{"pageNumber":"608","pageRowStart":"15175","pageSize":"25","recordCount":184689,"records":[{"id":70210993,"text":"70210993 - 2020 - Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","interactions":[],"lastModifiedDate":"2020-08-04T14:24:42.736989","indexId":"70210993","displayToPublicDate":"2020-06-30T08:41:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers","docAbstract":"In the arid landscape south of the Grand Canyon, natural springs and seeps are a critical resource for endemic species and Native American tribes. Groundwater is potentially threatened by expanding populations, visitations, and mineral extraction activities. Environmental tracers including noble gases, stable isotopes of hydrogen and oxygen in water, tritium, and carbon-14 were used to characterize recharge sources and flow paths in South Rim aquifers. Results confirm the regional Redwall-Muav Aquifer as the primary groundwater source to springs. However, a second local recharge source is required to explain the detection of tritium. Two probable sources are identified as: low-elevation infiltration of surface run-off with warm noble gas recharge temperatures, high excess air, and relatively low fractions of winter recharge, and high-elevation plateau recharge with cool recharge temperatures, low excess air, and fraction of winter recharge of ~ 1. Previous investigators have linked spring occurrence with regional faults and fractures. We show such features are also the likely control chemical mixing between the regional and local groundwater sources, the transport of deeply sourced and local recharge fluids, groundwater age, and thus the relative vulnerability of groundwater to depletion and contamination. The new conceptual model of groundwater sources and flow paths suggest many South Rim springs may respond on the order of 10s to 100s of years to groundwater depletion and contamination, even though the majority of groundwater flow is along longer flow paths with longer lag times. The magnitude of response to short term changes in the flow system remains unclear.","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02193-z","usgsCitation":"Solder, J.E., Beisner, K.R., Anderson, J.R., and Bills, D.J., 2020, Rethinking groundwater flow on the South Rim of the Grand Canyon, USA: Characterizing recharge sources and flow paths with environmental tracers: Hydrogeology Journal, v. 28, p. 1593-1613, https://doi.org/10.1007/s10040-020-02193-z.","productDescription":"21 p.","startPage":"1593","endPage":"1613","ipdsId":"IP-110439","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":456198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-020-02193-z","text":"Publisher Index Page"},{"id":436904,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WX8N0L","text":"USGS data release","linkHelpText":"Noble gas isotopes and lumped parameter model results for environmental tracer based groundwater ages, South Rim Grand Canyon, Arizona, USA"},{"id":376255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"South Rim of the Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4835205078125,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 35.7019167328534\n ],\n [\n -111.65679931640625,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 36.18000806322456\n ],\n [\n -112.4835205078125,\n 35.7019167328534\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Solder, John E. 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":201953,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Jessica R. 0000-0002-3286-7552 jranderson@usgs.gov","orcid":"https://orcid.org/0000-0002-3286-7552","contributorId":193158,"corporation":false,"usgs":true,"family":"Anderson","given":"Jessica","email":"jranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bills, Donald J. 0000-0001-8955-3370 djbills@usgs.gov","orcid":"https://orcid.org/0000-0001-8955-3370","contributorId":177439,"corporation":false,"usgs":true,"family":"Bills","given":"Donald","email":"djbills@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228412,"text":"70228412 - 2020 - Diet of a rare herbivore based on DNA metabarcoding of feces: Selection, seasonality, and survival","interactions":[],"lastModifiedDate":"2022-02-10T14:52:36.111767","indexId":"70228412","displayToPublicDate":"2020-06-30T08:28:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Diet of a rare herbivore based on DNA metabarcoding of feces: Selection, seasonality, and survival","docAbstract":"

In herbivores, survival and reproduction are influenced by quality and quantity of forage, and hence, diet and foraging behavior are the foundation of an herbivore's life history strategy. Given the importance of diet to most herbivores, it is imperative that we know the species of plants they prefer, especially for herbivorous species that are at risk for extinction. However, it is often difficult to identify the diet of small herbivores because: (a) They are difficult to observe, (b) collecting stomach contents requires sacrificing animals, and (c) microhistology requires accurately identifying taxa from partially digested plant fragments and likely overemphasizes less-digestible taxa. The northern Idaho ground squirrel (Urocitellus brunneus) is federally threatened in the United States under the Endangered Species Act. We used DNA metabarcoding techniques to identify the diet of 188 squirrels at 11 study sites from fecal samples. We identified 42 families, 126 genera, and 120 species of plants in the squirrel's diet. Our use of three gene regions was beneficial because reliance on only one gene region (e.g., only trnL) would have caused us to miss >30% of the taxa in their diet. Northern Idaho ground squirrel diet differed between spring and summer, frequency of many plants in the diet differed from their frequency within their foraging areas (evidence of selective foraging), and several plant genera in their diet were associated with survival. Our results suggest that while these squirrels are generalists (they consume a wide variety of plant species), they are also selective and do not eat plants relative to availability. Consumption of particular genera such as Perideridia may be associated with higher overwinter survival.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6488","usgsCitation":"Goldberg, A.R., Conway, C.J., Tank, D.C., Andrews, K.R., Gour, D.S., and Waits, L.P., 2020, Diet of a rare herbivore based on DNA metabarcoding of feces: Selection, seasonality, and survival: Ecology and Evolution, v. 10, no. 14, p. 7627-7643, https://doi.org/10.1002/ece3.6488.","productDescription":"17 p.","startPage":"7627","endPage":"7643","ipdsId":"IP-111251","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":456201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6488","text":"Publisher Index Page"},{"id":395765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Adams 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Amanda R.","contributorId":275716,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda","email":"","middleInitial":"R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tank, David C.","contributorId":275717,"corporation":false,"usgs":false,"family":"Tank","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrews, Kimberly R.","contributorId":275718,"corporation":false,"usgs":false,"family":"Andrews","given":"Kimberly","email":"","middleInitial":"R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gour, Digpal S.","contributorId":275719,"corporation":false,"usgs":false,"family":"Gour","given":"Digpal","email":"","middleInitial":"S.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waits, Lisette P.","contributorId":275720,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette","email":"","middleInitial":"P.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":834248,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215652,"text":"70215652 - 2020 - Estimation of vital population rates to assess the relative health of mussel assemblages in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2020-10-27T12:49:45.812712","indexId":"70215652","displayToPublicDate":"2020-06-30T07:43:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of vital population rates to assess the relative health of mussel assemblages in the Upper Mississippi River","docAbstract":"
  1. Native freshwater mussels are a guild of benthic, filter feeding invertebrates that perform important ecological functions in rivers. Because of their long lifespans (30–50 years or longer), mussels are slow to respond to human‐induced alterations. Thus, development of sensitive indicators of mussel population responses to river conditions and management would be beneficial. Compared to marine species, estimation of vital rates (e.g. survival, growth) in freshwater mussels has received little attention.
  2. We placed passively integrated transponder tags on 578 mussels of four species (Amblema plicata, Cyclonaias pustulosa, Obliquaria reflexa, and Pleurobema sintoxia) in a well‐studied mussel assemblage in a side channel of the upper Mississippi River. Growth and survival of tagged mussels were assessed annually for 4 years across core (high density) and peripheral (low density) areas of the assemblage.
  3. Overall survival was highly variable, ranging from c. 15 to 90%, and was related to life history, habitat quality, and hydrologic events. Survival, which varied significantly among species and over time, was consistently higher in the dense and species‐rich core of the mussel assemblage, relative to the periphery because substrates were consistently more stable in the core of the mussel bed relative to the periphery. Substrate movement during low flows was an order of magnitude lower in the core relative to the periphery, and survival was inversely related to stability of river substrates. Patterns in habitat‐specific survival indicate source–sink population dynamics such that mussels in the core habitat provide recruitment to the periphery, but mussels in the periphery are subject to unsustainably low survival; additional studies to track the source of recruitment in the periphery are needed to test this hypothesis.
  4. Growth rate did not vary significantly between core and peripheral areas but did vary by species. Growth rate (proportional change per year) declined with age, and was similar at mean age for A. plicata (0.016 per year), P. sintoxia (0.015 per year), and C. pustulosa (0.013 per year), but much lower for O. reflexa (0.008 per year).
  5. Effective management decisions for mussels requires a better understanding of how vital rates govern populations and how they vary across a suite of physical and biological factors. Information on how population vital rates vary among species and over time gives managers another tool to understand how mussels may respond to management actions such as habitat restoration projects. Given the importance of substrate stability inferred from this study, management actions that maintain or increase substrate stability are likely to result in high quality mussel assemblages and may restore a valuable component of ecosystem function in this region.
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13575","usgsCitation":"Newton, T., Zigler, S., Ries, P., Davis, M., and Smith, D.R., 2020, Estimation of vital population rates to assess the relative health of mussel assemblages in the Upper Mississippi River: Freshwater Biology, v. 65, no. 10, p. 1726-1739, https://doi.org/10.1111/fwb.13575.","productDescription":"14 p.","startPage":"1726","endPage":"1739","ipdsId":"IP-112461","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":379796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.768798828125,\n 43.68773584519811\n ],\n [\n -91.01074218749999,\n 43.68773584519811\n ],\n [\n -91.01074218749999,\n 44.11125397357155\n ],\n [\n -91.768798828125,\n 44.11125397357155\n ],\n [\n -91.768798828125,\n 43.68773584519811\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Newton, Teresa 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":150098,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":803069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zigler, Steven J. 0000-0002-4153-0652","orcid":"https://orcid.org/0000-0002-4153-0652","contributorId":244025,"corporation":false,"usgs":false,"family":"Zigler","given":"Steven J.","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":803070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ries, Patricia R. 0000-0001-5095-7896","orcid":"https://orcid.org/0000-0001-5095-7896","contributorId":244026,"corporation":false,"usgs":false,"family":"Ries","given":"Patricia R.","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":803071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Mike","contributorId":150099,"corporation":false,"usgs":false,"family":"Davis","given":"Mike","email":"","affiliations":[{"id":17913,"text":"River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":803072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":803073,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216279,"text":"70216279 - 2020 - Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico","interactions":[],"lastModifiedDate":"2020-11-11T13:41:55.681915","indexId":"70216279","displayToPublicDate":"2020-06-30T07:37:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico","docAbstract":"

Mobility is an important element of landslide hazard and risk assessments yet has been seldom studied for shallow landslides and debris flows in tropical environments. In September 2017, Hurricane Maria triggered > 70,000 landslides across Puerto Rico. Using aerial imagery and a lidar digital elevation model (DEM), we mapped and characterized the mobility of debris slides and flows in four different geologic materials: (1) mudstone, siltstone, and sandstone; (2) submarine basalt and chert; (3) marine volcaniclastics; and (4) granodiorite. We used the ratio of landslide-fall height (H) to travel length (L), H/L, to assess the mobility of landslides in each material. Additionally, we differentiated between landslides with single and multiple source areas and landslides that either did or did not enter drainages. Overall, extreme rainfall contributed to the mobility of landslides during Hurricane Maria, and our results showed that the mobility of debris slides and flows in Puerto Rico increased linearly as a function of the number of source areas that coalesced. Additionally, landslides that entered drainages were more mobile than those that did not. We found that landslides in soils developed on marine volcaniclastics were the most mobile and landslides in soils on submarine basalt and chert were the least mobile. While landslides were generally small (< 100 m2) and displayed a wide range of H/L values (0.1–2), coalescence increased the mobility of landslides that transitioned to debris flows. The high but variable mobility of landslides that occurred during Hurricane Maria and the associated hazards highlight the importance of characterizing and understanding the factors influencing landslide mobility in Puerto Rico and other tropical environments.



","language":"English","publisher":"Springer","doi":"10.1007/s10346-020-01445-z","usgsCitation":"Bessette-Kirton, E., Coe, J.A., Schulz, W.H., Cerovski-Darriau, C., and Einbund, M.M., 2020, Mobility characteristics of landslides triggered by Hurricane Maria in Puerto Rico: Landslides, v. 17, no. 12, p. 2795-2809, https://doi.org/10.1007/s10346-020-01445-z.","productDescription":"15 p.","startPage":"2795","endPage":"2809","ipdsId":"IP-114642","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":456204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10346-020-01445-z","text":"Publisher Index Page"},{"id":380402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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Rico\",\"nation\":\"USA \"}}]}","volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bessette-Kirton, Erin K. 0000-0002-2797-0694","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":225097,"corporation":false,"usgs":false,"family":"Bessette-Kirton","given":"Erin K.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":804574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":804575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":804576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":804577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Einbund, Mason Muir 0000-0002-8449-8015","orcid":"https://orcid.org/0000-0002-8449-8015","contributorId":244781,"corporation":false,"usgs":true,"family":"Einbund","given":"Mason","email":"","middleInitial":"Muir","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":804578,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217072,"text":"70217072 - 2020 - Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA","interactions":[],"lastModifiedDate":"2021-01-04T13:17:05.281621","indexId":"70217072","displayToPublicDate":"2020-06-30T07:12:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA","docAbstract":"

Study region

The study was conducted in the Northern Atlantic Coastal Plain aquifer system, in the eastern USA.

Study focus

Groundwater pH and redox conditions are fundamental chemical characteristics controlling the distribution of many contaminants of concern for drinking water or the ecological health of receiving waters. In this study, pH and redox conditions were modeled and mapped in a complex, layered aquifer system. Machine-learning methods (boosted regression trees) were applied to data from 3000 to 5000 wells. Predicted pH and the probability of anoxic conditions, defined by three thresholds of dissolved oxygen (0.5, 1, and 2 mg/L), were mapped at the 1-km2 scale for each of 10 regional aquifer layers.

New Hydrological Insights for the Region

Maps depict the extent of acidic groundwater and oxic conditions in the shallow, unconfined surficial aquifer and in unconfined, recharge-proximal areas of underlying aquifers, in contrast to alkaline and anoxic groundwater elsewhere. Geographic patterns and influential predictors–including elevation, overlying confining-units thickness, and simulated groundwater age and flux–are consistent with prior understanding of the processes controlling pH and redox in the aquifer system. The model-based maps support robust estimates of aquifer proportions, either areal or volumetric, likely to contain groundwater of a specified quality or be vulnerable to specific pH- or redox-sensitive contaminants. The machine-learning methods were an effective tool to map groundwater quality at the regional scale.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2020.100697","usgsCitation":"DeSimone, L.A., Pope, J.P., and Ransom, K.M., 2020, Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA: Journal of Hydrology: Regional Studies, v. 30, 100697, 20 p., https://doi.org/10.1016/j.ejrh.2020.100697.","productDescription":"100697, 20 p.","ipdsId":"IP-112751","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456207,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2020.100697","text":"Publisher Index Page"},{"id":436905,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94DYERF","text":"USGS data release","linkHelpText":"Data used to model and map pH and redox conditions in the Northern Atlantic Coastal Plain aquifer system, eastern USA"},{"id":381836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Maryland, Delaware, Virginia","otherGeospatial":"North Atlantic Coastal Plain Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7509765625,\n 40.3130432088809\n ],\n [\n -76.0693359375,\n 38.54816542304656\n ],\n [\n -76.6845703125,\n 37.26530995561875\n ],\n [\n -75.89355468749999,\n 36.35052700542763\n ],\n [\n -74.0478515625,\n 40.212440718286466\n ],\n [\n -74.7509765625,\n 40.3130432088809\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeSimone, Leslie A. 0000-0003-0774-9607 ldesimon@usgs.gov","orcid":"https://orcid.org/0000-0003-0774-9607","contributorId":195635,"corporation":false,"usgs":true,"family":"DeSimone","given":"Leslie","email":"ldesimon@usgs.gov","middleInitial":"A.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Jason P. 0000-0003-3199-993X jpope@usgs.gov","orcid":"https://orcid.org/0000-0003-3199-993X","contributorId":2044,"corporation":false,"usgs":true,"family":"Pope","given":"Jason","email":"jpope@usgs.gov","middleInitial":"P.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ransom, Katherine Marie 0000-0001-6195-7699","orcid":"https://orcid.org/0000-0001-6195-7699","contributorId":239552,"corporation":false,"usgs":true,"family":"Ransom","given":"Katherine","email":"","middleInitial":"Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807484,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216055,"text":"70216055 - 2020 - Magnetic field variations in Alaska: Recording space weather events on seismic stations in Alaska","interactions":[],"lastModifiedDate":"2020-11-05T12:42:11.544955","indexId":"70216055","displayToPublicDate":"2020-06-30T06:48:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Magnetic field variations in Alaska: Recording space weather events on seismic stations in Alaska","docAbstract":"

Seismometers are highly sensitive instruments to not only ground motion but also many other nonseismic noise sources (e.g., temperature, pressure, and magnetic field variations). We show that the Alaska component of the Transportable Array is particularly susceptible to recording magnetic storms and other space weather events because the sensors used in this network are unshielded and magnetic flux variations are stronger at higher latitudes. We also show that vertical‐component seismic records across Alaska are directly recording magnetic field variations between 40 and 800 s period as opposed to actual ground motion during geomagnetic events with sensitivities ranging from 0.004 to 0.48&#x2009;&#x2009;(m/s2)/T\">0.48  (m/s2)/T0.48  (m/s2)/T⁠. These sensitivities were found on a day where the root mean square variation in the magnetic field was 225 nT. Using a method developed by Forbriger (2007, his section 3.1), we show that improving vertical seismic resolution of an unshielded sensor by as much as 10 dB in the 100–400 s period band using magnetic data from a collocated three‐component magnetometer is possible. However, due to large spatial variations in Earth’s magnetic field, this methodology becomes increasingly ineffective as the distance between the seismometer and magnetometer increases (no more than 200 km separation). A potential solution to this issue may be to incorporate relatively low‐cost magnetometers as an additional environmental data stream at high‐latitude seismic stations. We demonstrate that the Bartington Mag‐690 sensors currently deployed at Global Seismographic Network sites are not only acceptable for performing corrections to seismic data, but are also capable of recording many magnetic field signals with similar signal‐to‐noise ratios, in the 20–1000 s period band, as the observatory grade magnetometers operated by the U.S. Geological Survey Geomagnetism Program. This approach would densify magnetic field observations and could also contribute to space weather monitoring by supplementing highly calibrated magnetometers with additional sensors.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200019","usgsCitation":"Ringler, A.T., Anthony, R.E., Wilson, D.C., Claycomb, A.E., and Spritzer, J., 2020, Magnetic field variations in Alaska: Recording space weather events on seismic stations in Alaska: Bulletin of the Seismological Society of America, v. 110, no. 5, p. 2530-2540, https://doi.org/10.1785/0120200019.","productDescription":"11 p.","startPage":"2530","endPage":"2540","ipdsId":"IP-118024","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":380116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Claycomb, Abram E. 0000-0002-2908-2586 aclaycomb@usgs.gov","orcid":"https://orcid.org/0000-0002-2908-2586","contributorId":236928,"corporation":false,"usgs":true,"family":"Claycomb","given":"Abram","email":"aclaycomb@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803892,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spritzer, John 0000-0002-2147-530X jspritzer@usgs.gov","orcid":"https://orcid.org/0000-0002-2147-530X","contributorId":244361,"corporation":false,"usgs":true,"family":"Spritzer","given":"John","email":"jspritzer@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803893,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210910,"text":"70210910 - 2020 - Frequency of extreme freeze events controls the distribution and structure of black mangroves (Avicennia germinans) near their northern range limit in coastal Louisiana","interactions":[],"lastModifiedDate":"2020-10-14T20:37:20.802359","indexId":"70210910","displayToPublicDate":"2020-06-29T13:31:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Frequency of extreme freeze events controls the distribution and structure of black mangroves (Avicennia germinans) near their northern range limit in coastal Louisiana","title":"Frequency of extreme freeze events controls the distribution and structure of black mangroves (Avicennia germinans) near their northern range limit in coastal Louisiana","docAbstract":"

Aim

Climate change is expected to result in the tropicalization of coastal wetlands in the northern Gulf of Mexico, as warming winters allow tropical mangrove forests to expand their distribution poleward at the expense of temperate salt marshes. Data limitations near mangrove range limits have hindered understanding of the effects of winter temperature extremes on mangrove distribution and structure. Here, we investigated the influence of extreme freeze events on the abundance, height and coverage of black mangroves (Avicennia germinans ) near their northern range limit in Louisiana.

Location

Coastal Louisiana, USA.

Methods

We quantified the relationships between the frequency of extreme freeze events and A. germinans abundance, height and coverage using: (a) mangrove observation points recorded via aerial surveys from a fixed‐wing aircraft; (b) 30 years of temperature data; and (c) mangrove mortality and leaf damage temperature thresholds. We used freeze frequency data and mangrove–climate relationships to evaluate and spatially depict the risk of A. germinans freeze damage across Louisiana.

Results

We identified strong negative relationships between the frequency of extreme freeze events and A. germinans abundance, height and coverage. Avicennia germinans is most abundant, tall and continuous along the south‐eastern outer coast of Louisiana, where the frequency of extreme freeze events is reduced (i.e., lower risk of mangrove freeze damage) by the buffering effects of comparatively warm Gulf of Mexico waters. Conversely, the risk of A. germinans freeze damage has historically been very high across Louisiana's Chenier Plain and within more inland wetlands in the Deltaic Plain.

Main conclusions

Our analyses advance understanding of how the frequency of extreme freeze events controls the distribution, height and coverage of A. germinans near its northern range limit. In addition to informing climate‐smart coastal restoration efforts, our findings can be used to better anticipate and prepare for the tropicalization of temperate wetlands due to climate change.

","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13119","usgsCitation":"Osland, M., Day, R., and Michot, T.C., 2020, Frequency of extreme freeze events controls the distribution and structure of black mangroves (Avicennia germinans) near their northern range limit in coastal Louisiana: Diversity and Distributions, v. 26, no. 10, p. 1366-1382, https://doi.org/10.1111/ddi.13119.","productDescription":"Article: 17 p.; Data Release","startPage":"1366","endPage":"1382","ipdsId":"IP-116815","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456209,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13119","text":"Publisher Index Page"},{"id":376104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379388,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RC8EIE"}],"country":"United States","state":"Louisiana","otherGeospatial":"Coastal Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.779296875,\n 29.152161283318915\n ],\n [\n -92.46093749999999,\n 28.998531814051795\n ],\n [\n -90.615234375,\n 28.8831596093235\n ],\n [\n -89.07714843749999,\n 29.305561325527698\n ],\n [\n -89.384765625,\n 30.29701788337205\n ],\n [\n -89.82421875,\n 30.600093873550072\n ],\n [\n -91.62597656249999,\n 30.44867367928756\n ],\n [\n -93.6474609375,\n 30.259067203213018\n ],\n [\n -94.130859375,\n 30.031055426540206\n ],\n [\n -93.779296875,\n 29.152161283318915\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":214842,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Richard 0000-0002-5959-7054","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":221895,"corporation":false,"usgs":true,"family":"Day","given":"Richard","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":792080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michot, Thomas C.","contributorId":228798,"corporation":false,"usgs":false,"family":"Michot","given":"Thomas","email":"","middleInitial":"C.","affiliations":[{"id":41511,"text":"USGS WARC (retired)","active":true,"usgs":false}],"preferred":false,"id":792081,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210812,"text":"70210812 - 2020 - After-hatch and hatch year Buff-breasted Sandpipers (Calidris subruficollis) can be sexed accurately using morphometric measures","interactions":[],"lastModifiedDate":"2020-06-30T14:38:17.416727","indexId":"70210812","displayToPublicDate":"2020-06-29T09:37:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"displayTitle":"After-hatch and hatch year Buff-breasted Sandpipers (Calidris subruficollis) can be sexed accurately using morphometric measures","title":"After-hatch and hatch year Buff-breasted Sandpipers (Calidris subruficollis) can be sexed accurately using morphometric measures","docAbstract":"

Determining the sex of birds quickly in the field can help in studies of behavior and distribution, and when selecting particular sexes for deploying tracking devices or collecting samples. However, discerning males from females is difficult in species that are plumage monomorphic and have overlapping sexual-size dimorphism, as in Buff-breasted Sandpipers Calidris subruficollis. We developed three discriminant functions to sex Buff-breasted Sandpipers based on measurements of live birds captured in Brazil whose sex was confirmed with molecular techniques. We validated these discriminant functions using morphometric measures from other independent samples of known-sex live birds from wintering (Brazil), migration (Texas), and breeding (Alaska) sites. Discriminant functions derived from birds captured in Brazil accurately sexed ≥88% of the validation sample from Brazil, Texas, and Alaska. Errors in classification occurred among males on the wintering (0–5%) and breeding (8–12%) grounds, and females during migration (0–11%). Discriminant functions worked well because of the substantial sexual size dimorphism present in the species, with male traits being in general 5.2–10.4% larger than female traits. The size of morphological traits did not vary by age (after controlling for sex) for birds sampled on the wintering grounds and during migration. Our results indicate that discriminant functions can be used to sex after-hatch year (AHY) Buff-breasted Sandpipers throughout their range, and for hatch year (HY) birds during their first southbound migration and winter. Being able to accurately sex both AHY and HY birds using only morphological measurements will improve studies of the ecology and population structure of this species and enhance the application of conservation measures.

","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00189","usgsCitation":"de Almeida, J.B., Lopes, I.F., Oring, L., Tibbitts, T.L., Pajot, L.M., and Lanctot, R., 2020, After-hatch and hatch year Buff-breasted Sandpipers (Calidris subruficollis) can be sexed accurately using morphometric measures: Wader Study, v. 127, no. 2, p. 37-42, https://doi.org/10.18194/ws.00189.","productDescription":"6 p.","startPage":"37","endPage":"42","ipdsId":"IP-112351","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":436906,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LVV8V6","text":"USGS data release","linkHelpText":"Buff-breasted Sandpiper (Calidris subruficollis) measurement data from Brazil, Texas, and Alaska"},{"id":376016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"de Almeida, Juliana Bose","contributorId":189645,"corporation":false,"usgs":false,"family":"de Almeida","given":"Juliana","middleInitial":"Bose","affiliations":[],"preferred":false,"id":791547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopes, Iara F.","contributorId":168611,"corporation":false,"usgs":false,"family":"Lopes","given":"Iara","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":791548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oring, Lewis","contributorId":225545,"corporation":false,"usgs":false,"family":"Oring","given":"Lewis","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":791549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":791550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pajot, Lisa M. 0000-0001-5704-2381 lpajot@usgs.gov","orcid":"https://orcid.org/0000-0001-5704-2381","contributorId":201730,"corporation":false,"usgs":true,"family":"Pajot","given":"Lisa","email":"lpajot@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":791551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":791552,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210838,"text":"70210838 - 2020 - Refining genetic boundaries for Agassiz’s desert tortoise (Gopherus agassizii) in the western Sonoran Desert: The influence of the Coachella Valley on gene flow among populations in southern California","interactions":[],"lastModifiedDate":"2020-10-12T16:52:30.666957","indexId":"70210838","displayToPublicDate":"2020-06-29T09:08:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5093,"text":"Frontiers of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Refining genetic boundaries for Agassiz’s desert tortoise (Gopherus agassizii) in the western Sonoran Desert: The influence of the Coachella Valley on gene flow among populations in southern California","docAbstract":"

Understanding the influence of geographic features on the evolutionary history and population structure of a species can assist wildlife managers in delimiting genetic units (GUs) for conservation and management. Landscape features including mountains, low elevation depressions, and even roads can influence connectivity and gene flow among Agassiz’s desert tortoise (Gopherus agassizii) populations. Substantial changes in the landscape of the American Southwest occurred during the last six million years (including the formation of the Gulf of California and the lower Colorado River), which shaped the distribution and genetic structuring of tortoise populations. The area northwest of the Gulf of California is occupied by the Salton Trough, including the Coachella Valley at its northern end. Much of this area is below sea level and unsuitable as tortoise habitat, thus forming a potential barrier for gene flow. We assessed genetic relationships among three tortoise populations separated by the Coachella Valley. Two adjacent populations were on the east side of the valley in the foothills of the Cottonwood and Orocopia mountains separated by Interstate 10. The third population, Mesa, was located about 87 km away in the foothills of the San Bernardino Mountains at the far northwestern tip of the valley. The Cottonwood and Orocopia localities showed genetic affiliation with the adjacent Colorado Desert GU immediately to the east, and the Mesa population exhibited affiliation with both the Southern Mojave and Colorado Desert GUs, despite having a greater geographic distance (0.5x–1.5x greater) to the Colorado Desert GU. The genetic affiliation with the Colorado Desert GU suggests that the boundary for that GU needs to be substantially extended to the west to include the desert tortoise populations around the Coachella Valley. Their inclusion in the Colorado Desert GU may benefit these often overlooked populations when recovery actions are considered.

","language":"English","publisher":"University of California","doi":"10.21425/F5FBG46888","usgsCitation":"Lovich, J.E., Edwards, T., Berry, K.H., Puffer, S., Cummings, K.L., R., E.J., Agha, M., Wood, R., Brundige, K.D., and Murphy, R.W., 2020, Refining genetic boundaries for Agassiz’s desert tortoise (Gopherus agassizii) in the western Sonoran Desert: The influence of the Coachella Valley on gene flow among populations in southern California: Frontiers of Biogeography, v. 12, no. 3, e46888, 14 p., https://doi.org/10.21425/F5FBG46888.","productDescription":"e46888, 14 p.","ipdsId":"IP-115804","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":456214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21425/f5fbg46888","text":"Publisher Index Page"},{"id":375969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6748046875,\n 33.47727218776036\n ],\n [\n -115.72723388671875,\n 33.47727218776036\n ],\n [\n -115.72723388671875,\n 34.02762404762424\n ],\n [\n -116.6748046875,\n 34.02762404762424\n ],\n [\n -116.6748046875,\n 33.47727218776036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science 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0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":791679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cummings, Kristy L. 0000-0002-8316-5059","orcid":"https://orcid.org/0000-0002-8316-5059","contributorId":202061,"corporation":false,"usgs":true,"family":"Cummings","given":"Kristy","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":791680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"R., Ennen Joshua","contributorId":195518,"corporation":false,"usgs":false,"family":"R.","given":"Ennen","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":791681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":791682,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wood, Rachel 0000-0001-7953-3173","orcid":"https://orcid.org/0000-0001-7953-3173","contributorId":225576,"corporation":false,"usgs":false,"family":"Wood","given":"Rachel","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":791683,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brundige, Kathleen D.","contributorId":193101,"corporation":false,"usgs":false,"family":"Brundige","given":"Kathleen","email":"","middleInitial":"D.","affiliations":[{"id":33710,"text":"Coachella Valley Conservation Commission, 73-710 Fred Waring Drive, Suite 200, Palm Desert, CA 92260-2516, USA","active":true,"usgs":false}],"preferred":false,"id":791684,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Murphy, Robert W.","contributorId":147498,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":791685,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70212966,"text":"70212966 - 2020 - Evidence for a concealed Midcontinent Rift-related northeast Iowa intrusive complex","interactions":[],"lastModifiedDate":"2020-09-02T14:15:18.406979","indexId":"70212966","displayToPublicDate":"2020-06-29T08:56:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for a concealed Midcontinent Rift-related northeast Iowa intrusive complex","docAbstract":"

Large amplitude aeromagnetic and gravity anomalies over a ~9500 km2 area of northeast Iowa and southeast Minnesota have been interpreted to reflect the northeast Iowa intrusive complex (NEIIC), a buried intrusive igneous complex composed of mafic/ultramafic rocks in the Yavapai Province (1.8–1.7 Ga). Hundreds of meters of Paleozoic sedimentary cover and a paucity of basement drilling have prevented detailed studies of the NEIIC. Long considered, but not proven, to be related to the ~1.1 Ga Midcontinent Rift System (MRS), the NEIIC is comparable in areal extent to the richly mineralized Duluth Complex and is similarly located near the margin of the MRS. New geochronological and geophysical data together support an MRS affinity for the NEIIC. A dike swarm imaged in aeromagnetic data is cut by intrusions of the NEIIC, and a new apatite U-Pb date of ~1170 Ma on one of the dikes thus represents a maximum age for the NEIIC. A minimum age constraint is suggested by (1) large-volume magmatism associated with the MRS that was the last such event to affect the region; and (2) the presence of reversely magnetized dikes, similar in character to MRS-related dikes elsewhere, that cut several intrusions of the NEIIC. The NEIIC is largely characterized by the presence of multiple zoned intrusions, many of which contain large volumes of mafic-ultramafic rocks and have strong geophysical similarities to alkaline intrusive complexes elsewhere, including the MRS-related Coldwell Complex of Ontario. The largest of the zoned intrusions are ~40 km in diameter and are interpreted to have thicknesses of many kilometers. Suspected faults, alignments of intrusions, and intrusive margins tend to be aligned along northwest and northeast trends that match the trends of the Belle Plaine fault zone and Fayette structural zone, both previously interpreted as pre-MRS, possibly lithospheric-scale discontinuities that may have controlled NEIIC emplacement. These interpretations collectively imply notable potential for the NEIIC to host several different types of undiscovered base metal and critical mineral deposits.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2020.105845","usgsCitation":"Drenth, B.J., Souders, A., Schulz, K.J., Feinberg, J.M., Anderson, R., Chandler, V.W., Cannon, W.F., and Clark, R., 2020, Evidence for a concealed Midcontinent Rift-related northeast Iowa intrusive complex: Precambrian Research, v. 347, 105845, 23 p., https://doi.org/10.1016/j.precamres.2020.105845.","productDescription":"105845, 23 p.","ipdsId":"IP-117960","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":456217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2020.105845","text":"Publisher Index Page"},{"id":378096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.2744140625,\n 41.96765920367816\n ],\n [\n -91.49414062499999,\n 43.197167282501276\n ],\n [\n -92.59277343749999,\n 44.08758502824516\n ],\n [\n -93.07617187499999,\n 43.96119063892024\n ],\n [\n -92.8125,\n 42.58544425738491\n ],\n [\n -92.59277343749999,\n 41.244772343082076\n ],\n [\n -92.021484375,\n 41.178653972331674\n ],\n [\n -91.23046875,\n 41.60722821271717\n ],\n [\n -91.2744140625,\n 41.96765920367816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"347","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":797835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, A. Kate 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":239820,"corporation":false,"usgs":false,"family":"Souders","given":"A. Kate","affiliations":[],"preferred":false,"id":797836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, Klaus J. 0000-0003-2967-4765 kschulz@usgs.gov","orcid":"https://orcid.org/0000-0003-2967-4765","contributorId":2438,"corporation":false,"usgs":true,"family":"Schulz","given":"Klaus","email":"kschulz@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinberg, Joshua M.","contributorId":194010,"corporation":false,"usgs":false,"family":"Feinberg","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":797838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Raymond R.","contributorId":22430,"corporation":false,"usgs":true,"family":"Anderson","given":"Raymond R.","affiliations":[],"preferred":false,"id":797839,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chandler, Val W.","contributorId":117484,"corporation":false,"usgs":true,"family":"Chandler","given":"Val","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":797840,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cannon, William F. 0000-0002-2699-8118 wcannon@usgs.gov","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":1883,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"wcannon@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":797841,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clark, Ryan","contributorId":193538,"corporation":false,"usgs":false,"family":"Clark","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":797842,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215068,"text":"70215068 - 2020 - Structural controls on slope failure within the western Santa Barbara Channel based on 2D and 3D seismic imaging","interactions":[],"lastModifiedDate":"2020-10-07T13:53:27.178999","indexId":"70215068","displayToPublicDate":"2020-06-29T08:42:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7143,"text":"Geochemistry, Geophysics, and Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Structural controls on slope failure within the western Santa Barbara Channel based on 2D and 3D seismic imaging","docAbstract":"

The Santa Barbara Channel, offshore California, contains several submarine landslides and ample evidence for incipient failure. This region hosts active thrust and reverse faults that accommodate several mm/yr of convergence, yet the relationships between tectonic deformation and slope failure remain unclear. We present 3‐D and 2‐D multichannel seismic reflection (MCS) data sets, multibeam bathymetry, and chronostratigraphic constraints to investigate the controls on slope failure. Splay faulting along the North Channel Deformation Trend (NCDT) coincides with a distinct zone of compressional uplift and onlapping of steeply dipping Quaternary strata. The NCDT is spatially correlated with seafloor fissures, and 3‐D seismic analyses reveal an intricate system of en echelon reverse faults that offset sediments younger than ~25 ka. Localized uplift zones are located between faults, one of which underlies the Gaviota landslide headscarp. We observe a direct relationship between slope failure and along‐strike variations in the tectonostratigraphic framework. Based on geophysical properties at Ocean Drilling Program (ODP) Site 893, we predict a trend in compaction and porosity reduction in the basin that drives pore fluids up‐dip, toward the zone of onlap above the NCDT, thus reducing slope stability. This interplay between tectonic, sedimentary, and fluid‐flow processes along the NCDT has created a confluence of preconditioning factors, with Gaviota and Goleta landslides being distinguished from the surrounding slopes by their position above the NCDT. The distribution of seafloor fissures suggests sections of the slope remain unstable and are prone to future landsliding. These results provide insights into the processes and 3‐D feedbacks that lead to slope instability along other convergent margins.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GC009055","usgsCitation":"Kluesner, J.W., Brothers, D.S., Wright, A.L., and Johnson, S., 2020, Structural controls on slope failure within the western Santa Barbara Channel based on 2D and 3D seismic imaging: Geochemistry, Geophysics, and Geosystems, v. 21, no. 8, e2020GC009055, 34 p., https://doi.org/10.1029/2020GC009055.","productDescription":"e2020GC009055, 34 p.","ipdsId":"IP-117824","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":456220,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gc009055","text":"Publisher Index Page"},{"id":379168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara channel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.43624877929688,\n 34.04241857075928\n ],\n [\n -119.44061279296875,\n 34.04241857075928\n ],\n [\n -119.44061279296875,\n 34.44995361537075\n ],\n [\n -120.43624877929688,\n 34.44995361537075\n ],\n [\n -120.43624877929688,\n 34.04241857075928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":800710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Alexis L","contributorId":225553,"corporation":false,"usgs":false,"family":"Wright","given":"Alexis","email":"","middleInitial":"L","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":800711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":221270,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800712,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220662,"text":"70220662 - 2020 - Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars","interactions":[],"lastModifiedDate":"2021-05-24T13:22:20.872996","indexId":"70220662","displayToPublicDate":"2020-06-29T08:20:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars","docAbstract":"

Mars has several different types of slope feature that resemble aqueous flows. However, the current cold, dry conditions are inimical to liquid water, resulting in uncertainty about its role in modern surface processes. Dark slope streaks were among the first distinctive young slope features to be identified on Mars and the first with activity seen in orbital images. They form markings on steep slopes that can persist for decades, and the role of water in their formation remains a matter of debate. Here I analyse the geomorphic features of new slope streaks using high-resolution orbital images. Comparison of images before and after streak formation reveal how this process affects the surface and provides information about the cause. These observations demonstrate that slope streaks erode and deposit material in some instances. They also reveal that streaks can jump slopes and may be erosive very near their termini. These observations support a formation model where dark slope streaks form as ground-hugging, low-density avalanches of dry surface dust. Such streaks need not be treated as Special Regions for planetary protection.

","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41561-020-0598-x","usgsCitation":"Dundas, C.M., 2020, Geomorphological evidence for a dry dust avalanche origin of slope streaks on Mars: Nature Geoscience, v. 13, p. 473-476, https://doi.org/10.1038/s41561-020-0598-x.","productDescription":"4 p.","startPage":"473","endPage":"476","ipdsId":"IP-110925","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":456222,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8243413","text":"External Repository"},{"id":385891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":816346,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70210865,"text":"70210865 - 2020 - Changes in capture rates and body size among vertebrate species occupying an insular urban habitat reserve","interactions":[],"lastModifiedDate":"2020-09-10T20:02:03.342722","indexId":"70210865","displayToPublicDate":"2020-06-29T07:48:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Changes in capture rates and body size among vertebrate species occupying an insular urban habitat reserve","docAbstract":"

Long‐term ecological monitoring provides valuable and objective scientific information to inform management and decision‐making. In this article, we analyze 22 years of herpetofauna monitoring data from the Point Loma Ecological Conservation Area (PLECA), an insular urban reserve near San Diego, CA. Our analysis showed that counts of individuals for one of the four most common terrestrial vertebrates declined, whereas counts for other common species increased or remained stable. Two species exhibited declines in adult body length, whereas biomass pooled over the five most common species increased over time and was associated with higher wet season precipitation. Although the habitat and vegetation at PLECA have remained protected and intact, we suspect that changes in arthropod communities may be driving changes in the abundance, growth, and development of insectivorous lizards. This study underscores the value of long‐term monitoring for establishing quantitative baselines to assess biological changes that would otherwise go undetected.

","language":"English","publisher":"Wiley","doi":"10.1111/csp2.245","usgsCitation":"Stanley, T., Clark, R.W., Fisher, R.N., Rochester, C.J., Root, S.A., Lombardo, K.J., and Ostermann-Kelm, S.D., 2020, Changes in capture rates and body size among vertebrate species occupying an insular urban habitat reserve: Conservation Science and Practice, v. 2, no. 9, e245, 15 p., https://doi.org/10.1111/csp2.245.","productDescription":"e245, 15 p.","ipdsId":"IP-098996","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":456224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.245","text":"Publisher Index Page"},{"id":376010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Point Loma Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.26806640625,\n 32.56996256044998\n ],\n [\n -117.05932617187499,\n 32.56996256044998\n ],\n [\n -117.05932617187499,\n 32.794201303793194\n ],\n [\n -117.26806640625,\n 32.794201303793194\n ],\n [\n -117.26806640625,\n 32.56996256044998\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanley, Thomas 0000-0002-8393-0005","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":210435,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":791815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Rulon W.","contributorId":139393,"corporation":false,"usgs":false,"family":"Clark","given":"Rulon","email":"","middleInitial":"W.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":791816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":791817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rochester, Carlton J. 0000-0002-0625-4496","orcid":"https://orcid.org/0000-0002-0625-4496","contributorId":207764,"corporation":false,"usgs":true,"family":"Rochester","given":"Carlton","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":791818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Root, Stephanie A 0000-0002-8405-8108","orcid":"https://orcid.org/0000-0002-8405-8108","contributorId":225607,"corporation":false,"usgs":false,"family":"Root","given":"Stephanie","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":791819,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lombardo, Keith J","contributorId":225608,"corporation":false,"usgs":false,"family":"Lombardo","given":"Keith","email":"","middleInitial":"J","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":791820,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ostermann-Kelm, Stacey D","contributorId":225609,"corporation":false,"usgs":false,"family":"Ostermann-Kelm","given":"Stacey","email":"","middleInitial":"D","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":791821,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70210868,"text":"70210868 - 2020 - A rasterized building footprint dataset for the United States","interactions":[],"lastModifiedDate":"2020-06-30T12:31:08.886688","indexId":"70210868","displayToPublicDate":"2020-06-29T07:16:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"A rasterized building footprint dataset for the United States","docAbstract":"

Microsoft released a U.S.-wide vector building dataset in 2018. Although the vector building layers provide relatively accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High-Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state, excluding Alaska and Hawaii: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30 m cell size covering the 48 conterminous states. We also identify errors in the original building dataset. We evaluate precision and recall in the data for three large U.S. urban areas. Precision is high and comparable to results reported by Microsoft while recall is high for buildings with footprints larger than 200 m2 but lower for progressively smaller buildings.

","language":"English","publisher":"Nature","doi":"10.1038/s41597-020-0542-3","usgsCitation":"Pourpeikari Heris, M., Foks, N.L., Bagstad, K.J., Troy, A., and Ancona, Z.H., 2020, A rasterized building footprint dataset for the United States: Scientific Data, v. 7, 207, 10 p., https://doi.org/10.1038/s41597-020-0542-3.","productDescription":"207, 10 p.","ipdsId":"IP-107614","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":456227,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-020-0542-3","text":"Publisher Index Page"},{"id":436907,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XZCPMT","text":"USGS data release","linkHelpText":"Rasterized Building Footprints"},{"id":376007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n 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bird","interactions":[],"lastModifiedDate":"2020-10-14T15:48:42.9961","indexId":"70215291","displayToPublicDate":"2020-06-28T10:41:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mate fidelity improves survival and breeding propensity of a long‐lived bird","docAbstract":"
  1. Evolutionary and behavioural ecologists have long been interested in factors shaping the variation in mating behaviour observed in nature. Although much of the research on this topic has focused on the consequences of mate choice and mate change on annual reproductive success, studies of a potential positive link between mate fidelity and adult demographic rates have been comparatively rare. This is particularly true for long‐lived birds with multi‐year, socially monogamous pair bonds.
  2. We used a 26‐year capture–mark–recapture dataset of 3,330 black brent Branta bernicla nigricans to test whether breeding with a familiar mate improved future breeding propensity and survival. We predicted that experienced breeders nesting with a new partner would have rates of survival similar to familiar pairs because long‐lived species avoid jeopardizing survival since their lifetime fitness is sensitive to this vital rate. In contrast, we expected that any costs of breeding with a new partner would be paid through skipping the subsequent breeding attempt.
  3. We found that unfamiliar pairs had lower subsequent breeding propensity than faithful partners. However, contrary to our expectations, individuals breeding with a new mate also suffered reduced survival.
  4. These results add to a small number of studies indicating that a positive relationship between mate retention and adult demographic rates may exist in a diverse array of avian species. Given these results, researchers should consider costs of mate change that extend beyond within‐season reproductive success to fully understand the potential adaptive basis for perennial social monogamy. We caution that if mate retention enhances survival prospects, improvements in annual reproductive success with pair‐bond length could be a secondary factor favouring perennial social monogamy, particularly in species with slower life‐history strategies. Furthermore, some cases where annual reproductive success does not improve with pair‐bond duration, yet multi‐year pair bonds are common, could be explained by benefits afforded by mate fidelity to adult vital rates.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.13286","usgsCitation":"Leach, A.G., Riecke, T., Sedinger, J.S., Ward, D.H., and Boyd, S., 2020, Mate fidelity improves survival and breeding propensity of a long‐lived bird: Journal of Animal Ecology, v. 89, no. 10, p. 2290-2299, https://doi.org/10.1111/1365-2656.13286.","productDescription":"10 p.","startPage":"2290","endPage":"2299","ipdsId":"IP-108202","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":456230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13286","text":"Publisher Index Page"},{"id":379370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Leach, Alan G.","contributorId":203591,"corporation":false,"usgs":false,"family":"Leach","given":"Alan","email":"","middleInitial":"G.","affiliations":[{"id":36666,"text":"Department of Natural Resources and Environmental Science, University of Nevada-Reno","active":true,"usgs":false}],"preferred":false,"id":801619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riecke, Thomas V.","contributorId":171482,"corporation":false,"usgs":false,"family":"Riecke","given":"Thomas V.","affiliations":[],"preferred":false,"id":801620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sedinger, James S.","contributorId":84861,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":801621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":801622,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Sean","contributorId":76672,"corporation":false,"usgs":false,"family":"Boyd","given":"Sean","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":801623,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211185,"text":"70211185 - 2020 - Energy development and production in the Great Plains: Implications and restoration opportunities","interactions":[],"lastModifiedDate":"2021-10-04T16:45:27.336205","indexId":"70211185","displayToPublicDate":"2020-06-28T10:10:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Energy development and production in the Great Plains: Implications and restoration opportunities","docAbstract":"

Energy is an integral part of society. The major US energy sources of fossil fuels (coal, oil, natural gas); biofuels (ethanol); and wind are concentrated in grassland ecosystems of the Great Plains. As energy demand continues to increase, mounting pressures will be placed on North American grassland systems. In this review, we present the ecological effects of energy development and production on grassland systems. We then identify opportunities to mitigate these effects during the planning, construction, and production phases by using informed methodology and improved technology. Primary effects during energy development include small- and large-scale soil disturbance and vegetation removal as small patches of grasslands are used to host oil or gas wells, wind turbine pads, associated roadways, and pipelines or through the conversion of large grassland areas to biofuel croplands. Direct habitat loss or habitat fragmentation can affect wildlife directly through increased mortality or indirectly through reduction in habitat quantity and quality. During energy production, air and water quality can be affected through regular emissions or unplanned spills. Energy development can also affect the economy and health of local communities. During planning, energy development and production effects can be reduced by carefully considering effects on grasslands during siting and even by selecting different energy source types. During construction, effects on soil and plant systems can be minimized by eliminating weed populations before disturbance, salvaging and stockpiling topsoil for future revegetation, and harvesting native local seed for postsite restoration. During energy production operations, noise and road traffic reduction plans and atmospheric monitoring will enable more informed mitigation measures. Continued research on energy development effects and mitigation measures is necessary to establish best management practices beneficial to grassland health while providing needed energy for the United States.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2020.05.003","usgsCitation":"Ott, J.P., Hanberry, B.B., Khalil, M., Paschke, M.W., Post van der Burg, M., and Prenni, A.J., 2020, Energy development and production in the Great Plains: Implications and restoration opportunities: Rangeland Ecology and Management, v. 78, p. 257-272, https://doi.org/10.1016/j.rama.2020.05.003.","productDescription":"16 p.","startPage":"257","endPage":"272","ipdsId":"IP-109053","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":456232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2020.05.003","text":"Publisher Index Page"},{"id":376427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Illinois, Indiana, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Wisconsin, Wyoming","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.00976562499999,\n 49.15296965617042\n ],\n [\n -113.73046875,\n 48.86471476180277\n ],\n [\n -106.787109375,\n 40.64730356252251\n ],\n [\n -105.205078125,\n 34.016241889667015\n ],\n [\n -102.74414062499999,\n 30.675715404167743\n ],\n [\n -97.294921875,\n 30.372875188118016\n ],\n [\n -94.658203125,\n 36.73888412439431\n ],\n [\n -86.66015624999999,\n 39.639537564366684\n ],\n [\n -87.978515625,\n 42.09822241118974\n ],\n [\n -93.1640625,\n 44.276671273775186\n ],\n [\n -95.00976562499999,\n 49.15296965617042\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ott, Jacqueline P.","contributorId":229363,"corporation":false,"usgs":false,"family":"Ott","given":"Jacqueline","email":"","middleInitial":"P.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":793006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanberry, Brice B. 0000-0001-8657-9540","orcid":"https://orcid.org/0000-0001-8657-9540","contributorId":229364,"corporation":false,"usgs":false,"family":"Hanberry","given":"Brice","email":"","middleInitial":"B.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":793007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khalil, Mona 0000-0002-6046-1293","orcid":"https://orcid.org/0000-0002-6046-1293","contributorId":207187,"corporation":false,"usgs":true,"family":"Khalil","given":"Mona","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":793008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paschke, Mark W. 0000-0002-6345-5905","orcid":"https://orcid.org/0000-0002-6345-5905","contributorId":229365,"corporation":false,"usgs":false,"family":"Paschke","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":793009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":793010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prenni, Anthony J. 0000-0002-0256-5166","orcid":"https://orcid.org/0000-0002-0256-5166","contributorId":229366,"corporation":false,"usgs":false,"family":"Prenni","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793011,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210866,"text":"70210866 - 2020 - Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA","interactions":[],"lastModifiedDate":"2020-06-30T12:38:45.776529","indexId":"70210866","displayToPublicDate":"2020-06-28T07:32:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA","docAbstract":"

Tools to evaluate reservoir thermal energy storage (RTES; heat storage in slow-moving or stagnant geochemically evolved permeable zones in strata that underlie well-connected regional aquifers) are developed and applied to the Columbia River Basalt Group (CRBG) beneath the Portland Basin, Oregon, USA. The performance of RTES for heat storage and recovery in the Portland Basin is strongly dependent on the operational schedule of heat injection and extraction. We examined the effects of the operational schedule, based on an annual solar hot water supply pattern and a building heating demand model, using heat and fluid flow simulations with SUTRA. We show RTES to be feasible for supply of heating energy for a large combined research/teaching building on the Oregon Health and Science University South Waterfront expansion, an area of planned future development. Initially, heat is consumed to increase the reservoir temperature, and conductive heat loss is high due to high temperature gradients between the reservoir and surrounding rock. Conductive heat loss continues into the future, but the rate of heat loss decreases, and heat recovery efficiency of the RTES system increases over time. Simulations demonstrate the effects of varying heat-delivery rate and temperature on the heat production history of the reservoir. If 100% of building heating needs are to be supplied by combined solar/RTES, then the solar system must be sized to meet building needs plus long-term thermal losses (i.e., conductive losses once the system is heated to pseudo-steady state) from the RTES system. If the solar heating system barely meets these criteria, then during early years, less than 100% of the building demand will be supplied until the reservoir is fully-heated. The duration of supplying less than 100% of building demand can be greatly shortened by pre-heating the reservoir before building heating operations or by adding extra heat from external sources during early years. Analytic solutions are developed to evaluate efficacy and to help design RTES systems (e.g., well-spacing, thermal source sizing, etc.). A map of thermal energy storage capacity is produced for the CRBG beneath the Portland Basin. The simulated building has an annual heat load of ∼1.9 GWh, and the total annual storage capacity of the Portland Basin is estimated to be 43,400 GWh assuming seasonal storage of heat yields water from which 10 °C can be extracted via heat exchange, indicating a tremendous heating capacity of the CRBG.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2020.101877","usgsCitation":"Burns, E.R., Bershaw, J., Williams, C.F., Wells, R.E., Uddenberg, M.W., Scanlon, D.P., Cladouhos, T.T., and Van Houten, B., 2020, Using saline or brackish aquifers as reservoirs for thermal energy storage, with example calculations for direct-use heating in the Portland Basin, Oregon, USA: Geothermics, v. 88, 101877, 17 p., https://doi.org/10.1016/j.geothermics.2020.101877.","productDescription":"101877, 17 p.","ipdsId":"IP-114387","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":456234,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2020.101877","text":"Publisher Index Page"},{"id":436908,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A6D6XM","text":"USGS data release","linkHelpText":"SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon, USA"},{"id":376008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Portland basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.057861328125,\n 45.1433047394883\n ],\n [\n -122.1844482421875,\n 45.1433047394883\n ],\n [\n -122.1844482421875,\n 46.00840867976967\n ],\n [\n -123.057861328125,\n 46.00840867976967\n ],\n [\n -123.057861328125,\n 45.1433047394883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Van Houten, Boz","contributorId":222629,"corporation":false,"usgs":false,"family":"Van Houten","given":"Boz","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":791829,"contributorType":{"id":2,"text":"Editors"},"rank":8}],"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bershaw, John 0000-0003-4555-5766","orcid":"https://orcid.org/0000-0003-4555-5766","contributorId":222626,"corporation":false,"usgs":false,"family":"Bershaw","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":791823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":791824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wells, Ray E","contributorId":222637,"corporation":false,"usgs":false,"family":"Wells","given":"Ray","email":"","middleInitial":"E","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":791825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Uddenberg, Matt W","contributorId":222636,"corporation":false,"usgs":false,"family":"Uddenberg","given":"Matt","email":"","middleInitial":"W","affiliations":[{"id":40573,"text":"Stravan Consulting","active":true,"usgs":false}],"preferred":false,"id":791826,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scanlon, Darby P","contributorId":222634,"corporation":false,"usgs":false,"family":"Scanlon","given":"Darby","email":"","middleInitial":"P","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":791827,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cladouhos, Trenton T 0000-0002-1127-8118","orcid":"https://orcid.org/0000-0002-1127-8118","contributorId":222627,"corporation":false,"usgs":false,"family":"Cladouhos","given":"Trenton","email":"","middleInitial":"T","affiliations":[{"id":40571,"text":"CyrqEnergy","active":true,"usgs":false}],"preferred":false,"id":791828,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Houten, Boz","contributorId":222629,"corporation":false,"usgs":false,"family":"Van Houten","given":"Boz","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":791884,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210888,"text":"70210888 - 2020 - Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting","interactions":[],"lastModifiedDate":"2020-08-26T19:17:12.307798","indexId":"70210888","displayToPublicDate":"2020-06-27T10:27:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting","docAbstract":"Operational ecological forecasting is an emerging field that leverages ecological models in a new, cross-disciplinary way – using a real-time or nearly real-time climate forecast to project near-term ecosystem states. These applications give decision-makers lead time to anticipate and manage state changes that degrade ecosystem functions or directly impact humans. The Everglades Forecasting model (EverForecast) is an operational forecast model designed specifically for conservation management purposes including water management. It provides up to six-month forecasts of daily projected, spatially continuous stage values across the Everglades. We validated EverForecast quarterly to measured historical values at 207 gages (1 Jan 2000 – 31 Dec 2019). EverForecast hindcasted water stage accurately captured measured stage variation, with a low percentage of measured stage exceeding hindcasted values. Over the whole spatial extent, the mean RMSE is 20.98 cm, the mean MAE is 14.42 cm, and the mean MBE is 0.91 cm.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104783","usgsCitation":"Pearlstine, L.G., Beerens, J., Reynolds, G., Haider, S., McKelvy, M., Suir, K., Romanach, S., and Nestler, J.H., 2020, Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting: Environmental Modelling and Software, v. 132, 104783, 13 p., https://doi.org/10.1016/j.envsoft.2020.104783.","productDescription":"104783, 13 p.","ipdsId":"IP-115300","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456237,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2020.104783","text":"Publisher Index Page"},{"id":436909,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UARKTV","text":"USGS data release","linkHelpText":"EverForecast hydrologic output for April 2020: a six-month water stage forecast for the Greater Everglades"},{"id":376058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.97174072265625,\n 25.090573819461\n ],\n [\n -80.15899658203125,\n 25.090573819461\n ],\n [\n -80.15899658203125,\n 26.775039386999605\n ],\n [\n -81.97174072265625,\n 26.775039386999605\n ],\n [\n -81.97174072265625,\n 25.090573819461\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":791947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beerens, James M. 0000-0001-8143-916X","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":25440,"corporation":false,"usgs":false,"family":"Beerens","given":"James M.","affiliations":[],"preferred":false,"id":791948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Gregg","contributorId":225642,"corporation":false,"usgs":false,"family":"Reynolds","given":"Gregg","email":"","affiliations":[{"id":13415,"text":"Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":791949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haider, Saira 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":216195,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":791950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKelvy, Mark 0000-0001-5465-2571 mckelvym@usgs.gov","orcid":"https://orcid.org/0000-0001-5465-2571","contributorId":4865,"corporation":false,"usgs":true,"family":"McKelvy","given":"Mark","email":"mckelvym@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":791951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suir, Kevin 0000-0003-1570-9648","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":218812,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":791952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":791953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nestler, Jennifer H. 0000-0003-4552-1734","orcid":"https://orcid.org/0000-0003-4552-1734","contributorId":225643,"corporation":false,"usgs":false,"family":"Nestler","given":"Jennifer","email":"","middleInitial":"H.","affiliations":[{"id":41177,"text":"Cherokee Federal, contracted to Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":791954,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70211505,"text":"70211505 - 2020 - Behavioural responses of female lake trout Salvelinus namaycush to male chemical stimuli and prostaglandin F2α","interactions":[],"lastModifiedDate":"2020-10-28T15:37:32.690273","indexId":"70211505","displayToPublicDate":"2020-06-27T09:43:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Behavioural responses of female lake trout Salvelinus namaycush to male chemical stimuli and prostaglandin F2α","title":"Behavioural responses of female lake trout Salvelinus namaycush to male chemical stimuli and prostaglandin F2α","docAbstract":"Male olfactory cues may guide aggregation on spawning reefs, mate evaluation, and synchronized gamete release in lake trout Salvelinus namaycush, but a lack of information on the source and identity of the cues precludes direct tests of their function. Using a two-channel flume assay, we found female lake trout increased time spent in the channel treated with male-conditioned water, urine, and bile but not synthesized prostaglandin F2α. We suggest future efforts to characterize male olfactory cues focus on urine and postulate that bile acids contribute to its behavioural activity.","language":"English","publisher":"Wiley","doi":"10.1111/jfb.14446","usgsCitation":"Buchinger, T.J., Li, W., and Johnson, N., 2020, Behavioural responses of female lake trout Salvelinus namaycush to male chemical stimuli and prostaglandin F2α: Journal of Fish Biology, v. 97, no. 4, p. 1224-1227, https://doi.org/10.1111/jfb.14446.","productDescription":"4 p.","startPage":"1224","endPage":"1227","ipdsId":"IP-119435","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":376840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Buchinger, Tyler John","contributorId":192316,"corporation":false,"usgs":false,"family":"Buchinger","given":"Tyler","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":794383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":794384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794385,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211596,"text":"70211596 - 2020 - Quantitative paleoflood hydrology","interactions":[],"lastModifiedDate":"2021-02-03T23:11:52.214282","indexId":"70211596","displayToPublicDate":"2020-06-27T08:12:07","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Quantitative paleoflood hydrology","docAbstract":"This chapter reviews the paleohydrologic techniques and approaches used to reconstruct the magnitude and frequency of past floods using geological evidence. Quantitative paleoflood hydrology typically leads to two phases of analysis: (1) documentation and assessment of flood physical evidence (paleostage indicators), and (2) relating identified flood evidence to flood discharge, based on hydraulic calculations. Most paleoflood studies rely on stratigraphic sequences of fine-grained flood deposits found in slack-water and eddy environments in bedrock rivers to enable the estimates of paleodischarges for floods of past few centuries or millennia. Geochronology, commonly based on techniques such as optically stimulated luminescence (OSL) and radiocarbon, enable paleoflood age estimates. Such paleoflood discharge and age information can vastly improve flood frequency estimates, particularly for large and rare floods for which quantile estimates are typically poorly constrained by short historical records. The inclusion of such physical evidence of flooding into flood frequency assessments has been aided by new techniques of frequency analysis that can efficiently employ such data. Consequently, paleoflood analysis is supporting probability risk management of critical infrastructure such as nuclear facilities, dams, or bridges. Paleoflood studies also support understanding of the recurrence of geomorphically effective flows and assessment of non-stationarity in the frequency of large floods due to climate, land-use, or other environmental changes.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12495-9","usgsCitation":"Benito, G., and O'Connor, J., 2020, Quantitative paleoflood hydrology, chap. of Reference module in earth systems and environmental sciences, p. 459-474, https://doi.org/10.1016/B978-0-12-409548-9.12495-9.","productDescription":"16 p.","startPage":"459","endPage":"474","ipdsId":"IP-116576","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":377006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Spain","otherGeospatial":"Llobregat River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 2.146453857421875,\n 41.307729208348015\n ],\n [\n 2.077789306640625,\n 41.51783221717116\n ],\n [\n 2.0269775390625,\n 41.64828831259533\n ],\n [\n 1.9418334960937498,\n 41.80305444575587\n ],\n [\n 1.90887451171875,\n 41.94519164538106\n ],\n [\n 1.833343505859375,\n 41.94825586972943\n ],\n [\n 1.8429565429687498,\n 41.77336007442076\n ],\n [\n 1.803131103515625,\n 41.63084096540012\n ],\n [\n 1.882781982421875,\n 41.529141988723104\n ],\n [\n 1.943206787109375,\n 41.38711263243966\n ],\n [\n 2.06817626953125,\n 41.307729208348015\n ],\n [\n 2.1148681640624996,\n 41.28606238749825\n ],\n [\n 2.146453857421875,\n 41.307729208348015\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benito, Gerardo","contributorId":236942,"corporation":false,"usgs":false,"family":"Benito","given":"Gerardo","email":"","affiliations":[{"id":47572,"text":"Spanish National Research Council (CSIC), National Museum of Natural Sciences","active":true,"usgs":false}],"preferred":false,"id":794756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":794758,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70213245,"text":"70213245 - 2020 - Design and operations of the Hydrate 01 Stratigraphic test well, Alaska North Slope","interactions":[],"lastModifiedDate":"2020-09-16T00:59:13.821094","indexId":"70213245","displayToPublicDate":"2020-06-26T19:18:15","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Design and operations of the Hydrate 01 Stratigraphic test well, Alaska North Slope","docAbstract":"

The National Energy Technology Laboratory, the Japan Oil, Gas and Metals National Corporation, and the U.S. Geological Survey are leading an effort to conduct an extended gas hydrate production test in northern Alaska. The proposed production test required the drilling of an initial stratigraphic test well (STW) to confirm the geologic conditions of the proposed test site. This well was completed in December 2018 in cooperation with the Prudhoe Bay Unit Interest Owners. With the success of the STW, the project leadership group is developing plans to drill a geologic data well and a production test well. Drilling plans for the STW were advanced in late 2018. The Prudhoe Bay Unit Hydrate-01 well was spudded on 10-December-2018. Downhole data acquisition was completed on 25-December-2018 and the rig was released on 01-January-2019. The STW was drilled in two sections. The surface hole was drilled to a depth of 2248 ft (MD, measured depth) and cased, and the “production hole section” was drilled to a depth of 3558 ft (MD) and also cased. A thermally chilled mineral-oilbased mud was used to maintain drillhole stability and quality of the borehole acquired data. The primary borehole data were acquired using a suite of Schlumberger logging-while-drilling tools. To gather grain size and other data needed to inform the design of the production test well, sidewall pressure cores were collected using Halliburton’s CoreVault tool. In addition to confirming the geologic conditions at the test site, the Hydrate-01 well was designed to serve as a monitoring well during future field operations. Therefore, two sets of fiber optic cables, each including bundled Distributed Acoustic Sensors (DAS) and Distributed Temperature Sensors (DTS), were clamped to the outside of the well casing and cemented in place. In March 2019, the project team worked with SAExploration to acquire 3D DAS Vertical Seismic Profiling (VSP) data in the Hydrate-01 well, which was the largest 3D DAS-VSP ever conducted. Additionally, since the December 2018 completion of the STW, several borehole temperature surveys have been acquired with the DTS deployed in the Hydrate-01 well.

","conferenceTitle":"10th International Conference on Gas Hydrates (ICGH10)","conferenceDate":"June 21-26, 2020","conferenceLocation":"Singapore","language":"English","publisher":"National Energy Technology Laboratory","usgsCitation":"Collett, T.S., Zyrianova, M.V., Okinaka, N., Wakatsuki, M., Boswell, R., Marsteller, S., Minge, D., Crumley, S., Itter, D., and Hunter, R.D., 2020, Design and operations of the Hydrate 01 Stratigraphic test well, Alaska North Slope, 10th International Conference on Gas Hydrates (ICGH10), Singapore, June 21-26, 2020, 8 p.","productDescription":"8 p.","ipdsId":"IP-115172","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":378430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378429,"rank":1,"type":{"id":15,"text":"Index 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In 2016, the U.S. Geological Survey published an assessment of technically recoverable continuous oil and gas resources of the Wolfcamp shale in the Midland Basin, Permian Basin Province, Texas. Estimated ultimate recoveries (EURs) were calculated with production data from IHS MarkitTM using DeclinePlus software in the Harmony interface. These EURs were a major component of the quantitative resource assessment. For five of the six assessment units in the study, an industry operator in the Midland Basin provided information that was used to differentiate the Wolfcamp horizontal well landing zones. The IHS MarkitTM production database does not distinguish between the Wolfcamp A, B, C, and D well landing zones. These different units of the Wolfcamp have different production patterns that are important for calculation of EURs. The calculated mean EURs for each assessment unit ranged from 99,000 barrels of oil in the Wolfcamp C to 142,000 barrels of oil in the Wolfcamp A.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205042","usgsCitation":"Leathers-Miller, H.M., 2020, Procedure for calculating estimated ultimate recoveries of wells in the Wolfcamp shale of the Midland Basin, Permian Basin Province, Texas: U.S. Geological Survey Scientific Investigations Report 2020–5042, 5 p., https://doi.org/10.3133/sir20205042.","productDescription":"iii, 5 p.","onlineOnly":"Y","ipdsId":"IP-091005","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375829,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5042/coverthb.jpg"},{"id":375830,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5042/sir20205042.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5042"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.974609375,\n 30.031055426540206\n ],\n [\n -98.1298828125,\n 30.031055426540206\n ],\n [\n -98.0859375,\n 33.61461929233378\n ],\n [\n -101.05224609374999,\n 33.63291573870479\n ],\n [\n -103.9306640625,\n 33.687781758439364\n ],\n [\n -103.974609375,\n 30.031055426540206\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2020-06-26","noUsgsAuthors":false,"publicationDate":"2020-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Leathers-Miller, Heidi M. 0000-0001-5208-9906 hleathers@usgs.gov","orcid":"https://orcid.org/0000-0001-5208-9906","contributorId":150419,"corporation":false,"usgs":true,"family":"Leathers-Miller","given":"Heidi","email":"hleathers@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791338,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211907,"text":"70211907 - 2020 - Western bumble bee: Declines in United States and range-wide information gaps","interactions":[],"lastModifiedDate":"2020-08-11T18:53:01.069132","indexId":"70211907","displayToPublicDate":"2020-06-26T13:42:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Western bumble bee: Declines in United States and range-wide information gaps","docAbstract":"

In recent decades, many bumble bee species have declined due to changes in habitat, climate, and pressures from pathogens, pesticides, and introduced species. The western bumble bee (Bombus occidentalis ), once common throughout western North America, is a species of concern and will be considered for listing by the U.S. Fish and Wildlife Service (USFWS) under the Endangered Species Act (ESA). We attempt to improve alignment of data collection and research with USFWS needs to consider redundancy, resiliency, and representation in the upcoming species status assessment. We reviewed existing data and literature on B. occidentalis , highlighting information gaps and priority topics for research. Priorities include increased knowledge of trends, basic information on several life‐history stages, and improved understanding of the relative and interacting effects of stressors on population trends, especially the effects of pathogens, pesticides, climate change, and habitat loss. An understanding of how and where geographic range extent has changed for the two subspecies of B. occidentalis is also needed. We outline data that could be easily collected in other research projects that would increase their utility for understanding range‐wide trends of bumble bees. We modeled the overall trend in occupancy from 1998 to 2018 of Bombus occidentalis within the continental United States using existing data. The probability of local occupancy declined by 93% over 21 yr from 0.81 (95% CRI = 0.43, 0.98) in 1998 to 0.06 (95% CRI = 0.02, 0.16) in 2018. The decline in occupancy varied spatially by landcover and other environmental factors. Detection rates vary in both space and time, but peak detection across the continental United States occurs in mid‐July. We found considerable spatial gaps in recent sampling, with limited sampling in many regions, including most of Alaska, northwestern Canada, and the southwestern United States. We therefore propose a sampling design to address these gaps to best inform the ESA species status assessment through improved assessment of how the spatial distribution of stressors influences occupancy changes. Finally, we request involvement via data sharing, participation in occupancy sampling with repeated visits to distributed survey sites, and complementary research to address priorities outlined in this paper.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3141","usgsCitation":"Graves, T., Janousek, W.M., Gaulke, S., Nicholas, A., Keinath, D., Bell, C.M., Cannings, S., Hatfield, R.G., Heron, J.M., Koch, J.B., Loffland, H.L., Richardson, L., Rohde, A., Rykken, J., Strange, J.P., Tronstead, L., and Sheffield, C., 2020, Western bumble bee: Declines in United States and range-wide information gaps: Ecosphere, v. 11, no. 6, e03141, 13 p., https://doi.org/10.1002/ecs2.3141.","productDescription":"e03141, 13 p.","ipdsId":"IP-113225","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":456241,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3141","text":"Publisher Index Page"},{"id":436910,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QY8ZA0","text":"USGS data release","linkHelpText":"Western bumble bee 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States?","interactions":[],"lastModifiedDate":"2020-07-06T17:25:49.548009","indexId":"70210928","displayToPublicDate":"2020-06-26T12:13:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Wind, sun, and wildlife: Do wind and solar energy development “short-circuit” conservation in the western United States?","docAbstract":"

Despite the trade-offs between renewable energy development, land use, humans, and wildlife, wind and solar development continues to transform the southwestern US into a green energy landscape. While renewable energy reduces carbon emissions and reliance on fossil fuels, many studies have emerged on the associated ecological and social impacts of this technology. Here, we review the current state of knowledge on the nexus between wildlife conservation and energy development in the western US since 2010. We revisit pertinent ecological concepts and questions presented in earlier reviews to assess how far the field has progressed in mitigating negative effects. Specifically, we ask, what density or design of development maximizes energy benefits while minimizing negative effects on wildlife, whether the results of previously-deficient before-after control-impact studies are now more readily-available, and ultimately, can the impacts of renewable energy development on wildlife be mitigated? We also provide a case study on the federally-protected Desert Tortoise, a conservation-reliant species in the Desert Southwest US, to highlight efforts to mitigate the negative effects of renewable energy development. Our review concludes that successful mitigation is possible via use of spatial decision support tools, applying novel wildlife deterrence and detection systems developed for existing installed facilities, and incorporating impact studies that provide managers with conservation metrics for evaluating different future development land-use scenarios.

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The second U.S. Department of the Interior (DOI) Economics Training Workshop (hereafter “Workshop”) was held during September 25–27, 2018, in Washington, D.C., to identify, highlight, and better understand needs and opportunities for economic analysis to support DOI’s mission. Building on the first workshop in 2017, the second Workshop, jointly convened by the DOI Office of Policy Analysis and the U.S. Geological Survey (USGS) Science and Decisions Center, provided an opportunity for DOI economists to share expertise and experiences and to build collaboration and communication channels across DOI. In addition, the second Workshop provided training sessions on a variety of relevant economic and modeling topics. More than 40 DOI economists gathered at the Workshop to share their work, discuss shared challenges, and identify approaches to advance the use and contribution of economics at the DOI.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201044","collaboration":"Prepared in cooperation with the U.S. Department of the Interior Office of Policy Analysis","usgsCitation":"Alhassan, M., Pindilli, E.J., Crowley, C.S.L., Shapiro, C.D., and Simon, B.M., 2020, Supporting natural resource-management decisions—The role of economics at the U.S. Department of the Interior (DOI)—2018 DOI Economics Training Workshop: U.S. Geological Survey Open-File Report 2020–1044, 26 p., https://doi.org/10.3133/ofr20201044.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112653","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":375485,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181054","text":"Open-File Report 2018-1054","linkHelpText":"- Supporting natural resource management—The role of economics at the Department of the Interior—A workshop report"},{"id":375947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1044/ofr20201044.pdf","text":"Report","size":"6.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":375483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1044/coverthb.jpg"}],"contact":"

Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-06-16","noUsgsAuthors":false,"publicationDate":"2020-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Alhassan, Mustapha 0000-0001-6201-0077","orcid":"https://orcid.org/0000-0001-6201-0077","contributorId":212088,"corporation":false,"usgs":true,"family":"Alhassan","given":"Mustapha","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":790643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":790644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crowley, Christian S.L.","contributorId":203551,"corporation":false,"usgs":false,"family":"Crowley","given":"Christian","email":"","middleInitial":"S.L.","affiliations":[{"id":36651,"text":"Department of the Interior Office of Policy Analysis","active":true,"usgs":false}],"preferred":false,"id":790645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":790646,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simon, Benjamin","contributorId":203554,"corporation":false,"usgs":false,"family":"Simon","given":"Benjamin","email":"","affiliations":[{"id":36651,"text":"Department of the Interior Office of Policy Analysis","active":true,"usgs":false}],"preferred":false,"id":790647,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}