Large river deltas are complex ecosystems that are believed to play a pivotal role in promoting the early marine growth and survival of threatened Chinook Salmon Oncorhynchus tshawytscha. We used a fish bioenergetics model to assess the functional role of multiple delta habitats across a gradient of salinities and vegetation types, where consumption and growth rate potential (GRP) were considered as proxies for habitat quality. We subsequently compared our model output to empirical, or realized, growth estimates from scale circuli. In terms of consumption, prey energy density (EDprey) was 46–86% higher in tidal freshwater forest than in any other habitat type, while estimated consumption rates (expressed as proportion of maximum daily consumption; Pcmax) were positively correlated with FL. These size‐related differences in Pcmax led to a noticeable increase along a freshwater‐to‐saline gradient from roughly 0.25 in tidal freshwater forest to 0.55 in the offshore subtidal zone, yet despite higher observed Pcmax values in nearshore and offshore habitats, the tidal freshwater forest and emergent salt marsh demonstrated the highest modeled GRP values. Similarly, realized growth rates for fish caught in tidal freshwater forest were up to 0.5% higher per day than for fish caught in the offshore area, but habitat‐level differences were overshadowed by allometry and rearing origin. Scales from unmarked fish (assumed to be of wild origin) indicated that they grew, on average, 11% faster than did hatchery fish; however, these differences were subtle and were more obvious at fork lengths <100 mm. Our results suggest that tidal forests and emergent marshes may offer early life growth advantages for wild Chinook Salmon, but that wild and hatchery fish can compensate as they move seaward by opportunistically consuming greater quantities of low‐energy density prey, taking advantage of pulses of larval forage fish, or by spending time in multiple interconnected habitat types.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10134","usgsCitation":"Davis, M.J., Woo, I., Ellings, C.S., Hodgson, S., Beauchamp, D.A., Nakai, G., and De La Cruz, S.E., 2019, Freshwater tidal forests and estuarine wetlands may confer early life growth advantages for delta-reared Chinook Salmon: Transactions of the American Fisheries Society, v. 148, no. 2, p. 289-307, https://doi.org/10.1002/tafs.10134.","productDescription":"19 p.","startPage":"289","endPage":"307","ipdsId":"IP-103088","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":756755,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgson, Sayre","contributorId":172121,"corporation":false,"usgs":false,"family":"Hodgson","given":"Sayre","email":"","affiliations":[{"id":26985,"text":"Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":756756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":756757,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":756758,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":756752,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201141,"text":"sir20185164 - 2019 - Assessment of bird exposure to lead at Tyndall and Beale Air Force Bases, 2016–17","interactions":[],"lastModifiedDate":"2019-02-06T10:31:52","indexId":"sir20185164","displayToPublicDate":"2019-02-05T14:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5164","displayTitle":"Assessment of Bird Exposure to Lead at Tyndall and Beale Air Force Bases, 2016–17","title":"Assessment of bird exposure to lead at Tyndall and Beale Air Force Bases, 2016–17","docAbstract":"Soil contamination by lead (Pb) from past small munitions training on Beale Air Force Base, California, and Tyndall Air Force Base, Florida, may result in adverse effects for passerine birds that utilize the locations. A study was conducted during 2016-17 by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and U.S. Air Force, at both Air Force Bases (AFBs) to assess the risk of bird exposure to Pb. Two different methods were used to estimate exposure. The first was analysis of blood and feather samples collected from birds captured on both AFBs, and the second was food chain modeling using data on Pb concentrations in dietary items (invertebrates and seeds) collected from both AFBs. Lead concentrations in blood and feathers for birds captured at Beale AFB indicate low exposure and risk; potential toxicity is possible based on blood and feather data for birds from Tyndall AFB. Food chain modeling utilizing dietary contamination indicates a risk likelihood of up to 35 percent at Beale AFB and up to 34 percent at Tyndall AFB. Lead exposure from incidental soil ingestion increased risk likelihood at both AFBs and is a significant uncertainty in this risk assessment. A companion data release for data collected during this project can be found at https://doi.org/10.5066/P92YXMQ2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185164","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, U.S. Air Force","usgsCitation":"Bargar, T.A., 2019, Assessment of bird exposure to lead at Tyndall and Beale Air Force Bases, 2016–17: U.S. Geological Survey Scientific Investigations Report 2018–5164, 30 p., https://doi.org/10.3133/sir20185164.","productDescription":"Report: viii, 30 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101102","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437582,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YXMQ2","text":"USGS data release","linkHelpText":"Assessment of bird exposure to lead at Tyndall and Beale Air Force Bases"},{"id":361009,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/P92YXMQ2","text":"USGS data release","description":"USGS data release","linkHelpText":"Assessment of bird exposure to lead at Tyndall and Beale Air Force Bases"},{"id":360558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5164/coverthb2.jpg"},{"id":360559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5164/sir20185164.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5164"}],"country":"United States","state":"California, Florida","otherGeospatial":"Beale Air Force Base, St. Joe Bay Buffer Preserve, Tyndall Air Force Base","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
U.S. Geological Survey science supports groundwater resource management in the Mississippi Alluvial Plain region. The USGS Science and Decisions Center is working with the Water Availability and Use Science Program to integrate economics into a sophisticated model of groundwater in the region. The model will quantify the status of the groundwater system and help researchers, stakeholders, and decision-makers understand and manage groundwater resources. Including economics in the model will let users consider the influence of groundwater levels on regional economics and the effects of economic factors on the demand for groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193003","usgsCitation":"Alhassan, M., Lawrence, C., Richardson, S., and Pindilli, E., 2019, The Mississippi Alluvial Plain aquifers—An engine for economic activity: U.S. Geological Survey Fact Sheet 2019–3003, 4 p., https://doi.org/10.3133/fs20193003.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101445","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":361020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3003/coverthb.jpg"},{"id":361021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3003/fs20193003.pdf","text":"Report","size":"12.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3003"},{"id":361022,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RW8Y2A","text":"USGS data release","description":"USGS data release","linkHelpText":"The Mississippi Alluvial Plain Aquifers: An Engine for Economic Activity - Data"}],"country":"United States","otherGeospatial":"Mississippi Alluvial Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93,\n 29\n ],\n [\n -88.5,\n 29\n ],\n [\n -88.5,\n 38\n ],\n [\n -93,\n 38\n ],\n [\n -93,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Science and Decisions Center
U.S. Geological Survey
913 National Center
Reston, VA 20192
Email: gs_emeh_sdc@usgs.gov
During late summer and fall, elk (Cervus canadensis) need access to adequate nutrition to support physiological requirements for reproduction and overwinter survival. The archery hunting season often occurs during this period and can affect distributions of elk as they seek areas that minimize perceived harvest risk. Areas that confer lower harvest risk may provide relatively low‐value nutrition, resulting in a potential tradeoff between minimizing risk and accessing adequate forage. We used radio‐collar data collected from female elk during late summer and fall (Aug–Oct) and estimated resource selection models to evaluate the extent of this potential risk‐nutrition tradeoff. To evaluate if elk exposed to a greater hunting risk altered selection for forage resources, we assessed the relationship between individuals’ selection coefficients for forage and the proportion of their late‐summer‐fall home range accessible to hunters (our metric of hunting risk). Our results indicate that during the archery season, elk with higher‐risk home ranges selected more strongly for areas farther from motorized routes than elk with lower‐risk home ranges. Regardless of the level of risk, however, elk maintained or increased selection for areas with higher forage quality, suggesting that elk did not compromise access to nutritional resources during the archery season. Elk with higher‐risk home ranges were also exposed to the poorest nutrition and increased their selection for areas with higher forage quality more strongly than elk with lower‐risk home ranges during the hunting season. Elk with lower‐risk home ranges had access to the highest nutrition, which may be due to the availability of concentrated sources of high‐quality forage from irrigated agricultural areas on private lands that restricted hunter access. Resource agencies interested in encouraging elk to remain on public lands during the hunting seasons might consider closing motorized travel during the archery season to increase security on public lands, limiting hunter pressure on public lands, improving forage quality on public lands, and working with private land owners to enhance hunter accessibility and restrict elk access to high‐quality forage resources.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21638","usgsCitation":"DeVoe, J., Proffitt, K., Mitchell, M.S., Jourdonnais, C., and Barker, K.J., 2019, Elk forage and risk tradeoffs during the fall archery season: Journal of Wildlife Management, v. 83, no. 4, p. 801-816, https://doi.org/10.1002/jwmg.21638.","productDescription":"16 p.","startPage":"801","endPage":"816","ipdsId":"IP-092979","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Bitterroot River valley, Sapphire Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.488525390625,\n 46.01985337287631\n ],\n [\n -113.54644775390625,\n 46.01985337287631\n ],\n [\n -113.54644775390625,\n 46.92963428624288\n ],\n [\n -114.488525390625,\n 46.92963428624288\n ],\n [\n -114.488525390625,\n 46.01985337287631\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"DeVoe, Jesse","contributorId":243380,"corporation":false,"usgs":false,"family":"DeVoe","given":"Jesse","email":"","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":802168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proffitt, Kelly 0000-0001-5528-3309","orcid":"https://orcid.org/0000-0001-5528-3309","contributorId":210093,"corporation":false,"usgs":false,"family":"Proffitt","given":"Kelly","email":"","affiliations":[{"id":38065,"text":"Montana Fish, Wildlife and Parks, Bozeman, Montana","active":true,"usgs":false}],"preferred":false,"id":802169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":802170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jourdonnais, Craig","contributorId":243381,"corporation":false,"usgs":false,"family":"Jourdonnais","given":"Craig","email":"","affiliations":[{"id":48708,"text":"private entitty","active":true,"usgs":false}],"preferred":false,"id":802171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barker, Kristin J.","contributorId":204755,"corporation":false,"usgs":false,"family":"Barker","given":"Kristin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":802172,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202003,"text":"70202003 - 2019 - Long-term suppression of the Lake Trout (Salvelinus namaycush) population in Lake Pend Oreille, Idaho","interactions":[],"lastModifiedDate":"2019-08-19T14:16:28","indexId":"70202003","displayToPublicDate":"2019-02-05T10:01:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Long-term suppression of the Lake Trout (Salvelinus namaycush) population in Lake Pend Oreille, Idaho","title":"Long-term suppression of the Lake Trout (Salvelinus namaycush) population in Lake Pend Oreille, Idaho","docAbstract":"A simulation model of lake trout Salvelinus namaycush (Walbaum 1792) population dynamics in Lake Pend Oreille, Idaho, was used to estimate (1) the optimal allocation of effort among gillnet mesh sizes that minimizes abundance in the shortest time; (2) the number of years needed to suppress the population to 90% of peak abundance; and (3) once suppressed, how much effort could be reduced to sustain abundance indefinitely. A density-dependent stochastic simulation model was parameterized from data in 2006–2016, including parameter uncertainty and implementation error. Time to suppression could be reduced by using more large-mesh gillnet than was used during 2007–2016. Continued fishing at the peak level of total gillnetting effort, but using an optimal effort allocation among meshes, would suppress abundance to the target level within 7–13 years. Once suppressed, gillnet effort could be reduced 76–86% (157,000 m, 95% CI 116,000–199,000 m) to sustain abundance at the target level. Our findings suggest that time to suppression of lake trout populations in other systems may be able to be reduced by optimizing gillnet effort allocation among mesh sizes, and that total effort can be greatly reduced to sustain abundance at the reduced level thereafter.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-019-3890-2","usgsCitation":"Hansen, M.J., Corsi, M.P., and Dux, A.M., 2019, Long-term suppression of the Lake Trout (Salvelinus namaycush) population in Lake Pend Oreille, Idaho: Hydrobiologia, v. 840, no. 1, p. 335-349, https://doi.org/10.1007/s10750-019-3890-2.","productDescription":"15 p.","startPage":"335","endPage":"349","ipdsId":"IP-103474","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":361007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6095733642578,\n 48.24525380784484\n ],\n [\n -116.61300659179688,\n 48.22787470681804\n 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-116.45576477050783,\n 48.31927743759854\n ],\n [\n -116.47499084472656,\n 48.31334122833889\n ],\n [\n -116.47705078125,\n 48.30009642638653\n ],\n [\n -116.50108337402342,\n 48.31242790407178\n ],\n [\n -116.5264892578125,\n 48.310144521881575\n ],\n [\n -116.55326843261719,\n 48.2964420830209\n ],\n [\n -116.55876159667967,\n 48.280908205375084\n ],\n [\n -116.55326843261719,\n 48.2731394946377\n ],\n [\n -116.58485412597656,\n 48.262627005675796\n ],\n [\n -116.6095733642578,\n 48.24525380784484\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"840","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":756611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Matthew P.","contributorId":212797,"corporation":false,"usgs":false,"family":"Corsi","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":756612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":756613,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201989,"text":"70201989 - 2019 - Evaluation of temporally correlated noise in global navigation satellite system time series: Geodetic monument performance","interactions":[],"lastModifiedDate":"2019-03-04T11:09:16","indexId":"70201989","displayToPublicDate":"2019-02-04T16:12:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of temporally correlated noise in global navigation satellite system time series: Geodetic monument performance","docAbstract":"Estimates of background noise of Global Positioning System‐derived time series of positions for 740 sites in the western United States are examined. These data consist of daily epochs of three components of displacements that are at least 9.75 years long within the interval between 2000 and 2018. We find that these time series have significant temporal correlations that could be represented as a combination of white, flicker, random‐walk, and band‐pass filtered noise. From this noise model, two other metrics are computed: the root‐mean‐square of seasonal noise, that is, the integrated power spectrum between 0.5 and 2 cycles per year, and the standard error in position rate for a 10‐year‐long time series. These two metrics are used to evaluate potential correlations with different geographic regions and with different methods of construction of monuments used to attach the Global Positioning System antenna to the Earth's surface. The sites with the lowest noise, both in terms of rate error and seasonal root‐mean‐square, are located in semiarid regions east of the rain shadow provided by the Cascade and Sierra Nevada mountain ranges. In addition, according to statistical rank tests, monuments known as drilled‐braced monuments perform 30% to 50% better than other monument types (buildings, boreholes, piers, etc.) in terms of having smaller rate errors and lower seasonal noise.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB016783","usgsCitation":"Langbein, J., and Svarc, J.L., 2019, Evaluation of temporally correlated noise in global navigation satellite system time series: Geodetic monument performance: Journal of Geophysical Research B: Solid Earth, v. 124, no. 1, p. 925-942, https://doi.org/10.1029/2018JB016783.","productDescription":"18 p.","startPage":"925","endPage":"942","ipdsId":"IP-099225","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":467933,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb016783","text":"Publisher Index Page"},{"id":360990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Langbein, John 0000-0002-7821-8101","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":212735,"corporation":false,"usgs":true,"family":"Langbein","given":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":756441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Svarc, Jerry L. 0000-0002-2802-4528","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":212736,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":756442,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201969,"text":"70201969 - 2019 - Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest","interactions":[],"lastModifiedDate":"2019-06-18T10:04:01","indexId":"70201969","displayToPublicDate":"2019-02-04T12:43:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest","title":"Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest","docAbstract":"The community structures and ecosystem functions of floodplains are primarily driven by variation in flood inundation. However, global changes, such as invasive species and nutrient enrichment, may alter the effects of flooding in these systems. We added nitrogen (N) to correspond with twice the annual atmospheric deposition rate of the south-west Wisconsin, USA region within mature floodplain forest plots and patches of an invasive grass (reed canarygrass, Phalaris arundinacea) along a floodplain elevation gradient in an Upper Mississippi River floodplain forest. We measured soil physicochemical properties and the activity of six extracellular enzymes during 3 months that varied in flooding conditions. Multivariate analyses (distance-based redundancy analysis) revealed that floodplain elevation, month of sampling, and vegetation type were all significant predictors of variation in soil physicochemical properties, while elevation and month were significant predictors of multivariate extracellular enzyme activity (EEA). The best model for predicting EEA consisted of nitrogen availability, soil porosity, and water filled pore space. Although the categorical fertilization and invasion treatments were not significant predictors of EEA, our results suggest that their effects depend on the degree to which they modify N availability and soil moisture. In this system, spatial and temporal patterns in flooding appear to be the main driver of these properties, but N enrichment and invasion may have the potential to further modify them.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-018-09651-2","usgsCitation":"De Jager, N.R., Swanson, W., Hernandez, D.L., Reich, J., Erickson, R.A., and Strauss, E.A., 2019, Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen enrichment on extracellular enzyme activity in an Upper Mississippi River floodplain forest: Wetlands Ecology and Management, v. 27, no. 2-3, p. 443-454, https://doi.org/10.1007/s11273-018-09651-2.","productDescription":"12 p.","startPage":"443","endPage":"454","ipdsId":"IP-102848","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437583,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K2RQMG","text":"USGS data release","linkHelpText":"Effects of flood inundation, invasion by Phalaris arundinacea, and nitrogen deposition on extracellular enzyme activity in an UMR forest: Data"},{"id":360976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"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 -91.40556335449219,\n 43.69071491326582\n ],\n [\n -91.11717224121094,\n 43.69071491326582\n ],\n [\n -91.11717224121094,\n 43.90778718292443\n ],\n [\n -91.40556335449219,\n 43.90778718292443\n ],\n [\n -91.40556335449219,\n 43.69071491326582\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"2-3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":756373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swanson, Whitney","contributorId":194558,"corporation":false,"usgs":false,"family":"Swanson","given":"Whitney","affiliations":[],"preferred":false,"id":756374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hernandez, Daniel L.","contributorId":205330,"corporation":false,"usgs":false,"family":"Hernandez","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":33615,"text":"Carleton College","active":true,"usgs":false}],"preferred":false,"id":756375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reich, Julia","contributorId":205331,"corporation":false,"usgs":false,"family":"Reich","given":"Julia","email":"","affiliations":[{"id":33615,"text":"Carleton College","active":true,"usgs":false}],"preferred":false,"id":756376,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":756377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Strauss, Eric A.","contributorId":190148,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":756378,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228125,"text":"70228125 - 2019 - Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota","interactions":[],"lastModifiedDate":"2022-02-04T17:43:06.939077","indexId":"70228125","displayToPublicDate":"2019-02-04T11:27:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota","title":"Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota","docAbstract":"Changes in land use have resulted in range shifts of many wildlife species, including those entering novel environments, resulting in the critical need to understand their spatial ecology to inform ecosystem effects and management decisions. Dispersing elk (Cervus elaphus) were colonizing areas of suitable habitat in the Northern Great Plains, USA, resulting in crop depredation complaints in these areas. Although state resource managers had little information on these elk herds, limited evidence suggested temporal movements into Canada. We collected and analyzed essential information on home range and habitat selection for 3 elk herds residing in North Dakota. We captured 5 adult female elk in each study area, affixed global positioning system collars, and monitored them for 1 year (2016–2017). We estimated diel period, seasonal, and hunting season home ranges using Brownian Bridge Movement Models for each individual. We analyzed habitat selection using multinomial logit models to test for differences in use of land classes, and for departures from proportionate use based on random sampling; our predictor variables included individual elk, diel period, and season. Home ranges differed between the 3 herds, seasons, and diel period; gun and winter season home ranges were both larger than in summer, as was night when compared with day. Female elk generally restricted themselves to cover during the day and entered open areas at night and during winter months. Our results also suggest that elk in our study areas tended to seek more cover, and in the case of our Turtle Mountain study area, some cross into Canada during gun season. Our study provides a better understanding of the spatial ecology of elk in the Northern Great Plains while highlighting the need for enhanced international cooperative management efforts.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0211650","usgsCitation":"Amor, J.M., Newman, R., Jensen, W.F., Rundquist, B., Walter, W., and Boulanger, J.R., 2019, Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota: PLoS ONE, v. 14, no. 2, p. 1-17, https://doi.org/10.1371/journal.pone.0211650.","productDescription":"e0211650, 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-102787","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0211650","text":"Publisher Index Page"},{"id":395453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Pembina Hills, Porcupine Hills, Turtle Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.5029296875,\n 48.75075629617738\n ],\n [\n -99.6624755859375,\n 48.75075629617738\n ],\n [\n -99.6624755859375,\n 49.001843917978526\n ],\n [\n -100.5029296875,\n 49.001843917978526\n ],\n [\n -100.5029296875,\n 48.75075629617738\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.37158203125,\n 48.474742152125636\n ],\n [\n -97.61627197265625,\n 48.474742152125636\n ],\n [\n -97.61627197265625,\n 49.00004203215395\n ],\n [\n -98.37158203125,\n 49.00004203215395\n ],\n [\n -98.37158203125,\n 48.474742152125636\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.9808349609375,\n 45.98932892799953\n ],\n [\n -100.6951904296875,\n 45.98932892799953\n ],\n [\n -100.6951904296875,\n 46.13607331774968\n ],\n [\n -100.9808349609375,\n 46.13607331774968\n ],\n [\n -100.9808349609375,\n 45.98932892799953\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-02-04","publicationStatus":"PW","contributors":{"editors":[{"text":"Weckerly, Floyd W.","contributorId":15545,"corporation":false,"usgs":true,"family":"Weckerly","given":"Floyd","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":833214,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Amor, Jacqueline M.","contributorId":274630,"corporation":false,"usgs":false,"family":"Amor","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":833172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, Robert","contributorId":248514,"corporation":false,"usgs":false,"family":"Newman","given":"Robert","affiliations":[],"preferred":false,"id":833173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, William F.","contributorId":204832,"corporation":false,"usgs":false,"family":"Jensen","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":36989,"text":"North Dakota Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":833174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rundquist, Bradley 0000-0002-2572-9792","orcid":"https://orcid.org/0000-0002-2572-9792","contributorId":251983,"corporation":false,"usgs":false,"family":"Rundquist","given":"Bradley","email":"","affiliations":[],"preferred":false,"id":833175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boulanger, Jason R.","contributorId":264725,"corporation":false,"usgs":false,"family":"Boulanger","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":833176,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215390,"text":"70215390 - 2019 - Influences of Lake Trout (Salvelinus namaycush) and Mysis diluviana on Kokanee (Oncorhynchus nerka) in Lake Pend Oreille, Idaho","interactions":[],"lastModifiedDate":"2020-10-17T16:07:32.778296","indexId":"70215390","displayToPublicDate":"2019-02-04T10:58:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Influences of Lake Trout (Salvelinus namaycush) and Mysis diluviana on Kokanee (Oncorhynchus nerka) in Lake Pend Oreille, Idaho","docAbstract":"Research on Lake Pend Oreille, Idaho, has focused on the influence of two potential limiting factors for kokanee Oncorhynchus nerka (Walbaum, 1792): competition for food with Mysis diluviana (Loven, 1862, hereafter Mysis) and predation by lake trout Salvelinus namaycush (Walbaum, 1792). Population fluctuations of Mysis and lake trout have resulted in substantial heterogeneity in food web conditions, apparently altering both bottom-up and top-down dynamics. Therefore, relative importance of predation and competition were evaluated as drivers of kokanee abundance, biomass, and production. A series of general linear models was used to evaluate relative influences of Mysis and lake trout on kokanee. Kokanee production was a density-dependent process and the collapse of Mysis corresponded to an increase in the modeled maximum annual production of kokanee from 224 tonnes to 408 tonnes. Lake trout also negatively influenced kokanee biomass. A Mysis-mediated, predator-induced kokanee biomass collapse occurred when lake trout and Mysis abundances were both high. Sustainable management of this fishery requires recognition that competition with Mysis will define the scope of kokanee production and therefore the scope of sustainable predation.
The innermost ring in impact basins exposes material originating from various depths, and can be used to study the composition of the lunar crust with depth. In this study, we conduct quantitative mineralogical analyses of the innermost ring in 13 lunar impact basins using reflectance data from the Kaguya Multiband Imager and radiative transfer modeling. We use results from recent hydrocode modeling to calculate the depth of origin of the material exposed by the innermost rings. We find that the most abundant rock type on the innermost ring of most basins is anorthosite. The mafic assemblages are dominated by olivine in some cases, but most often by pyroxene. The impact modeling suggests that the innermost ring material was excavated from a wide range of depths. Here we focus on two mean depths: a crustal component and a mantle component. The crustal component largely dominates the innermost ring material, and the mantle component is present on the innermost ring of 9 of the basins we studied. On these 9 rings, the abundance of low-calcium pyroxene decreases with the proportion of crustal component, suggesting a dominantly mantle origin. However, as we do not detect exposures of ultramafic material, such mantle material is possibly present at the sub-pixel scale (<62 m). This quantitative study reassesses the composition of the lunar crust and upper mantle, which is of great importance for understanding the formation of the Moon.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.pss.2018.10.003","usgsCitation":"Lemelin, M., Lucey, P.G., Miljkovic, K., Gaddis, L.R., Hare, T.M., and Ohtake, M., 2019, The compositions of the lunar crust and upper mantle: Spectral analysis of the inner rings of lunar impact basins: Planetary and Space Science, v. 165, p. 230-243, https://doi.org/10.1016/j.pss.2018.10.003.","productDescription":"14 p.","startPage":"230","endPage":"243","ipdsId":"IP-080945","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":460501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://id.nii.ac.jp/1696/00030188/","text":"Publisher Index Page"},{"id":361216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lemelin, Myriam","contributorId":213214,"corporation":false,"usgs":false,"family":"Lemelin","given":"Myriam","email":"","affiliations":[],"preferred":false,"id":757133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucey, Paul G.","contributorId":100218,"corporation":false,"usgs":true,"family":"Lucey","given":"Paul","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":757134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miljkovic, Katarina","contributorId":213215,"corporation":false,"usgs":false,"family":"Miljkovic","given":"Katarina","email":"","affiliations":[],"preferred":false,"id":757135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaddis, Lisa R. 0000-0001-9953-5483 lgaddis@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-5483","contributorId":2817,"corporation":false,"usgs":true,"family":"Gaddis","given":"Lisa","email":"lgaddis@usgs.gov","middleInitial":"R.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hare, Trent M. 0000-0001-8842-389X thare@usgs.gov","orcid":"https://orcid.org/0000-0001-8842-389X","contributorId":3188,"corporation":false,"usgs":true,"family":"Hare","given":"Trent","email":"thare@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":757137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ohtake, Makiko","contributorId":213216,"corporation":false,"usgs":false,"family":"Ohtake","given":"Makiko","email":"","affiliations":[],"preferred":false,"id":757138,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203646,"text":"70203646 - 2019 - Ecological consequences of anomalies in atmospheric moisture and snowpack","interactions":[],"lastModifiedDate":"2019-05-30T15:40:41","indexId":"70203646","displayToPublicDate":"2019-02-01T15:39:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological consequences of anomalies in atmospheric moisture and snowpack","docAbstract":"Although increased frequency of extreme‐weather events is one of the most secure predictions associated with contemporary climate change, effects of such events on distribution and abundance of climate‐sensitive species remain poorly understood. Montane ecosystems may be especially sensitive to extreme weather because of complex abiotic and biotic interactions that propagate from climate‐driven reductions in snowpack. Snowpack not only protects subnivean biotas from extreme cold, but also influences forage availability through timing of melt‐off and water availability. We related relative abundances of an alpine mammal, the American pika (Ochotona princeps), to measures of weather and snowpack dynamics over an 8‐yr period that included before and after a year of record‐low snowpack in Washington, USA. We sought to (1) quantify any change in pika abundance associated with the snowpack anomaly and (2) identify aspects of weather and snowpack that influenced abundance of pikas. Pikas showed a 1‐yr lag response to the snowpack anomaly and exhibited marked declines in abundance at elevations below 1,400 m simultaneous with increased abundances at higher elevations. Atmospheric moisture, indexed by vapor pressure deficit (VPD), was especially important, evidenced by strong support for the top‐ranked model that included the interaction of VPD with snowpack duration. Notably, our novel application of VPD from gridded climate data for analyses of animal abundances shows strong potential for improving species distribution models because VPD represents an important aspect of weather that influences the physiology and habitat of biota. Pikas were apparently affected by cold stress without snowpack at mid elevations, whereas changes to forage associated with snowpack and VPD were influential at high and low elevations. Our results reveal context dependency in pika responses to weather and illustrate how snow drought can lead to rapid change in the abundance of subnivean animals.
The Ellenburger–San Saba aquifer discharges spring flows into the overlying Hamilton Creek bed in Burnet County, central Texas. The aquifer is susceptible to contamination from surface‐water reservoirs because of the presence of dissolution cavities that are hydraulically connected to the reservoirs in some locations. There is concern that preferential groundwater seepage from reservoirs into the aquifer in these locations might ultimately degrade the quality of the springwater that enters Hamilton Creek. To investigate preferential groundwater seepage patterns and hydraulic connectivity between surface‐water reservoirs and the Ellenburger–San Saba aquifer, geophysical reconnaissance surveys were completed between July 2017 and January 2018 to map dissolution cavities and locate preferential groundwater seepage within a specific region of the aquifer. Two‐dimensional electric resistivity tomography and self‐potential profiling were utilized, and a simplified, three‐dimensional finite‐element model of the field site was constructed to provide an interpretive aid. The self‐potential data indicated the occurrence of preferential groundwater seepage through a porous seepage conduit that was imaged by the electric resistivity tomography data but did not indicate the occurrence of groundwater seepage through two fluid‐filled dissolution cavities that were imaged by electric resistivity tomography data. Collectively, the surveying and modelling results demonstrate the efficacy of geoelectric methods for mapping the locations of dissolution cavities and preferential groundwater seepage in the electrically resistive karst terrane of the Ellenburger–San Saba aquifer.
","language":"English","publisher":"Wiley","doi":"10.1002/nsg.12023","usgsCitation":"Ikard, S., and Pease, E., 2019, Preferential groundwater seepage in karst terrane inferred from geoelectric measurements: Near Surface Geophysics, v. 17, no. 1, p. 43-53, https://doi.org/10.1002/nsg.12023.","productDescription":"11 p.","startPage":"43","endPage":"53","ipdsId":"IP-091309","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":467939,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nsg.12023","text":"Publisher Index Page"},{"id":437585,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VX0FSC","text":"USGS data release","linkHelpText":"650-m Profiles of Self-Potential, Contact Resistance, and Electric Resistance Tomography Measurements Adjacent to Hamilton Creek, Burnet County, Texas, July 2017 - January 2018"},{"id":360931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":212256,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pease, Emily 0000-0001-8295-1632","orcid":"https://orcid.org/0000-0001-8295-1632","contributorId":210588,"corporation":false,"usgs":true,"family":"Pease","given":"Emily","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755917,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202016,"text":"70202016 - 2019 - Valuation of the flood attenuation ecosystem service in Difficult Run, VA, USA","interactions":[],"lastModifiedDate":"2019-02-05T15:03:04","indexId":"70202016","displayToPublicDate":"2019-02-01T15:02:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Valuation of the flood attenuation ecosystem service in Difficult Run, VA, USA","docAbstract":"Floodplains and riparian wetlands provide several ecosystem services that directly benefit people. We present a methodology for valuing the flood attenuation ecosystem service in Difficult Run, a suburban watershed with extensive natural floodplains in northern Virginia. High-resolution lidar-derived data were combined with GIS modeling techniques to produce estimates of flood inundation. We combined the modeled estimates with parcel-level property and primary economic data using a baseline and a counterfactual scenario to estimate the magnitude of flood attenuation and the associated value of the ecosystem service. Our framework brings new models and data to look at floodplains and an alternative land surface scenario in a way that has not previously been done. Annualized avoided property losses totaled $42,184 in the baseline scenario and $115,596 in the counterfactual scenario for the combined 200-, 100-, 50-, 20-, 10-, and 5-year flood events. We estimate the total annualized value of the flood attenuation ecosystem service in Difficult Run is $73,412, which is $77 per hectare of floodplain area and is consistent with similar valuation studies of floodplains. The framework presented here is not specific to the study area and could be deployed at larger spatial areas in other locations. Our methods may better inform land use decision making on the impacts of development in and surrounding floodplain areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2018.10.023","usgsCitation":"Lawrence, C.B., Pindilli, E., and Hogan, D.M., 2019, Valuation of the flood attenuation ecosystem service in Difficult Run, VA, USA: Journal of Environmental Management, v. 231, p. 1056-1064, https://doi.org/10.1016/j.jenvman.2018.10.023.","productDescription":"9 p.","startPage":"1056","endPage":"1064","ipdsId":"IP-093393","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":467940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2018.10.023","text":"Publisher Index Page"},{"id":361037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Difficult Run watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.35,\n 38.85\n ],\n [\n -77.1833,\n 38.85\n ],\n [\n -77.1833,\n 39.0167\n ],\n [\n -77.35,\n 39.0167\n ],\n [\n -77.35,\n 38.85\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"231","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lawrence, Collin B. 0000-0001-9224-5774","orcid":"https://orcid.org/0000-0001-9224-5774","contributorId":212089,"corporation":false,"usgs":true,"family":"Lawrence","given":"Collin","email":"","middleInitial":"B.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":756699,"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":756700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":756701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70207449,"text":"70207449 - 2019 - Probabilistic relationships between acid-base chemistry and fish assemblages in streams of the western Adirondack Mountains, New York, USA","interactions":[],"lastModifiedDate":"2019-12-19T13:05:48","indexId":"70207449","displayToPublicDate":"2019-02-01T13:01:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic relationships between acid-base chemistry and fish assemblages in streams of the western Adirondack Mountains, New York, USA","docAbstract":"Surface waters across much of the Adirondacks of New York were acidified in the late 20th century but began to recover after the 1990 amendments to the Clean Air Act. Little data, however, were available to characterize biological impacts and predict recovery of fish assemblages in regional streams. Quantitative fish and chemistry surveys were completed in 47 headwater streams during summer 2014-16 to develop logistic (probabilistic) models that characterize the status of contemporary fish assemblages and predict how different N and S deposition loads may affect future fish assemblages. Models for Ali and richness ≥1 species, ANC and total density >400 fish/0.1 ha, ANC and total biomass >1500 g/0.1, presence of Brook Trout, trout density >200 fish/0.1 ha, and trout biomass >1000 g/0.1 ha were suitable for evaluating community and population responses to changes in acid-base chemistry. Anticipated changes in national (US) secondary standards for atmospheric emissions of NOx and SOx to achieve target N and S deposition loads will alter acid-base chemistry and the probabilities for observing various levels of fish metrics in streams across the region and elsewhere.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0260","usgsCitation":"Baldigo, B., George, S., Sullivan, T.J., Driscoll, C.T., Burns, D., Shoa, S., and Lawrence, G.B., 2019, Probabilistic relationships between acid-base chemistry and fish assemblages in streams of the western Adirondack Mountains, New York, USA: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 11, p. 2013-2026, https://doi.org/10.1139/cjfas-2018-0260.","productDescription":"14 p.","startPage":"2013","endPage":"2026","ipdsId":"IP-098032","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":467943,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2018-0260","text":"Publisher Index Page"},{"id":437586,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4V25","text":"USGS data release","linkHelpText":"Adirondack and Catskill Stream-Fish Survey Dataset (ver. 7.0, December 2023)"},{"id":370496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.311279296875,\n 41.77950486590359\n ],\n [\n -73.9215087890625,\n 41.77950486590359\n ],\n [\n -73.9215087890625,\n 42.36666166373274\n ],\n [\n -75.311279296875,\n 42.36666166373274\n ],\n [\n -75.311279296875,\n 41.77950486590359\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"11","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":221408,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott","contributorId":221409,"corporation":false,"usgs":true,"family":"George","given":"Scott","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":778084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":778085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":778086,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shoa, Shuai","contributorId":221410,"corporation":false,"usgs":false,"family":"Shoa","given":"Shuai","email":"","affiliations":[{"id":40368,"text":"Syracuse University, Department of Civil and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":778087,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":778088,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202240,"text":"70202240 - 2019 - Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow","interactions":[],"lastModifiedDate":"2019-02-19T11:43:05","indexId":"70202240","displayToPublicDate":"2019-02-01T11:43:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow","docAbstract":"Tracking changes in stream nutrient inputs to Lake Erie over multidecadal time scales depends on the use of statistical methods that can remove the influence of year-to-year variability of streamflow but also explicitly consider the influence of long-term trends in streamflow. The methods introduced in this paper include an extended version of Weighted Regressions on Time, Discharge, and Season (WRTDS) modeling that explicitly considers nonstationary streamflow by incorporating information on changes in the frequency distribution of daily measured streamflow (discharge) over time. Soluble reactive phosphorus (SRP) trends in annual flow-normalized fluxes (loads) at five long-term monitoring sites in the western Lake Erie drainage basin show increases of 109 to 322% over the period 1995 to 2015. About one-third of the increase appears attributable to increasing discharge trends, while the remaining two-thirds appears to be driven by changes in concentration versus discharge relationships reflecting higher concentrations for any given discharge during recent years. Trends in total phosphorus and three nitrogen parameters (total nitrogen, nitrate-nitrite, and total Kjeldahl nitrogen) at the 10 sites analyzed were much less pronounced, and commonly show decreases in concentration-discharge relationships accompanied by increases in discharge, resulting in little net change in total flux. Trends in monthly SRP fluxes and discharge, dissolved versus particulate fractions of nutrients, and N:P flux ratios were also evaluated. The methods described here provide tools to more clearly discern the effectiveness of nutrient-control strategies and can serve as ongoing measures of progress, or lack of progress, towards nutrient-reduction goals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2018.11.012","usgsCitation":"Choquette, A.F., Hirsch, R.M., Murphy, J.C., Johnson, L., and Confesor, R., 2019, Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow: Journal of Great Lakes Research, v. 45, no. 1, p. 21-39, https://doi.org/10.1016/j.jglr.2018.11.012.","productDescription":"19 p.","startPage":"21","endPage":"39","ipdsId":"IP-098855","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":460508,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2018.11.012","text":"Publisher Index Page"},{"id":361336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.27587890625,\n 40.65980593837852\n ],\n [\n -80.4144287109375,\n 40.65980593837852\n ],\n [\n -80.4144287109375,\n 43.113014204188914\n ],\n [\n -85.27587890625,\n 43.113014204188914\n ],\n [\n -85.27587890625,\n 40.65980593837852\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choquette, Anne F. 0000-0002-7858-1728 achoq@usgs.gov","orcid":"https://orcid.org/0000-0002-7858-1728","contributorId":210699,"corporation":false,"usgs":true,"family":"Choquette","given":"Anne","email":"achoq@usgs.gov","middleInitial":"F.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":167405,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":757448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, L.T.","contributorId":213319,"corporation":false,"usgs":false,"family":"Johnson","given":"L.T.","email":"","affiliations":[{"id":38736,"text":"National Center for Water Quality Research, Heidelberg Univeristy, Tiffin, Ohio","active":true,"usgs":false}],"preferred":false,"id":757449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Confesor, R. B.","contributorId":213320,"corporation":false,"usgs":false,"family":"Confesor","given":"R. B.","affiliations":[{"id":38737,"text":"National Center for Water Quality Research, Heidelberg University, Tiffin, Ohio","active":true,"usgs":false}],"preferred":false,"id":757450,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202090,"text":"70202090 - 2019 - Climate, snow, and soil moisture data set for the Tuolumne and Merced river watersheds, California, USA","interactions":[],"lastModifiedDate":"2019-02-11T10:46:44","indexId":"70202090","displayToPublicDate":"2019-02-01T10:46:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"Climate, snow, and soil moisture data set for the Tuolumne and Merced river watersheds, California, USA","docAbstract":"We present hourly climate data to force land surface process models and assessments over the Merced and Tuolumne watersheds in the Sierra Nevada, California, for the water year 2010–2014 period. Climate data (38 stations) include temperature and humidity (23), precipitation (13), solar radiation (8), and wind speed and direction (8), spanning an elevation range of 333 to 2987 m. Each data set contains raw data as obtained from the source (Level 0), data that are serially continuous with noise and nonphysical points removed (Level 1), and, where possible, data that are gap filled using linear interpolation or regression with a nearby station record (Level 2). All stations chosen for this data set were known or documented to be regularly maintained and components checked and calibrated during the period. Additional time-series data included are available snow water equivalent records from automated stations (8) and manual snow courses (22), as well as distributed snow depth and co-located soil moisture measurements (2–6) from four locations spanning the rain–snow transition zone in the center of the domain. Spatial data layers pertinent to snowpack modeling in this data set are basin polygons and 100 m resolution rasters of elevation, vegetation type, forest canopy cover, tree height, transmissivity, and extinction coefficient. All data are available from online data repositories (https://doi.org/10.6071/M3FH3D).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-11-101-2019","usgsCitation":"Roche, J.W., Rice, R., Meng, X., Cayan, D.R., Dettinger, M.D., Alden, D., Patel, S.C., Mason, M.A., Conklin, M.H., and Bales, R.C., 2019, Climate, snow, and soil moisture data set for the Tuolumne and Merced river watersheds, California, USA: Earth System Science Data, v. 11, p. 101-110, https://doi.org/10.5194/essd-11-101-2019.","productDescription":"10 p.","startPage":"101","endPage":"110","ipdsId":"IP-103542","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":467945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-11-101-2019","text":"Publisher Index Page"},{"id":361121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tuolumne and Merced river watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5,\n 37.5\n ],\n [\n -119,\n 37.5\n ],\n [\n -119,\n 38.25\n ],\n [\n -120.5,\n 38.2546649284538942\n ],\n [\n -120.5,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Roche, James W.","contributorId":178800,"corporation":false,"usgs":false,"family":"Roche","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":756832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rice, Robert","contributorId":149915,"corporation":false,"usgs":false,"family":"Rice","given":"Robert","affiliations":[],"preferred":false,"id":756833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meng, Xiande","contributorId":213043,"corporation":false,"usgs":false,"family":"Meng","given":"Xiande","email":"","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":756834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayan, Daniel R. 0000-0002-2719-6811 drcayan@usgs.gov","orcid":"https://orcid.org/0000-0002-2719-6811","contributorId":1494,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","email":"drcayan@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":756835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":756831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alden, Douglas","contributorId":213045,"corporation":false,"usgs":false,"family":"Alden","given":"Douglas","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":756836,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patel, Sarina C.","contributorId":213046,"corporation":false,"usgs":false,"family":"Patel","given":"Sarina","email":"","middleInitial":"C.","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":756837,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mason, Megan A.","contributorId":213047,"corporation":false,"usgs":false,"family":"Mason","given":"Megan","email":"","middleInitial":"A.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":756838,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conklin, Martha H.","contributorId":189395,"corporation":false,"usgs":false,"family":"Conklin","given":"Martha","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":756839,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bales, Roger C.","contributorId":189659,"corporation":false,"usgs":false,"family":"Bales","given":"Roger","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":756840,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70205060,"text":"70205060 - 2019 - Financing agricultural drought risk through ex-ante cash transfers","interactions":[],"lastModifiedDate":"2024-05-17T14:55:18.445952","indexId":"70205060","displayToPublicDate":"2019-02-01T09:26:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Financing agricultural drought risk through ex-ante cash transfers","docAbstract":"Despite advances in drought early warning systems, forecast information is rarely used for triggering and financing early actions, such as cash transfer. Scaling up cash transfer pay-outs , and overcoming the barriers to actions based on forecasts, requires an understanding of costs resulting from False Alarms, and the potential benefits associated with appropriate early interventions. On this study, we evaluate the potential cost-effectiveness of cash transfer responses, comparing the relative costs of ex-ante cash transfers during the maize growing season to ex-post cash transfers after harvesting in Kenya. For that, we developed a forecast model using Fast-and Frugal Trees that unravels early warning relationships between climate variability, vegetation coverage, and maize yields at multiple lead times. Results indicate that our models correctly forecast low maize yield events 85% of the time across the districts studied, some already six months before harvesting. The models’ performance improves towards the end of the growing season driven by a decrease of 39% in the probability of False Alarms. Overall, we show that timely cash transfers ex-ante to a disaster can often be more cost-effective than investing in ex-post expenditures. Our findings suggest that early response can yield significant cost savings, and can potentially increase the effectiveness of existing cash transfer systems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.10.406","usgsCitation":"Nobre, G.G., Davenport, F., Bischiniotis, K., Veldcamp, T., Jongman, B., Funk, C., Husak, G., Ward, P.J., and Aerts, J.C., 2019, Financing agricultural drought risk through ex-ante cash transfers: Science of the Total Environment, v. 653, p. 523-535, https://doi.org/10.1016/j.scitotenv.2018.10.406.","productDescription":"13 p.","startPage":"523","endPage":"535","ipdsId":"IP-099846","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467946,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.10.406","text":"Publisher Index Page"},{"id":367065,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kenya","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[40.993,-0.85829],[41.58513,-1.68325],[40.88477,-2.08255],[40.63785,-2.49979],[40.26304,-2.57309],[40.12119,-3.27768],[39.80006,-3.68116],[39.60489,-4.34653],[39.20222,-4.67677],[37.7669,-3.67712],[37.69869,-3.09699],[34.07262,-1.05982],[33.90371,-0.95],[33.89357,0.10981],[34.18,0.515],[34.6721,1.17694],[35.03599,1.90584],[34.59607,3.05374],[34.47913,3.5556],[34.005,4.24988],[34.6202,4.84712],[35.29801,5.506],[35.81745,5.33823],[35.81745,4.77697],[36.15908,4.44786],[36.85509,4.44786],[38.12091,3.59861],[38.43697,3.58851],[38.67114,3.61607],[38.89251,3.50074],[39.55938,3.42206],[39.85494,3.83879],[40.76848,4.25702],[41.1718,3.91909],[41.85508,3.91891],[40.98105,2.78452],[40.993,-0.85829]]]},\"properties\":{\"name\":\"Kenya\"}}]}","volume":"653","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nobre, Gabriela Guimaraes","contributorId":218649,"corporation":false,"usgs":false,"family":"Nobre","given":"Gabriela","email":"","middleInitial":"Guimaraes","affiliations":[{"id":39879,"text":"Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam","active":true,"usgs":false}],"preferred":false,"id":769801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davenport, Frank","contributorId":145816,"corporation":false,"usgs":false,"family":"Davenport","given":"Frank","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":769802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bischiniotis, Konstantinos","contributorId":218650,"corporation":false,"usgs":false,"family":"Bischiniotis","given":"Konstantinos","email":"","affiliations":[{"id":39880,"text":"Institute for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":769803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veldcamp, Ted","contributorId":218651,"corporation":false,"usgs":false,"family":"Veldcamp","given":"Ted","email":"","affiliations":[{"id":39880,"text":"Institute for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":769805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jongman, Brenden","contributorId":218652,"corporation":false,"usgs":false,"family":"Jongman","given":"Brenden","email":"","affiliations":[{"id":39880,"text":"Institute for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":769806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":769800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769807,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ward, Philip J.","contributorId":67434,"corporation":false,"usgs":true,"family":"Ward","given":"Philip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":769861,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Aerts, Jeroen C.J.H.","contributorId":215545,"corporation":false,"usgs":false,"family":"Aerts","given":"Jeroen","email":"","middleInitial":"C.J.H.","affiliations":[{"id":39273,"text":"Institute for Environmental Studies (IVM), VU University Amsterdam","active":true,"usgs":false}],"preferred":false,"id":769808,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204530,"text":"70204530 - 2019 - Flow-ecology relationships are spatially structured and differ among flow regimes","interactions":[],"lastModifiedDate":"2019-08-01T08:37:26","indexId":"70204530","displayToPublicDate":"2019-02-01T08:36:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Flow-ecology relationships are spatially structured and differ among flow regimes","docAbstract":"In streams, hydrology is a predominant driver of ecological structure and function. Providing adequate flows to support aquatic life, or environmental flows, is therefore a top management priority in stream systems.\n\nFlow regime classification is a widely accepted approach for establishing environmental flow guidelines. However, it is surprisingly difficult to quantify relationships between hydrology and ecology (flow–ecology relationships) while describing how these relationships vary across classified flow regimes. Developing such relationships is complicated by several sources of spatial bias, such as autocorrelation due to spatial design, flow regime classification and other environmental or ecological sources of spatial bias.\n\nWe used mixed moving‐average spatial stream network models to develop flow–ecology relationships across classified flow regimes and to assess spatial patterns of these relationships. We compared relationships between fish traits and life‐history strategies with hydrologic metrics across flow regimes and assessed whether spatial autocorrelation influenced these relationships.\n\nTrait–hydrology relationships varied between flow regimes and across all streams combined. Some relationships between traits and hydrologic metrics fit predictions based on life‐history theory, while others exhibited unexpected relationships with hydrology. Spatial factors described a large proportion of variability in fish traits and different patterns of spatial autocorrelation were observed in different flow regimes.\n\nSynthesis and applications. Further work is needed to understand why flow–ecology relationships vary across classified flow regimes and why these relationships may not fit predictions based on life‐history theories. Managers determining environmental flow standards need to be aware that different hydrologic metrics are often important drivers of fish trait diversity in different flow regimes. Flow–ecology relationships may therefore be confounded by spatial structure inherent in flow regime classification and much existing biological data. Complex patterns of spatial bias should be considered when managing stream systems within an environmental flows framework.","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.13297","usgsCitation":"Magoulick, D.D., 2019, Flow-ecology relationships are spatially structured and differ among flow regimes: Journal of Applied Ecology, v. 56, no. 2, p. 398-412, https://doi.org/10.1111/1365-2664.13297.","productDescription":"15 p.","startPage":"398","endPage":"412","ipdsId":"IP-084577","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13297","text":"Publisher Index Page"},{"id":366059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":767415,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202727,"text":"70202727 - 2019 - Hierarchical multi-population viability analysis","interactions":[],"lastModifiedDate":"2019-03-25T09:23:33","indexId":"70202727","displayToPublicDate":"2019-01-31T16:26:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical multi-population viability analysis","docAbstract":"Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985–2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical\nmulti-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with\nrobust estimates of population dynamics, extinction risks, and uncertainties.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2538","usgsCitation":"Leasure, D.R., Wenger, S.J., Chelgren, N., Neville, H.M., Dauwalter, D.C., Bjork, R., Fesenmyer, K.A., Dunham, J.B., Peacock, M.M., Luce, C.H., Lute, A.C., and Isaak, D.J., 2019, Hierarchical multi-population viability analysis: Ecology, v. 100, no. 1, p. 1-18, https://doi.org/10.1002/ecy.2538.","productDescription":"Article e02538: 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-098568","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2538","text":"Publisher Index Page"},{"id":362254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Leasure, Douglas R.","contributorId":145643,"corporation":false,"usgs":false,"family":"Leasure","given":"Douglas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":759674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":759675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":759676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neville, Helen M.","contributorId":214338,"corporation":false,"usgs":false,"family":"Neville","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":759677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dauwalter, Daniel C.","contributorId":214339,"corporation":false,"usgs":false,"family":"Dauwalter","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":759678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bjork, Robin","contributorId":214340,"corporation":false,"usgs":false,"family":"Bjork","given":"Robin","email":"","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":759679,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fesenmyer, Kurt A.","contributorId":214341,"corporation":false,"usgs":false,"family":"Fesenmyer","given":"Kurt","email":"","middleInitial":"A.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":759680,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759681,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peacock, Mary M.","contributorId":167605,"corporation":false,"usgs":false,"family":"Peacock","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":24774,"text":"Department of Natural Resources, College of Agriculture and Life","active":true,"usgs":false}],"preferred":false,"id":759682,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Luce, Charlie H.","contributorId":173471,"corporation":false,"usgs":false,"family":"Luce","given":"Charlie","email":"","middleInitial":"H.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":759683,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lute, Abby C.","contributorId":214342,"corporation":false,"usgs":false,"family":"Lute","given":"Abby","email":"","middleInitial":"C.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":759684,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":759685,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70201879,"text":"70201879 - 2019 - Decision-making in agent-based modeling: A current review and future prospectus","interactions":[],"lastModifiedDate":"2019-01-31T15:10:29","indexId":"70201879","displayToPublicDate":"2019-01-31T15:10:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Decision-making in agent-based modeling: A current review and future prospectus","docAbstract":"All basic processes of ecological populations involve decisions; when and where to move, when and what to eat, and whether to fight or flee. Yet decisions and the underlying principles of decision-making have been difficult to integrate into the classical population-level models of ecology. Certainly, there is a long history of modeling individuals' searching behavior, diet selection, or conflict dynamics within social interactions. When all the individuals are given certain simple rules to govern their decision-making processes, the resultant population–level models have yielded important generalizations and theory. But it is also recognized that such models do not represent the way real individuals decide on actions. Factors that influence a decision include the organism's environment with its dynamic rewards and risks, the complex internal state of the organism, and its imperfect knowledge of the environment. In the case of animals, it may also involve complex social factors, and experience and learning, which vary among individuals. The way that all factors are weighed and processed to lead to decisions is a major area of behavioral theory.
While classic population-level modeling is limited in its ability to integrate decision-making in its actual complexity, the development of individual- or agent-based models (IBM/ABMs) (we use ABM throughout to designate both “agent-based modeling” and an “agent-based model”) has opened the possibility of describing the way that decisions are made, and their effects, in minute detail. Over the years, these models have increased in size and complexity. Current ABMs can simulate thousands of individuals in realistic environments, and with highly detailed internal physiology, perception and ability to process the perceptions and make decisions based on those and their internal states. The implementation of decision-making in ABMs ranges from fairly simple to highly complex; the process of an individual deciding on an action can occur through the use of logical and simple (if-then) rules to more sophisticated neural networks and genetic algorithms. The purpose of this paper is to give an overview of the ways in which decisions are integrated into a variety of ABMs and to give a prospectus on the future of modeling of decisions in ABMs.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2018.00237","usgsCitation":"DeAngelis, D.L., and Diaz, S.G., 2019, Decision-making in agent-based modeling: A current review and future prospectus: Frontiers in Ecology and Evolution, v. 6, p. 1-16, https://doi.org/10.3389/fevo.2018.00237.","productDescription":"Article 237; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-102146","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2018.00237","text":"Publisher Index Page"},{"id":360887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","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":755750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diaz, Stephanie G.","contributorId":212228,"corporation":false,"usgs":false,"family":"Diaz","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":755751,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201820,"text":"70201820 - 2019 - The formation of gullies on Mars today","interactions":[],"lastModifiedDate":"2019-01-31T12:45:02","indexId":"70201820","displayToPublicDate":"2019-01-31T12:44:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"The formation of gullies on Mars today","docAbstract":"A decade of high-resolution monitoring has revealed extensive activity in fresh Martian gullies. Flows within the gullies are diverse: they can be relatively light, neutral or dark, colourful or bland, and range from superficial deposits to 10 m-scale topographic changes. We observed erosion and transport of material within gullies, new terraces, freshly eroded channel segments, migrating sinuous curves, channel abandonment, and lobate deposits. We also observed early stages of gully initiation, demonstrating that these processes are not merely modifying pre-existing landforms. The timing of activity closely correlates with the presence of seasonal CO2 frost, so the current changes must be part of ongoing gully formation that is driven largely by its presence. We suggest that the cumulative effect of many flows erodes alcoves and channels, and builds lobate aprons, with no involvement of liquid water. Instead, flows may be fluidized by sublimation of entrained CO2 ice or other mechanisms. The frequent activity is likely to have erased any features dating from high-obliquity periods, so fresh gully geomorphology at middle and high latitudes is not evidence for past liquid water. CO2 ice-driven processes may have been important throughout Martian geological history and their deposits could exist in the rock record, perhaps resembling debris-flow sediments.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP467.5","usgsCitation":"Dundas, C.M., McEwen, A.S., Diniega, S., Hansen, C.J., and McElwaince, J.N., 2019, The formation of gullies on Mars today: Geological Society, London, Special Publications, v. 467, p. 67-94, https://doi.org/10.1144/SP467.5.","productDescription":"28 p.","startPage":"67","endPage":"94","ipdsId":"IP-082415","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":467952,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":360869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"467","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-27","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":755475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":755476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diniega, Serina","contributorId":212017,"corporation":false,"usgs":false,"family":"Diniega","given":"Serina","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":755477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Candice J.","contributorId":70235,"corporation":false,"usgs":false,"family":"Hansen","given":"Candice","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":755478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McElwaince, Jim N.","contributorId":212018,"corporation":false,"usgs":false,"family":"McElwaince","given":"Jim","email":"","middleInitial":"N.","affiliations":[{"id":38386,"text":"Durham University/PSI","active":true,"usgs":false}],"preferred":true,"id":755479,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203370,"text":"70203370 - 2019 - Seasonal distribution of Dall's porpoise in Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2019-05-09T12:53:12","indexId":"70203370","displayToPublicDate":"2019-01-31T12:43:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5536,"text":"Deep Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal distribution of Dall's porpoise in Prince William Sound, Alaska","docAbstract":"Dall's porpoise, Phocoenoides dalli, are a conspicuous predator in the Prince William Sound ecosystem, yet there has been little effort directed towards monitoring this species since the 1980s, prior to the Exxon Valdez oil spill. We used vessel-based surveys to examine the seasonal distribution of Dall's porpoise in the waters of Prince William Sound during eight years from 2007 to 2015. Over the course of 168 days and 15,653. km of survey effort, 921 Dall's porpoise were encountered in 210 groups. We estimate an encounter rate of 0.061 porpoise/km traveled or 1 porpoise encountered for every 16.5. km traveled. Dall's porpoise were found throughout the year in Prince William Sound, and used a wide range of habitats, including those not considered typical of the species, such as bays, shallow water, and nearshore waters. Dall's porpoise seasonally shifted their center of distribution from the western passages in fall to the bays of the eastern Sound in winter and spring. Dall's porpoises were widely dispersed throughout the Sound in summer. We identified potential Dall's porpoise habitat (depth, slope, and distance from shore) within Prince William Sound using generalized additive models (GAM). Dall's porpoise were found in deeper water during summer and in shallowest water during spring. We propose that their use of novel habitats is a function of reduced predation risk associated with the decline of their main predator, killer whales (Orcinus orca), following the Exxon Valdez oil spill, and the presence of overwintering and spawning Pacific herring (Clupea pallasii). While the size of the Dall's porpoise population within Prince William Sound remains unknown, our encounter rates were lower than those reported in the 1970s. Their high metabolic rate and ubiquitous presence makes them one of the more important, yet understudied, forage fish predators in the region.","language":"English","doi":"10.1016/j.dsr2.2017.11.002","usgsCitation":"Moran, J., O’Dell, M., Arimitsu, M.L., Straley, J.M., and Dickson, D., 2019, Seasonal distribution of Dall's porpoise in Prince William Sound, Alaska: Deep Sea Research Part II: Topical Studies in Oceanography, v. 147, p. 164-172, https://doi.org/10.1016/j.dsr2.2017.11.002.","productDescription":"9 p.","startPage":"164","endPage":"172","ipdsId":"IP-081589","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":467953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2017.11.002","text":"Publisher Index Page"},{"id":363644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148.5,60.0 ], [ -148.5,61.0 ], [ -146.5,61.0 ], [ -146.5,60.0 ], [ -148.5,60.0 ] ] ] } } ] }","volume":"147","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moran, J.R.","contributorId":215437,"corporation":false,"usgs":false,"family":"Moran","given":"J.R.","email":"","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":762359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Dell, M.B.","contributorId":215438,"corporation":false,"usgs":false,"family":"O’Dell","given":"M.B.","email":"","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":762360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":762358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Straley, Jan M","contributorId":215440,"corporation":false,"usgs":false,"family":"Straley","given":"Jan","email":"","middleInitial":"M","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":762362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickson, D.M.S.","contributorId":215439,"corporation":false,"usgs":false,"family":"Dickson","given":"D.M.S.","email":"","affiliations":[{"id":39247,"text":"North Pacific Research Board","active":true,"usgs":false}],"preferred":false,"id":762361,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201817,"text":"70201817 - 2019 - The flood lavas of Kasei Valles, Mars","interactions":[],"lastModifiedDate":"2019-01-31T11:48:53","indexId":"70201817","displayToPublicDate":"2019-01-31T11:48:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"The flood lavas of Kasei Valles, Mars","docAbstract":"Both the northern and southern arms of Kasei Valles are occupied by platy-ridged flood lavas. We have mapped these flows and examined their morphology to better understand their emplacement. The lavas were emplaced as high-flux, turbulent flows (exceeding 106 m3 s−1). Lava in southern Kasei Valles can be traced back up onto the Tharsis rise, which is also the likely source of lavas in the northern arm. These eruptions were similar to, but somewhat smaller than, the Athabasca Valles flood lava in Elysium Planitia, with estimated volumes of > 1200 km3 here and 5000 km3 in Athabasca Valles. The flood lavas in both Kasei and Athabasca Valles have evidence for distal inflation as well as widespread drainage or volume loss in medial areas; this may be an important characteristic of many large, recent Martian eruptions. Despite their great size and flux, the Kasei Valles flood lavas are only a late modification to the valley system capable of only modest local erosion. The more vigorous Athabasca Valles lava may have been capable of somewhat more erosion in its smaller valley system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2018.11.008","usgsCitation":"Dundas, C.M., Cushing, G.E., and Keszthelyi, L.P., 2019, The flood lavas of Kasei Valles, Mars: Icarus, v. 321, p. 346-357, https://doi.org/10.1016/j.icarus.2018.11.008.","productDescription":"12 p.","startPage":"346","endPage":"357","ipdsId":"IP-095264","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":467954,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8312693","text":"External Repository"},{"id":360865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"321","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"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":755471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cushing, Glen E. 0000-0002-9673-8207 gcushing@usgs.gov","orcid":"https://orcid.org/0000-0002-9673-8207","contributorId":175449,"corporation":false,"usgs":true,"family":"Cushing","given":"Glen","email":"gcushing@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":755472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":227,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"laz@usgs.gov","middleInitial":"P.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":755473,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201824,"text":"70201824 - 2019 - Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060","interactions":[],"lastModifiedDate":"2019-01-31T11:41:56","indexId":"70201824","displayToPublicDate":"2019-01-31T11:41:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060","docAbstract":"In order to simulate the potential effect of forecasted land‐cover change on streamflow and water availability, there has to be confidence that the hydrologic model used is sensitive to small changes in land cover (<10%) and that this land‐cover change exceeds the inherent uncertainty in forecasted conditions. To investigate this, a 26‐year streamflow record was simulated for 33 basins (54–928 km2) in the Delaware River Basin using three dates of land cover: the 2011 National Land‐Cover Dataset (Homer, Fry, & Barnes, 2012), 2030 land‐cover conditions representing median values from 101 equally‐likely forecasts, and 2060 land‐cover conditions corresponding to the same iterations used to represent 2030. Streamflow was simulated using a process‐based hydrologic model that includes both pervious and impervious methods as parameterized by three land‐cover‐based hydrologic response units (HRUs)—forested, agricultural, and developed land. Small, but significant differences in streamflow magnitude, variability, and seasonality were seen among the three time periods—2011, 2030, and 2060. Temporal differences were discernible from the range of conditions simulated with 101 equally likely forecasts for 2030. Development was co‐located with the most frequent landscape components, as characterized by topographic wetness index, resulting in a change in hydrology for each HRU, highlighting that knowing the location of disturbance is key to understanding potential streamflow changes. These results show that streamflow simulation using regional calibration that incorporates land‐cover‐based HRUs can be sensitive to relatively small changes in land‐cover and that temporal trends resulting from land‐cover change can be isolated in order to evaluate other changes that might affect water resources.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13315","usgsCitation":"Williamson, T.N., and Claggett, P.R., 2019, Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060: Hydrological Processes, v. 33, no. 1, p. 115-129, https://doi.org/10.1002/hyp.13315.","productDescription":"15 p.","startPage":"115","endPage":"129","ipdsId":"IP-084563","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":467955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13315","text":"Publisher Index Page"},{"id":360863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware River Basin ","volume":"33","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claggett, Peter R. 0000-0002-5335-2857 pclaggett@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":176287,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","email":"pclaggett@usgs.gov","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":755495,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}