAbstract":"

The Arkansas bauxite district, which comprises about 275 square miles (710 square kilometers) of central Arkansas, produced an order of magnitude more bauxite and alumina than the other bauxite districts in the United States combined. Bauxite was mined in the region continuously from 1898 to 1982. These bauxites are laterite deposits, formed from intensive in-place weathering of the exposed surface of the Granite Mountain pluton, a Late Cretaceous batholith composed mainly of nepheline syenite and lesser amounts of syenite. Nepheline syenite was the aluminum source for the bauxite and clay deposits that blanket the pluton. The early Eocene continental sedimentary rocks that contain and overlie the bauxite deposits indicate that central Arkansas had a warm tropical environment during bauxite formation.

Bauxite ores are the principal sources of aluminum. Some of the global bauxite deposits have been found to contain co-occurring metals that have essential applications in modern technologies. For example, bauxite is the largest global source of gallium (Ga), used in semiconductors, which is recovered as a byproduct of processing bauxite to recover alumina. Other critical metal commodities within some bauxites that reportedly have potential for byproduct recovery include niobium (Nb), scandium (Sc), and rare earth elements (REEs). Currently (2021), the United States is wholly dependent on imports for its supplies of bauxite for processing to produce alumina. The United States is also dependent on foreign sources of gallium, niobium, and scandium, as well for most of its domestic requirements of REEs.

For these reasons, samples were collected from Arkansas bauxite deposits, associated clays, mill residue wastes (respectively referred to as red muds and black sands), and the parent nepheline syenite to determine their elemental content, with a particular focus on gallium, niobium, scandium, and REEs. Each sample was analyzed for 60 elements; these data and the methods used are published as a U.S. Geological Survey data release.

The results indicate that, of the critical metals in bauxites, gallium is a potential byproduct from the central Arkansas bauxite deposits. The highest gallium concentrations occur in the raw bauxite ore, with an average concentration of 76 parts per million (ppm). Gallium partitions with alumina (the product) rather than into mine waste residues. Results indicate an average niobium content of 662 ppm in the Arkansas bauxite ores. Niobium progressively increases in concentration from parent syenite (247 ppm) to clays (315 ppm) and further from bauxite (662 ppm) to processed residues (1,075 ppm). Low concentrations of scandium were found in all samples, averaging 10 ppm or less in the parent rock (syenite), bauxite, clays, and processing residues. Modest concentrations of the light and heavy REEs were found in samples of bauxite ores, bauxitic clays and interbedded clays, syenite, and the residues of ore. The highest REE values were found in processed residues, with average concentrations of 613 ppm total light REEs and 130 ppm total heavy REEs. These concentrations suggest that additional processing to recover REEs is unlikely to be economic in the foreseeable future.


","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211073","usgsCitation":"Van Gosen, B.S., and Choate, L.M., 2021, Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas: U.S. Geological Survey Open-File Report 2021–1073, 18 p., https://doi.org/10.3133/ofr20211073.","productDescription":"Report: vi, 18 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-122543","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":387553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1073/coverthb.jpg"},{"id":387554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1073/ofr20211073.pdf","text":"Report","size":"2.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1073"},{"id":387555,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P999FSXM","text":"USGS data release","linkHelpText":"Geochemical analyses of bauxite and associated rocks from the Arkansas bauxite region, central Arkansas"}],"country":"United States","state":"Arkansas","county":"Pulaski County, Saline County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.71774291992186,\n 34.473165492385505\n ],\n [\n -92.21923828124999,\n 34.473165492385505\n ],\n [\n -92.21923828124999,\n 34.80140001594981\n ],\n [\n -92.71774291992186,\n 34.80140001594981\n ],\n [\n -92.71774291992186,\n 34.473165492385505\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225

","tableOfContents":"","publishedDate":"2021-08-05","noUsgsAuthors":false,"publicationDate":"2021-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":820102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choate, LaDonna M. 0000-0002-0229-7210 lchoate@usgs.gov","orcid":"https://orcid.org/0000-0002-0229-7210","contributorId":1176,"corporation":false,"usgs":true,"family":"Choate","given":"LaDonna","email":"lchoate@usgs.gov","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":820103,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}