Arid shrublands are stressful environments, typified by alkaline soils low in organic matter, with biologically-limiting extremes in water availability, temperature, and UV radiation. The widely-spaced plants and interspace biological soil crusts in these regions provide soil nutrients in a localized fashion, creating a mosaic pattern of plant- or crust-associated microhabitats with distinct nutrient composition. With sporadic and limited rainfall, nutrients are primarily retained in the shallow surface soil, patterning biological activity. We examined soil bacterial and fungal community responses to simulated nitrogen (N) deposition in an arid Larrea tridentata-Ambrosia dumosa field experiment in southern Nevada, USA, using high-throughput sequencing of ribosomal RNA genes. To examine potential interactions among the N application, microhabitat and soil depth, we sampled soils associated with shrub canopies and interspace biological crusts at two soil depths (0–0.5 or 0–10 cm) across the N-amendment gradient (0, 7, and 15 kg ha−1 yr−1). We hypothesized that localized compositional differences in soil microbiota would constrain the impacts of N addition to a microhabitat distribution that would reflect highly localized geochemical conditions and microbial community composition. The richness and community composition of both bacterial and fungal communities differed significantly by microhabitat and with soil depth in each microhabitat. Only bacterial communities exhibited significant responses to the N addition. Community composition correlated with microhabitat and depth differences in soil geochemical features. Given the distinct roles of soil bacteria and fungi in major nutrient cycles, the resilience of fungi and sensitivity of bacteria to N amendments suggests that increased N input predicted for many arid ecosystems could shift nutrient cycling toward pathways driven primarily by fungal communities.
The Colorado River and its tributaries supply water to more than 35 million people in the United States and 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about 12 billion kilowatt hours of hydroelectric power annually. The Upper Colorado River Basin, encompassing more than 110,000 square miles (mi2), contains the headwaters of the Colorado River (also known as the River) and is an important source of snowmelt runoff to the River. Groundwater discharge also is an important source of water in the River and its tributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin. Planning for the sustainable management of the Colorado River in future climates requires an understanding of the Upper Colorado River Basin groundwater system. This report documents input datasets for a Soil-Water Balance groundwater recharge model that was developed for the Upper Colorado River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151160","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the USGS Groundwater Resources Program","usgsCitation":"Tillman, F., 2015, Documentation of input datasets for the soil-water balance groundwater recharge model of the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1160, v, 17 p., https://doi.org/10.3133/ofr20151160.","productDescription":"v, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066684","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":307918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1160/coverthb.jpg"},{"id":307919,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1160/ofr20151160.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1160 PDF"},{"id":316699,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://water.usgs.gov/lookup/getspatial?ofr_2015_1160_soil-water_balance"}],"country":"Mexico, United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.69937133789062,\n 36.730079507078415\n ],\n [\n -111.68083190917969,\n 36.730079507078415\n ],\n [\n -111.64581298828125,\n 36.72677751526221\n ],\n [\n -111.4068603515625,\n 36.67723060234619\n ],\n [\n -111.181640625,\n 36.54936246839778\n ],\n [\n -110.45654296875,\n 36.46105407505434\n ],\n [\n -109.8687744140625,\n 35.991340960635405\n ],\n [\n -109.5062255859375,\n 35.67068501330236\n ],\n [\n -109.21508789062499,\n 35.48751102385376\n ],\n [\n -108.907470703125,\n 35.34425514918409\n ],\n [\n -107.5286865234375,\n 35.290468565908775\n ],\n [\n -107.2760009765625,\n 35.28150065789119\n ],\n [\n -107.215576171875,\n 35.31736632923788\n ],\n [\n -107.13317871093749,\n 35.460669951495305\n ],\n [\n -106.9793701171875,\n 35.62604706595698\n ],\n [\n -106.94091796875,\n 35.817813158696616\n ],\n [\n -106.875,\n 36.26199220445664\n ],\n [\n -106.842041015625,\n 36.67723060234619\n ],\n [\n -106.864013671875,\n 37.02886944696474\n ],\n [\n -107.0068359375,\n 37.21283151445594\n ],\n [\n -107.33642578124999,\n 37.37015718405753\n ],\n [\n -107.545166015625,\n 37.55328764595765\n ],\n [\n -107.666015625,\n 37.74465712069939\n ],\n [\n -107.42431640625,\n 37.84883250647402\n ],\n [\n -107.07275390625,\n 37.90953361677018\n ],\n [\n -106.6552734375,\n 38.004819966413194\n ],\n [\n -106.666259765625,\n 38.33303882235456\n ],\n [\n -106.69921875,\n 38.685509760012\n ],\n [\n -106.875,\n 39.13006024213511\n ],\n [\n -106.435546875,\n 39.40224434029275\n ],\n [\n -105.9521484375,\n 39.740986355883564\n ],\n [\n -105.908203125,\n 40.34654412118006\n ],\n [\n -105.99609375,\n 40.613952441166596\n ],\n [\n -106.435546875,\n 40.74725696280421\n ],\n [\n -106.69921875,\n 41.64007838467894\n ],\n [\n -107.57812499999999,\n 42.65012181368025\n ],\n [\n -108.10546875,\n 42.84375132629023\n ],\n [\n -108.8525390625,\n 43.13306116240612\n ],\n [\n -109.423828125,\n 43.197167282501276\n ],\n [\n -109.77539062499999,\n 43.42100882994726\n ],\n [\n -109.9072265625,\n 43.67581809328341\n ],\n [\n -110.3466796875,\n 43.83452678223682\n ],\n [\n -110.61035156249999,\n 43.67581809328341\n ],\n [\n -110.74218749999999,\n 43.13306116240612\n ],\n [\n -110.8740234375,\n 42.19596877629178\n ],\n [\n -111.0498046875,\n 41.44272637767212\n ],\n [\n -111.0498046875,\n 41.19518982948959\n ],\n [\n -111.181640625,\n 41.04621681452063\n ],\n [\n -111.37939453125,\n 40.94671366508002\n ],\n [\n -111.533203125,\n 40.613952441166596\n ],\n [\n -111.73095703125,\n 40.245991504199026\n ],\n [\n -111.884765625,\n 39.8928799002948\n ],\n [\n -111.97265625,\n 39.33429742980725\n ],\n [\n -112.2802734375,\n 39.11301365149975\n ],\n [\n -112.43408203124999,\n 38.856820134743636\n ],\n [\n -112.60986328125,\n 38.59970036588819\n ],\n [\n -112.60986328125,\n 38.376115424036016\n ],\n [\n -112.67578124999999,\n 38.22091976683121\n ],\n [\n -112.8955078125,\n 37.87485339352928\n ],\n [\n -113.02734374999999,\n 37.579412513438385\n ],\n [\n -113.02734374999999,\n 37.26530995561875\n ],\n [\n -112.9833984375,\n 37.00255267215955\n ],\n [\n -112.67578124999999,\n 36.756490329505155\n ],\n [\n -112.34619140625,\n 36.5978891330702\n ],\n [\n -111.97265625,\n 36.56260003738548\n ],\n [\n -111.69937133789062,\n 36.730079507078415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
The population of Striped Bass Morone saxatilis in Chesapeake Bay has increased significantly since the 1980s because of management efforts while the relative abundance of some key prey fish has declined since the 1970s. We examined the trophic interactions and prey consumption patterns of Striped Bass in Chesapeake Bay to determine how Striped Bass have responded to changing prey resources. Seasonal diet, growth, and thermal data were collected from 1955 to 1959, 1990 to 1992, and 1998 to 2001; these data were coupled with a bioenergetics model approach to characterize temporal patterns in prey consumption for Striped Bass. The estimates were compared across each period to build a historical prey consumption profile from 1955 to 2001. Prey consumption dynamics for Striped Bass have changed dramatically between 1955 and 2001. In general, Striped Bass in the early and late 1990s consumed less Atlantic Menhaden Brevoortia tyranus and more Bay Anchovy Anchoa mitchilli than during the 1950s. The largest differences in consumption were observed in the younger age-classes. During 1998–2001, age-1 and age-2 Striped Bass consumed, respectively, 15.5 and 11.9 times less Atlantic Menhaden than during the 1950sand 12.2 and 7.2 less than during 1990–1992. Bay Anchovy were almost absent in the diet of bass age 3 and older during the 1950s but were consumed by the age-3+ group during 1990–1992 and to a greater extent during 1998–2001. Age-3+ Striped Bass during 1998–2001, on average, consumed twice as much Bay Anchovy than during 1990–1992. Blue crab Callinectes sappidus were consumed only by age 2 in the 1950s and 1990–1992 and by ages 2 and older in 1998–2001. Age-2 bass consumed 8.8 more blue crab in 1990–1992 and 7.5 times more in 1998–2001 than during the 1950s. The patterns in the consumption of Atlantic Menhaden coincided with increased consumption of Bay Anchovy and blue crab, possibly as a result of the declines in Atlantic Menhaden relative abundance in Chesapeake Bay. The difference in consumption was also evident in the total energy consumed; age-1 and age-6 Striped Bass consumed 1.6 times more energy in 1955–1959 than during 1998–2001. Our research demonstrates how the elements of Striped Bass feeding, including diet composition, amount of food eaten, and consumption rates, are affected by prey resources.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2015.1045989","usgsCitation":"Overton, A.S., Griffin, J., Margraf, F.J., May, E.B., and Hartman, K.J., 2015, Chronicling long-term predator responses to a shifting forage base in Chesapeake Bay: an energetics approach: Transactions of the American Fisheries Society, v. 144, no. 5, p. 956-966, https://doi.org/10.1080/00028487.2015.1045989.","productDescription":"11 p.","startPage":"956","endPage":"966","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1955-01-01","temporalEnd":"2001-12-31","ipdsId":"IP-059482","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":307928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.992431640625,\n 36.910372213522535\n ],\n [\n -75.56396484375,\n 38.00049145082287\n ],\n [\n -75.8221435546875,\n 39.690280594818034\n ],\n [\n -76.7340087890625,\n 39.25352462727606\n ],\n [\n -77.0965576171875,\n 38.06539235133249\n ],\n [\n -77.0965576171875,\n 37.16907157713011\n ],\n [\n -76.5802001953125,\n 36.76969233214548\n ],\n [\n -75.992431640625,\n 36.910372213522535\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-12","publicationStatus":"PW","scienceBaseUri":"55e96120e4b0dacf699e7855","contributors":{"authors":[{"text":"Overton, Anthony S.","contributorId":147350,"corporation":false,"usgs":false,"family":"Overton","given":"Anthony","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":571416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffin, Jennifer C.","contributorId":147352,"corporation":false,"usgs":false,"family":"Griffin","given":"Jennifer C.","affiliations":[],"preferred":false,"id":571417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Margraf, F. Joseph jmargraf@usgs.gov","contributorId":257,"corporation":false,"usgs":true,"family":"Margraf","given":"F.","email":"jmargraf@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":571039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"May, Eric B.","contributorId":147354,"corporation":false,"usgs":false,"family":"May","given":"Eric","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":571418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, Kyle J.","contributorId":6414,"corporation":false,"usgs":false,"family":"Hartman","given":"Kyle","email":"","middleInitial":"J.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":571419,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155968,"text":"fs20153052 - 2015 - Assessment of undiscovered oil and gas resources in the Uteland Butte Member of the Eocene Green River Formation, Uinta Basin, Utah","interactions":[],"lastModifiedDate":"2015-09-04T09:15:43","indexId":"fs20153052","displayToPublicDate":"2015-09-03T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3052","title":"Assessment of undiscovered oil and gas resources in the Uteland Butte Member of the Eocene Green River Formation, Uinta Basin, Utah","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered resources of 214 million barrels of oil, 329 billion cubic feet of associated/dissolved natural gas, and 14 million barrels of natural gas liquids in the informal Uteland Butte member of the Green River Formation, Uinta Basin, Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153052","collaboration":"Prepared in cooperation with the National and Global Petroleum Assessment","usgsCitation":"Johnson, R.C., Birdwell, J.E., Mercier, T.J., Brownfield, M.E., Charpentier, R.R., Klett, T.R., Leathers, H.M., Schenk, C.J., and Tennyson, M.E., 2015, Assessment of undiscovered oil and gas resources in the Uteland Butte Member of the Eocene Green River Formation, Uinta Basin, Utah: U.S. Geological Survey Fact Sheet 2015–3052, 2 p., https://dx.doi.org/10.3133/fs20153052.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065844","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438685,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VT1Q4H","text":"USGS data release","linkHelpText":"USGS National Assessment of Oil and Gas Project - Uteland Butte Assessment Units"},{"id":307707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3052/coverthb.jpg"},{"id":307708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3052/fs20153052.pdf","text":"Report","size":"1.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3052"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.80810546875,\n 41.590796851056005\n ],\n [\n -104.87548828125,\n 41.590796851056005\n ],\n [\n -104.78759765625,\n 37.43997405227057\n ],\n [\n -112.17041015625,\n 37.43997405227057\n ],\n [\n -112.25830078125,\n 41.16211393939692\n ],\n [\n -112.17041015625,\n 41.42625319507272\n ],\n [\n -110.80810546875,\n 41.590796851056005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
Three different geophysical sensor types were used to characterize the underwater pressure waves generated by the underwater firing of a seismic water gun and their suitability for establishing a pressure barrier to potentially direct or prevent the movement of the Asian carps. The sensors used to collect the seismic information were blast rated hydrophones and underwater blast sensors. Specific location information for the water guns and the sensors was obtained using either laser rangefinders or differentially corrected global positioning systems (GPS).
\nTwo separate studies are discussed in this report. The two studies were completed during September 2012 and July 2013. Both of these studies took place in an earthen testing pond on the campus of Upper Midwest Environmental Sciences Center (UMESC) in La Crosse, Wisconsin.
\nPrevious studies had identified 5 pounds per square inch (lb/in2) as a target value for the successful operation of a water gun barrier. The September 2012 study evaluated the performance of 1-cubic-inch (in3) and 80-in3 water guns. Data from the 1-in3 gun showed that it produces a very planar wave with limited effect on the depths above and below its gun ports. The 1-in3 gun did not produce the 5-lb/in2
\ntarget pressure at a sufficient distance to be considered effective. The 80-in3 gun produced a bowl-shaped pressure field with the 5-lb/in2 target radius at the surface extending to 45 feet.
\nThe July 2013 study consisted of three scenarios: fish behavior, single gun assessment, and experimental barrier evaluation. The fish behavior scenario simulated the pond conditions from previous studies. Two 80-in3 water guns were fired in the south end of the testing pond. Pressures essentially doubled from the testing of the single 80-in3 water gun. The single gun assessment scenario sought to replicate the setup of the 80-in3 scenario in September 2012, but with additional sensors to better define the pressure field. The 5-lb/in2 target pressure field continued to show a radius ranging from 40 to 45 feet, dependent on the pressure of the input air. The final scenario, the experimental barrier evaluation, showed that a two-dimensional continuous plane of 5 lb/in2 can be created between two 80-in3 water guns to a separation of 99 feet and a depth of 6.5 feet with 1,500 lb/in2 of input air.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151130","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Adams, R.F., and Morrow, W.S., 2015, Geophysical investigation of the pressure field produced by water guns at a pond site in La Crosse, Wisconsin: U.S. Geological Survey Open-File Report 2015–1130, 24 p., 1 app., https://dx.doi.org/10.3133/ofr20151130.","productDescription":"iv, 56 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-09-01","temporalEnd":"2013-07-31","ipdsId":"IP-053140","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":307792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1130/coverthb.jpg"},{"id":307793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1130/ofr20151130.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1130"}],"country":"United States","state":"Wisconsin","city":"La Crosse","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25677585601807,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.8665583482127\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
405 N. Goodwin
Urbana, IL 61801
(217) 328-8747
http://il.water.usgs.gov/
Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn—the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as ‘risk from turbines is highest in habitats between hoary bat summering and wintering grounds’. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0132599","collaboration":"Prepared in collaboration with University of Colorado Denver","usgsCitation":"Hayes, M.A., Cryan, P.M., and Wunder, M., 2015, Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development: PLoS ONE, v. 10, no. 7, e0132599; 20 p., https://doi.org/10.1371/journal.pone.0132599.","productDescription":"e0132599; 20 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1950-01-01","temporalEnd":"2000-12-31","ipdsId":"IP-066454","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0132599","text":"Publisher Index 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Determining the detailed movements of individual animals often requires them to carry tracking devices, but tracking broad-scale movement of small bats (< 30g) has been limited by transmitter technology and long-term attachment methods. This limitation inhibits our understanding of bat dispersal and migration, particularly in the context of emerging conservation issues like fatalities at wind turbines and diseases. 2. We tested a novel method of attaching lightweight global positioning system (GPS) tags and geolocating data loggers to small bats. We used monofilament, synthetic, absorbable sutures to secure GPS tags and data loggers to the skin of anesthetized big brown bats (Eptesicus fuscus) in Colorado and hoary bats (Lasiurus cinereus) in California. 3. GPS tags and data loggers were sutured to 17 bats in this study. Three tagged bats were recaptured seven months after initial deployment, with tags still attached; none of these bats showed ill effects from the tag. No severe injuries were apparent upon recapture of 6 additional bats that carried tags up to 26 days after attachment, however one of the bats exhibited skin chafing. 4. Use of absorbable sutures to affix small tracking devices seems to be a safe, effective method for studying movements of bats over multiple months, although additional testing is warranted. This new attachment method has the potential to quickly advance our understanding of small bats, particularly as more-sophisticated miniature tracking devices (e.g., satellite tags) become available.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1584","collaboration":"Prepared in cooperation with Wildlife Veterinary Consulting; U.S. Forest Service Pacific Southwest Research Station; Bat Conservation International","usgsCitation":"Castle, K.T., Weller, T.J., Cryan, P.M., Hein, C.D., and Schirmacher, M.R., 2015, Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies: Ecology and Evolution, v. 5, no. 14, p. 2980-2989, https://doi.org/10.1002/ece3.1584.","productDescription":"10 p.","startPage":"2980","endPage":"2989","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2014-08-01","temporalEnd":"2015-05-31","ipdsId":"IP-066197","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1584","text":"Publisher Index Page"},{"id":307915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-04","publicationStatus":"PW","scienceBaseUri":"55e9612ae4b0dacf699e7863","contributors":{"authors":[{"text":"Castle, Kevin T.","contributorId":90616,"corporation":false,"usgs":true,"family":"Castle","given":"Kevin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":571315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weller, Theodore J.","contributorId":105961,"corporation":false,"usgs":false,"family":"Weller","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":13261,"text":"USDA Forest Service, Pacific Southwest Research Station, Davis, California","active":true,"usgs":false}],"preferred":false,"id":571316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hein, Cris D.","contributorId":73910,"corporation":false,"usgs":false,"family":"Hein","given":"Cris","email":"","middleInitial":"D.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schirmacher, Michael R.","contributorId":76635,"corporation":false,"usgs":false,"family":"Schirmacher","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157006,"text":"70157006 - 2015 - Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","interactions":[],"lastModifiedDate":"2015-09-03T13:09:46","indexId":"70157006","displayToPublicDate":"2015-09-03T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","docAbstract":"Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.
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Earth Resources Observation and Science (EROS) Center
47914 252nd Street
Sioux Falls, SD 57198-0001
Long-term temporal trends in water temperature in rivers and streams are typically estimated under the assumption of evenly-spaced space-time measurements. However, sampling times and dates associated with historical water temperature datasets and some sampling designs may be haphazard. As a result, trends in temperature may be confounded with trends in time or space of sampling which, in turn, may yield biased trend estimators and thus unreliable conclusions. We address this concern using multilevel (hierarchical) linear models, where time effects are allowed to vary randomly by day and date effects by year. We evaluate the proposed approach by Monte Carlo simulations with imbalance, sparse data and confounding by trend in time and date of sampling. Simulation results indicate unbiased trend estimators while results from a case study of temperature data from the Illinois River, USA conform to river thermal assumptions. We also propose a new nonparametric bootstrap inference on multilevel models that allows for a relatively flexible and distribution-free quantification of uncertainties. The proposed multilevel modeling approach may be elaborated to accommodate nonlinearities within days and years when sampling times or dates typically span temperature extremes.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"Heidelberg, Germany","doi":"10.1007/s10260-015-0334-7","usgsCitation":"Gray, B.R., Lyubchich, V., Gel, Y.R., Rogala, J.T., Robertson, D.M., and Wei, X., 2015, Estimation of river and stream temperature trends under haphazard sampling: Statistical Methods & Applications, v. 25, no. 1, p. 89-105, https://doi.org/10.1007/s10260-015-0334-7.","productDescription":"27 p.","startPage":"89","endPage":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062819","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":323862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Illinois River","volume":"25","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-03","publicationStatus":"PW","scienceBaseUri":"57651f33e4b07657d19c7896","contributors":{"authors":[{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyubchich, Vyacheslav","contributorId":147780,"corporation":false,"usgs":false,"family":"Lyubchich","given":"Vyacheslav","email":"","affiliations":[{"id":12956,"text":"Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":572586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gel, Yulia R.","contributorId":147781,"corporation":false,"usgs":false,"family":"Gel","given":"Yulia","email":"","middleInitial":"R.","affiliations":[{"id":16934,"text":"Department of Mathematical Sciences, University of Texas at Dallas","active":true,"usgs":false}],"preferred":false,"id":572587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wei, Xiaoqiao","contributorId":147782,"corporation":false,"usgs":false,"family":"Wei","given":"Xiaoqiao","email":"","affiliations":[{"id":16935,"text":"3M Center, Saint Paul, MN","active":true,"usgs":false}],"preferred":false,"id":572590,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160535,"text":"70160535 - 2015 - Habitat, not resource availability, limits consumer production in lake ecosystems","interactions":[],"lastModifiedDate":"2015-12-22T15:34:21","indexId":"70160535","displayToPublicDate":"2015-09-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Habitat, not resource availability, limits consumer production in lake ecosystems","docAbstract":"Food web productivity in lakes can be limited by dissolved organic carbon (DOC), which reduces fish production by limiting the abundance of their zoobenthic prey. We demonstrate that in a set of 10 small, north temperate lakes spanning a wide DOC gradient, these negative effects of high DOC concentrations on zoobenthos production are driven primarily by availability of warm, well-oxygenated habitat, rather than by light limitation of benthic primary production as previously proposed. There was no significant effect of benthic primary production on zoobenthos production after controlling for oxygen, even though stable isotope analysis indicated that zoobenthos do use this resource. Mean whole-lake zoobenthos production was lower in high-DOC lakes with reduced availability of oxygenated habitat, as was fish biomass. These insights improve understanding of lake food webs and inform management in the face of spatial variability and ongoing temporal change in lake DOC concentrations.
","language":"English","publisher":"ASLO","doi":"10.1002/lno.10153","usgsCitation":"Craig, N., Jones, S., Weidel, B., and Solomon, C.T., 2015, Habitat, not resource availability, limits consumer production in lake ecosystems: Limnology and Oceanography, v. 60, no. 6, p. 2079-2089, https://doi.org/10.1002/lno.10153.","productDescription":"11 p.","startPage":"2079","endPage":"2089","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056993","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10153","text":"Publisher Index Page"},{"id":312745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin and Michigan","otherGeospatial":"University of Notre Dame Environmental Research Centre","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.56054687499999,\n 46.24397619106172\n ],\n [\n -89.39815521240234,\n 46.21737666278269\n ],\n [\n -89.4290542602539,\n 46.158194021968384\n ],\n [\n -89.59693908691406,\n 46.18672373121336\n ],\n [\n -89.56432342529297,\n 46.24350131252777\n ],\n [\n -89.56054687499999,\n 46.24397619106172\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-03","publicationStatus":"PW","scienceBaseUri":"567a823ce4b0a04ef490fcea","contributors":{"authors":[{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":583074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":583075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":583076,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155164,"text":"sir20155104 - 2015 - Flood-inundation Maps for the Deerfield River, Franklin County, Massachusetts, from the Confluence with the Cold River Tributary to the Connecticut River","interactions":[],"lastModifiedDate":"2015-11-04T12:23:52","indexId":"sir20155104","displayToPublicDate":"2015-09-02T14:00:00","publicationYear":"2015","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":"2015-5104","title":"Flood-inundation Maps for the Deerfield River, Franklin County, Massachusetts, from the Confluence with the Cold River Tributary to the Connecticut River","docAbstract":"The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 30-mile reach of the Deerfield River from the confluence of the Cold River tributary to the Connecticut River in the towns of Charlemont, Buckland, Shelburne, Conway, Deerfield, and Greenfield in Franklin County, Massachusetts to assist land owners, and emergency management workers prepare for and recover from floods. Peak flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using current [2015] stage-discharge relations at two U.S. Geological Survey streamgages in the study reach—Deerfield River at Charlemont, MA (01168500) and Deerfield River near West Deerfield, MA (01170000)—and from documented high-water marks from the tropical storm Irene flood, which had between a 1- and 0.2-percent AEP.
\nThe hydraulic model was used to compute water-surface profiles for flood stages referenced to the two streamgages. Two sets of flood-inundation map libraries were created from the modeled profiles. The library for the upstream, western portion of the modeled reach is 9.1 miles long, extends from just downstream of the confluence of the Deerfield River with the Cold River to just upstream of the confluence with Clesson Brook, and is calibrated to the Deerfield River at Charlemont, MA streamgage. The library for the downstream, eastern portion of the modeled reach is 8.9 miles long, extends from just downstream of the confluence of the Deerfield River with the South River to just upstream of the confluence with the Green River, and is calibrated to the Deerfield River near West Deerfield streamgage. Stages for mapped profiles of the upstream reach range from 8.7 feet (ft) at the local datum (525.6 ft when converted to the North American Vertical Datum of 1988 [NAVD 88]) to 25.7 ft (542.6 ft at NAVD 88) at the Charlemont streamgage, and stages for mapped profiles of the downstream reach range from 8.5 ft (165.2 ft at NAVD 88) to 29.0 ft (185.7 ft at NAVD 88) at the West Deerfield streamgage. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from 0.5-ft vertical accuracy light detection and ranging (lidar) data to create the two sets of flood-inundation maps.
\nThe availability of the flood-inundation maps at http://water.usgs.gov/osw/flood_inundation/, combined with information regarding current (near real-time) stage from the two U.S. Geological Survey streamgages in the study reach, can provide emergency management personnel and residents with information to aid in flood response activities, such as evacuations and road closures, and with postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155104","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Lombard, P.J., and Bent, G.C., 2015, Flood-inundation maps for the Deerfield River, Franklin County, Massachusetts, from the confluence with the Cold River tributary to the Connecticut River: U.S. Geological Survey Scientific Investigations Report 2015–5104, 22 p., appendixes, https://dx.doi.org/10.3133/sir20155104.","productDescription":"Report: vi, 22 p.; 2 Appendixes; Metadata","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061958","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":310302,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_flood-inundation_gis_charlemont.xml","text":"Charlemont flood inundation mapping GIS metadata (xml)","size":"12.3 KB","description":"SIR 2015-5104 - Metadata"},{"id":310303,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_flood-inundation_gis_wdeerfield.xml","text":"West Deerfield flood inundation mapping GIS metadata (xml)","size":"12.4 KB","description":"SIR 2015-5104 - Metadata"},{"id":310304,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_flood-inundation_gis_charlemont.zip","text":"Charlemont flood inundation mapping GIS","size":"27 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5104 - Spatial Data"},{"id":310305,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_flood-inundation_gis_wdeerfield.zip","text":"West Deerfield flood inundation mapping GIS","size":"85.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5104 - Spatial Data"},{"id":310306,"rank":10,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html","text":"Flood Inundation Mapper","linkFileType":{"id":5,"text":"html"},"description":"SIR 2015-5104"},{"id":307531,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_app2metadata.xml","text":"Appendix 2 Metadata (xml)","size":"12.4 KB","description":"SIR 2015-5104 - Metadata"},{"id":307527,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5104/sir20155104.pdf","text":"Report","size":"1.66MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5104"},{"id":307526,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5104/coverthb.jpg"},{"id":307536,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_appendix2.zip","text":"Appendix 2","size":"350 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5104 Appendix 2","linkHelpText":"Area of Flood Inundation for the 1- and 0.2-Percent Annual Exceedance Probability Flows Along the Deerfield River Study Reach in Franklin County, Massachusetts"},{"id":307528,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5104/downloads/sir20155104_appendix1.xlsx","text":"Appendix 1","size":"24 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5104 Appendix 1","linkHelpText":"Water-Surface Elevations at Modeled Cross Sections Along the Deerfield River, Franklin County, Massachusetts"}],"country":"United States","state":"Massachusetts","county":"Franklin County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.35870361328125,\n 42.72280375732727\n ],\n [\n -72.3175048828125,\n 42.6895017559477\n ],\n [\n -72.24746704101562,\n 42.67839711889057\n ],\n [\n -72.22824096679688,\n 42.65214190481525\n ],\n [\n -72.22137451171874,\n 42.622844161937174\n ],\n [\n -72.26943969726562,\n 42.60465241823049\n ],\n [\n -72.28179931640625,\n 42.589488572714245\n ],\n [\n -72.2625732421875,\n 42.56521874494336\n ],\n [\n -72.24746704101562,\n 42.527784255084676\n ],\n [\n -72.27630615234375,\n 42.50551526821832\n ],\n [\n -72.30926513671875,\n 42.533856237848504\n ],\n [\n -72.32162475585938,\n 42.47310984904908\n ],\n [\n -72.333984375,\n 42.453861188491175\n ],\n [\n -72.322998046875,\n 42.42244277484678\n ],\n [\n -72.32437133789062,\n 42.3839083919257\n ],\n [\n -72.32025146484375,\n 42.34941019930749\n ],\n [\n -72.34634399414061,\n 42.3179394544685\n ],\n [\n -72.34634399414061,\n 42.33926006673673\n ],\n [\n -72.35458374023438,\n 42.39912215986002\n ],\n [\n -72.38616943359375,\n 42.45791402988027\n ],\n [\n -72.38204956054688,\n 42.42142901536395\n ],\n [\n -72.4822998046875,\n 42.39506551565123\n ],\n [\n -72.50564575195312,\n 42.420415239489934\n ],\n [\n -72.79266357421875,\n 42.382894009614056\n ],\n [\n -72.80502319335938,\n 42.445754718858524\n ],\n [\n -72.94235229492188,\n 42.49133996306382\n ],\n [\n -72.93960571289062,\n 42.55510352893436\n ],\n [\n -73.06182861328125,\n 42.58544425738491\n ],\n [\n -73.10440063476562,\n 42.742978093466434\n ],\n [\n -72.35870361328125,\n 42.72280375732727\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at
http://newengland.water.usgs.gov
Coagulation with metal-based salts is a practice commonly employed by drinking-water utilities to decrease particle and dissolved organic carbon concentrations in water. In addition to decreasing dissolved organic carbon concentrations, the effectiveness of iron- and aluminum-based coagulants for decreasing dissolved concentrations both of inorganic and monomethyl mercury in water was demonstrated in laboratory studies that used agricultural drainage water from the Sacramento–San Joaquin Delta of California. To test the effectiveness of this approach at the field scale, nine 15-by-40‑meter wetland cells were constructed on Twitchell Island that received untreated water from island drainage canals (control) or drainage water treated with polyaluminum chloride or ferric sulfate coagulants. Surface-water samples were collected approximately monthly during November 2012–September 2013 from the inlets and outlets of the wetland cells and then analyzed by the U.S. Geological Survey for total concentrations of mercury and monomethyl mercury in filtered (less than 0.3 micrometers) and suspended-particulate fractions and for concentrations of dissolved organic carbon.
\nIn the control wetland cells, total mercury concentrations in filtered water samples ranged from 0.94 to 2.47 nanograms per liter (ng/L) at the control inlets and from 0.84 to 2.63 ng/L at the control outlets, and particulate total mercury concentrations in water ranged from 0.27 to 1.49 ng/L at the control inlets and from 0.17 to 1.11 ng/L at the control outlets. Monomethyl mercury concentrations in filtered water ranged from 0.16 to 0.88 ng/L at the control inlets and from 0.13 to 1.30 ng/L at the control outlets; particulate monomethyl mercury concentrations in water ranged from 0.03 to 0.24 ng/L at the control inlets and from 0.03 to 0.23 ng/L at the control outlets. Dissolved organic carbon concentrations in water ranged from 7.9 to 26.7 milligrams per liter at the control inlets and from 8.5 to 28.0 milligrams per liter at the control outlets.
\nFollowing coagulation, but prior to passage through the wetland cells, coagulation treatments transferred dissolved mercury and carbon to the particulate fraction relative to untreated source water: at the wetland cell inlets, the coagulation treatments decreased concentrations of filtered total mercury by 59–76 percent, filtered monomethyl mercury by 40–70 percent, and dissolved organic carbon by 65–86 percent. Passage through the wetland cells decreased the particulate fraction of mercury in wetland cells that received coagulant-treated water. Changes in total mercury, monomethyl mercury, and dissolved organic carbon concentrations resulting from wetland passage varied both by treatment and season. Despite increased monomethyl mercury in the filtered fraction during wetland passage between March and August, the coagulation-wetland systems generally decreased total mercury (filtered plus particulate) and monomethyl mercury (filtered plus particulate) concentrations relative to source water. Coagulation—either alone or in association with constructed wetlands—could be an effective way to decrease concentrations of mercury and dissolved organic carbon in surface water as well as the bioavailability of mercury in the Sacramento–San Joaquin Delta.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds950","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the California Department of Water Resources","usgsCitation":"Stumpner, E.B., Kraus, T.E.C., Fleck, J.A., Hansen, A.M., Bachand, S.M., Horwath, W.R., DeWild, J.F., Krabbenhoft, D.P., and Bachand, P.A.M., 2015, Mercury, monomethyl mercury, and dissolved organic carbon concentrations in surface water entering and exiting constructed wetlands treated with metal-based coagulants, Twitchell Island, California: U.S. Geological Survey Data Series 950, 26 p., https://dx.doi.org/10.3133/ds950.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064756","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":307801,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0950/ds950.pdf","text":"Report","size":"8.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 950"},{"id":307800,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0950/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Twitchell Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.66465759277344,\n 38.18584706613636\n ],\n [\n -121.69967651367188,\n 38.12969560730616\n ],\n [\n -121.70860290527342,\n 38.1080873807306\n ],\n [\n -121.68663024902344,\n 38.085391861792274\n ],\n [\n -121.63993835449219,\n 38.08485140639173\n ],\n [\n -121.59049987792969,\n 38.08809407886681\n ],\n [\n -121.56097412109375,\n 38.0907961960593\n ],\n [\n -121.55479431152344,\n 38.108627664321276\n ],\n [\n -121.55136108398436,\n 38.12861534784239\n ],\n [\n -121.51908874511717,\n 38.16641491595218\n ],\n [\n -121.49848937988281,\n 38.19232329797254\n ],\n [\n -121.48818969726561,\n 38.213906578463856\n ],\n [\n -121.48338317871094,\n 38.23656213571519\n ],\n [\n -121.497802734375,\n 38.267836780226276\n ],\n [\n -121.56509399414061,\n 38.24680876017446\n ],\n [\n -121.57882690429688,\n 38.21552506654349\n ],\n [\n -121.59805297851561,\n 38.19232329797254\n ],\n [\n -121.63169860839845,\n 38.18692647809604\n ],\n [\n -121.66465759277344,\n 38.18584706613636\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
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http://ca.water.usgs.gov
The presence of mercury (Hg), particularly methylmercury (MeHg), is a concern for both human and ecological health as MeHg is a neurotoxin and can bioaccumulate to lethal levels in upper trophic level organisms. Recent research has demonstrated that coagulation with metal-based salts can effectively remove both inorganic mercury (IHg) and MeHg from solution through association with dissolved organic matter (DOM) and subsequent flocculation and precipitation. In this study, we sought to further examine interactions between Hg and DOM and the resulting organo-metallic precipitate (floc) to assess if (1) newly added IHg could be removed to the same extent as ambient IHg or whether the association between IHg and DOM requires time, and (2) once formed, if the floc has the capacity to remove additional Hg from solution. Agricultural drainage water samples containing ambient concentrations of both DOM and IHg were spiked with a traceable amount of isotopically enriched IHg and dosed with ferric sulfate after 0, 1, 5, and 30 days. Both ambient and newly added IHg were removed within hours, with 69–79 % removed. To a separate sample set, isotopically enriched IHg was added to solution after floc had formed. Under those conditions, 81–95 % of newly added Hg was removed even at Hg concentrations 1000-fold higher than ambient levels. Results of this study indicate coagulation with ferric sulfate effectively removes both ambient and newly added IHg entering a system and suggests rapid association between IHg and DOM. This work also provides new information regarding the ability of floc to remove additional Hg from solution even after it has formed.
","language":"English","publisher":"Springer","publisherLocation":"New York, NY","doi":"10.1007/s00267-015-0601-2","usgsCitation":"Henneberry, Y.K., Kraus, T.E., Krabbenhoft, D.P., and Horwath, W., 2015, Investigating the temporal effects of metal-based coagulants to remove mercury from solution in the presence of dissolved organic matter: Environmental Management, v. 57, no. 1, p. 220-228, https://doi.org/10.1007/s00267-015-0601-2.","productDescription":"9 p.","startPage":"220","endPage":"228","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063553","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":308426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-02","publicationStatus":"PW","scienceBaseUri":"5603cd45e4b03bc34f544b15","contributors":{"authors":[{"text":"Henneberry, Yumiko K.","contributorId":66157,"corporation":false,"usgs":true,"family":"Henneberry","given":"Yumiko","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":573005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horwath, William R.","contributorId":37234,"corporation":false,"usgs":true,"family":"Horwath","given":"William R.","affiliations":[],"preferred":false,"id":573007,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156871,"text":"70156871 - 2015 - Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA","interactions":[],"lastModifiedDate":"2015-09-02T09:00:25","indexId":"70156871","displayToPublicDate":"2015-09-02T10:00:00","publicationYear":"2015","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":"Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA","docAbstract":"Understanding the efficacy of revised watershed management methods is important to mitigating the impacts of urbanization on streamflow. We evaluated the influence of land use change, primarily as urbanization, and stormwater control measures on the relationship between precipitation and stream discharge over an 8-year period for five catchments near Clarksburg, Montgomery County, Maryland, USA. A unit-hydrograph model based on a temporal transfer function was employed to account for and standardize temporal variation in rainfall pattern, and properly apportion rainfall to streamflow at different time lags. From these lagged relationships, we quantified a correction to the precipitation time series to achieve a hydrograph that showed good agreement between precipitation and discharge records. Positive corrections appeared to include precipitation events that were of limited areal extent and therefore not captured by our rain gages. Negative corrections were analysed for potential causal relationships. We used mixed-model statistical techniques to isolate different sources of variance as drivers that mediate the rainfall–runoff dynamic before and after management. Seasonal periodicity mediated rainfall–runoff relationships, and land uses (i.e. agriculture, natural lands, wetlands and stormwater control measures) were statistically significant predictors of precipitation apportionment to stream discharge. Our approach is one way to evaluate actual effectiveness of management efforts in the face of complicating circumstances and could be paired with cost data to understand economic efficiency or life cycle aspects of watershed management. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10505","usgsCitation":"Rhea, L., Jarnagin, T., Hogan, D.M., Loperfido, J., and Shuster, W., 2015, Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA: Hydrological Processes, v. 29, no. 20, p. 4413-4426, https://doi.org/10.1002/hyp.10505.","productDescription":"14 p.","startPage":"4413","endPage":"4426","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1998-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-053400","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":307802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Montgomery County","otherGeospatial":"Clarksburg","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.32315063476562,\n 39.17771552084858\n ],\n [\n -77.32315063476562,\n 39.32101883236063\n ],\n [\n -77.16865539550781,\n 39.32101883236063\n ],\n [\n -77.16865539550781,\n 39.17771552084858\n ],\n [\n -77.32315063476562,\n 39.17771552084858\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-11","publicationStatus":"PW","scienceBaseUri":"55e80f98e4b0dacf699e663a","chorus":{"doi":"10.1002/hyp.10505","url":"http://dx.doi.org/10.1002/hyp.10505","publisher":"Wiley-Blackwell","authors":"Rhea Lee, Jarnagin Taylor, Hogan Dianna, Loperfido J. 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The long-tailed duck adenovirus genome was approximately 27 kb. A 907 bp hexon gene segment was used to design primers specific for the long-tailed duck adenovirus. Nineteen isolates were phylogenetically characterized based on portions of their hexon gene and 12 were most closely related to Goose adenovirus A. The remaining 7 shared no hexon sequences with any known adenoviruses. Experimental infections of mallards with a long-tailed duck reference adenovirus caused mild lymphoid infiltration of the intestine and paint brush hemorrhages of the mucosa and dilation of the intestine. This study shows novel adenoviruses from long-tailed ducks are diverse and provides further evidence that they should be considered in cases of morbidity and mortality in sea ducks. Conserved and specific primers have been developed that will help screen sea ducks for adenoviral infections.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.virol.2015.07.026","usgsCitation":"Counihan, K., Skerratt, L., Franson, J.C., and Hollmen, T.E., 2015, Phylogenetic and pathogenic characterization of novel adenoviruses from long-tailed ducks (Clangula hyemalis): Virology, v. 485, p. 393-401, https://doi.org/10.1016/j.virol.2015.07.026.","productDescription":"9 p.","startPage":"393","endPage":"401","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063770","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.virol.2015.07.026","text":"Publisher Index Page"},{"id":310613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Prudhoe Bay, Simpson Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.064453125,\n 69.53451763078358\n ],\n [\n -142.294921875,\n 69.41124235697256\n ],\n [\n -145.283203125,\n 69.3493386397765\n ],\n [\n -149.501953125,\n 69.4421276134176\n ],\n [\n -154.423828125,\n 69.65708627301174\n ],\n [\n -158.02734375,\n 69.83962194067463\n ],\n [\n -160.3125,\n 69.99053495947655\n ],\n [\n -161.89453125,\n 70.31873847853122\n ],\n [\n -162.509765625,\n 70.81581215931348\n ],\n [\n -161.630859375,\n 72.15488958260748\n ],\n [\n -160.927734375,\n 72.99690914812648\n ],\n [\n -156.708984375,\n 73.35305494105975\n ],\n [\n -151.69921875,\n 73.62778879339942\n ],\n [\n -147.392578125,\n 73.65254484149818\n ],\n [\n -143.7890625,\n 73.80031816408652\n ],\n [\n -138.1640625,\n 74.49641311694307\n ],\n [\n -131.220703125,\n 75.54111255781133\n ],\n [\n -129.111328125,\n 75.49715731893085\n ],\n [\n -126.5625,\n 75.45307133006602\n ],\n [\n -125.771484375,\n 75.23066741281573\n ],\n [\n -125.24414062499999,\n 74.913708156753\n ],\n [\n -124.892578125,\n 74.44935750063425\n ],\n [\n -124.541015625,\n 74.23587806874863\n ],\n [\n -124.45312499999999,\n 73.89811065820952\n ],\n [\n -124.45312499999999,\n 73.30262420189155\n ],\n [\n -125.33203125,\n 72.58082870324515\n ],\n [\n -126.5625,\n 71.99257805093251\n ],\n [\n -128.671875,\n 71.21607526596131\n ],\n [\n -130.4296875,\n 70.55417853776078\n ],\n [\n -132.890625,\n 70.0205873017406\n ],\n [\n -134.912109375,\n 70.05059634999759\n ],\n [\n -136.31835937499997,\n 69.53451763078358\n ],\n [\n -138.1640625,\n 69.65708627301174\n ],\n [\n -139.5703125,\n 69.80930869552193\n ],\n [\n -140.537109375,\n 69.83962194067463\n ],\n [\n -141.064453125,\n 69.53451763078358\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"485","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562b5a31e4b00162522207da","contributors":{"authors":[{"text":"Counihan, Katrina","contributorId":140780,"corporation":false,"usgs":false,"family":"Counihan","given":"Katrina","affiliations":[{"id":13561,"text":"Alaska Sea Life Center, Seward, AK","active":true,"usgs":false}],"preferred":false,"id":546933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skerratt, Lee","contributorId":140781,"corporation":false,"usgs":false,"family":"Skerratt","given":"Lee","email":"","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":546934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":140358,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":546932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollmen, Tuula E.","contributorId":106077,"corporation":false,"usgs":true,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":546935,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159967,"text":"70159967 - 2015 - Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories","interactions":[],"lastModifiedDate":"2015-12-04T14:47:17","indexId":"70159967","displayToPublicDate":"2015-09-02T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories","docAbstract":"Maintaining the health of aquatic systems is an essential component of sustainable catchmentmanagement, however, degradation of water quality and aquatic habitat continues to challenge scientistsand policy-makers. To support management and restoration efforts aquatic system models are requiredthat are able to capture the often complex trajectories that these systems display in response to multiplestressors. This paper explores the abilities and limitations of current model approaches in meeting this chal-lenge, and outlines a strategy based on integration of flexible model libraries and data from observationnetworks, within a learning framework, as a means to improve the accuracy and scope of model predictions.The framework is comprised of a data assimilation component that utilizes diverse data streams from sensornetworks, and a second component whereby model structural evolution can occur once the model isassessed against theoretically relevant metrics of system function. Given the scale and transdisciplinarynature of the prediction challenge, network science initiatives are identified as a means to develop and inte-grate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to modelassessment that can guide model adaptation. We outline how such a framework can help us explore thetheory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry,and, in doing so, also advance the role of prediction in aquatic ecosystem management.
","language":"English","publisher":"Wiley","doi":"10.1002/2015WR017175","usgsCitation":"Hipsey, M., Hamilton, D., Hanson, P.C., Carey, C.C., Coletti, J.Z., Read, J.S., Ibelings, B.W., Valensini, F.J., and Brookes, J.D., 2015, Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories: Water Resources Research, v. 51, no. 9, p. 7023-7043, https://doi.org/10.1002/2015WR017175.","productDescription":"21 p.","startPage":"7023","endPage":"7043","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063945","costCenters":[],"links":[{"id":471816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017175","text":"Publisher Index Page"},{"id":311939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-02","publicationStatus":"PW","scienceBaseUri":"5662c758e4b06a3ea36c67c7","contributors":{"authors":[{"text":"Hipsey, Matthew R.","contributorId":80968,"corporation":false,"usgs":true,"family":"Hipsey","given":"Matthew R.","affiliations":[],"preferred":false,"id":581334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamilton, David P.","contributorId":18633,"corporation":false,"usgs":true,"family":"Hamilton","given":"David P.","affiliations":[],"preferred":false,"id":581335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":581336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":581337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coletti, Janaine Z","contributorId":150282,"corporation":false,"usgs":false,"family":"Coletti","given":"Janaine","email":"","middleInitial":"Z","affiliations":[{"id":17958,"text":"Aquatic Ecodynamics, School of Earth and Environment, The University of Western Australia, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":581338,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":581339,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ibelings, Bas W","contributorId":130973,"corporation":false,"usgs":false,"family":"Ibelings","given":"Bas","email":"","middleInitial":"W","affiliations":[{"id":7189,"text":"Institut F.A. Forel, Versoix, Switzerland","active":true,"usgs":false}],"preferred":false,"id":581340,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Valensini, Fiona J","contributorId":150283,"corporation":false,"usgs":false,"family":"Valensini","given":"Fiona","email":"","middleInitial":"J","affiliations":[{"id":17959,"text":"Centre for Fish and Fisheries Research, Murdoch University, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":581341,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brookes, Justin D","contributorId":130984,"corporation":false,"usgs":false,"family":"Brookes","given":"Justin","email":"","middleInitial":"D","affiliations":[{"id":7196,"text":"Water Research Centre, The Environment Institute, School of Earth and Environmental Science, University of Adelaide, South Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":581342,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70157313,"text":"70157313 - 2015 - Trimming the FAT for seafloor research in China—Constructing a tripod to monitor deep-sea sediment movement","interactions":[],"lastModifiedDate":"2015-09-21T14:05:49","indexId":"70157313","displayToPublicDate":"2015-09-01T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3363,"text":"Sea Technology","active":true,"publicationSubtype":{"id":10}},"title":"Trimming the FAT for seafloor research in China—Constructing a tripod to monitor deep-sea sediment movement","docAbstract":"Summarizes technical aspects of the Free Ascending Tripod for very deep water, designed by George Tate for joint US-China research lead by Jingping Xu in South China Sea.
","language":"English","publisher":"Compass Publications, Inc.","collaboration":"University of Tongji, Shanghai, China","usgsCitation":"West, A., 2015, Trimming the FAT for seafloor research in China—Constructing a tripod to monitor deep-sea sediment movement: Sea Technology, v. 56, no. 6, p. 38-40.","productDescription":"3 p.","startPage":"38","endPage":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061412","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":308318,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308317,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sea-technology.com/features/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"},"description":"Index Page"}],"otherGeospatial":"South China Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 117.99316406249999,\n 23.765236889758672\n ],\n [\n 121.11328124999999,\n 19.47695020648843\n ],\n [\n 117.94921874999999,\n 10.358151400943683\n ],\n [\n 112.236328125,\n 3.337953961416485\n ],\n [\n 109.072265625,\n 2.1088986592431382\n ],\n [\n 105.29296874999999,\n 7.841615185204699\n ],\n [\n 109.64355468749999,\n 11.824341483849048\n ],\n [\n 109.072265625,\n 16.04581345375218\n ],\n [\n 106.0400390625,\n 18.89589255941504\n ],\n [\n 107.22656249999999,\n 20.92039691397189\n ],\n [\n 108.45703125,\n 20.550508894195637\n ],\n [\n 108.67675781249999,\n 18.687878686034196\n ],\n [\n 110.830078125,\n 18.771115062337024\n ],\n [\n 110.9619140625,\n 20.673905264672843\n ],\n [\n 117.99316406249999,\n 23.765236889758672\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56012ab7e4b03bc34f54443d","contributors":{"authors":[{"text":"West, Amy awest@usgs.gov","contributorId":147791,"corporation":false,"usgs":true,"family":"West","given":"Amy","email":"awest@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":572667,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156006,"text":"fs20153054 - 2015 - Assessment of undiscovered oil and gas resources in the Cherokee Platform Province area of Kansas, Oklahoma, and Missouri, 2015","interactions":[],"lastModifiedDate":"2018-02-15T15:00:31","indexId":"fs20153054","displayToPublicDate":"2015-09-01T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3054","title":"Assessment of undiscovered oil and gas resources in the Cherokee Platform Province area of Kansas, Oklahoma, and Missouri, 2015","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean volumes of undiscovered, technically recoverable resources of 463 million barrels of oil, 11.2 trillion cubic feet of gas, and 35 million barrels of natural gas liquids in the Cherokee Platform Province area of Kansas, Oklahoma, and Missouri.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153054","collaboration":"Prepared in cooperation with National and Global Petroleum Assessment Project","usgsCitation":"Drake, R.M., II, Hatch, J.R., Schenk, C.J., Charpentier, R.R., Klett, T.R., Phuong, A.L., Leathers, H.M., Brownfield, M.E., Gaswirth, S.B., Marra, K.R., Pitman, J.K., Potter, C.J., Tennyson, M.E., 2015, Assessment of undiscovered oil and gas resources in the Cherokee Platform Province area of Kansas, Oklahoma, and Missouri, 2015: U.S. Geological Survey Fact Sheet 2015-3054, 2 p., https://dx.doi.org/10.3133/fs20153054.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065431","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438686,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PC30FK","text":"USGS data release","linkHelpText":"USGS National Assessment of Oil and Gas Project - Cherokee Platform Province Assessment Units"},{"id":307665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3054/fs20153054.pdf","text":"Report","size":"860 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3054"},{"id":307664,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3054/coverthb.jpg"}],"country":"United States","state":"Kansas, Oklahoma, Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.36035156249999,\n 33.99802726234877\n ],\n [\n -99.36035156249999,\n 39.01064750994083\n ],\n [\n -92.21923828124999,\n 39.01064750994083\n ],\n [\n -92.21923828124999,\n 33.99802726234877\n ],\n [\n -99.36035156249999,\n 33.99802726234877\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
Oil development in the Bakken shale region has increased rapidly as a result of new technologies and strong demand for fossil fuel. This region also supports a particularly high density and diversity of grassland bird species, which are declining across North America. We examined grassland bird response to unconventional oil extraction sites (i.e. developed with hydraulic fracturing and horizontal drilling techniques) and associated roads in North Dakota. Our goal was to quantify the amount of habitat that was indirectly degraded by oil development, as evidenced by patterns of avoidance by birds. Grassland birds avoided areas within 150 m of roads (95% CI: 87–214 m), 267 m of single-bore well pads (95% CI: 157–378 m), and 150 m of multi-bore well pads (95% CI: 67–233 m). Individual species demonstrated variable tolerance of well pads. Clay-colored sparrows (Spizella pallida) were tolerant of oil-related infrastructure, whereas Sprague's pipit (Anthus spragueii) avoided areas within 350 m (95% CI: 215–485 m) of single-bore well pads. Given these density patterns around oil wells, the potential footprint of any individual oil well, and oil development across the region, is greatly multiplied for sensitive species. Efforts to reduce new road construction, concentrate wells along developed corridors, combine numerous wells on multi-bore pads rather than build many single-bore wells, and to place well pads near existing roads will serve to minimize loss of suitable habitat for birds. Quantifying environmental degradation caused by oil development is a critical step in understanding how to better mitigate harm to wildlife populations.
","language":"English","publisher":"Elsevier","publisherLocation":"Kidlington, Oxford","doi":"10.1016/j.biocon.2015.08.040","usgsCitation":"Thompson, S.J., Johnson, D.H., Nieumuth, N., and Ribic, C., 2015, Avoidance of unconventional oil wells and roads exacerbates habitat loss for grassland birds in the North American great plains: Biological Conservation, v. 192, p. 82-90, https://doi.org/10.1016/j.biocon.2015.08.040.","productDescription":"9 p.","startPage":"82","endPage":"90","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061836","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":309375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"192","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560d07ace4b058f706e542f8","contributors":{"authors":[{"text":"Thompson, Sarah J. 0000-0002-5733-8198 sjthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-5733-8198","contributorId":5434,"corporation":false,"usgs":true,"family":"Thompson","given":"Sarah","email":"sjthompson@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":573445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":573446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nieumuth, Neal","contributorId":147951,"corporation":false,"usgs":false,"family":"Nieumuth","given":"Neal","email":"","affiliations":[{"id":16966,"text":"USFWS, HAPET Bismarck, ND","active":true,"usgs":false}],"preferred":false,"id":573447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":573448,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159317,"text":"70159317 - 2015 - Does natural variation in diversity affect biotic resistance?","interactions":[],"lastModifiedDate":"2022-08-01T13:56:29.275714","indexId":"70159317","displayToPublicDate":"2015-09-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Does natural variation in diversity affect biotic resistance?","docAbstract":"This publication has been retracted. See the retraction notice.
","language":"English","publisher":"British Ecological Society","publisherLocation":"Cambridge","doi":"10.1111/1365-2745.12439","usgsCitation":"Harrison, S., Cornell, H., and Grace, J.B., 2015, Does natural variation in diversity affect biotic resistance?: Journal of Ecology, v. 103, no. 5, p. 1099-1106, https://doi.org/10.1111/1365-2745.12439.","productDescription":"8 p.","startPage":"1099","endPage":"1106","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059408","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":471817,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.12439","text":"Publisher Index Page"},{"id":310290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5628b72fe4b0d158f5926c14","contributors":{"authors":[{"text":"Harrison, Susan","contributorId":85707,"corporation":false,"usgs":true,"family":"Harrison","given":"Susan","affiliations":[],"preferred":false,"id":577998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cornell, Howard","contributorId":149333,"corporation":false,"usgs":false,"family":"Cornell","given":"Howard","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":577999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":577997,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157226,"text":"70157226 - 2015 - Effects of flooding on ion exchange rates in an Upper Mississippi River floodplain forest impacted by herbivory, invasion, and restoration","interactions":[],"lastModifiedDate":"2015-09-16T11:38:54","indexId":"70157226","displayToPublicDate":"2015-09-01T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Effects of flooding on ion exchange rates in an Upper Mississippi River floodplain forest impacted by herbivory, invasion, and restoration","docAbstract":"We examined effects of flooding on supply rates of 14 nutrients in floodplain areas invaded by Phalaris arundinacea (reed canarygrass), areas restored to young successional forests (browsed by white-tailed deer and unbrowsed), and remnant mature forests in the Upper Mississippi River floodplain. Plant Root Simulator ion-exchange probes were deployed for four separate 28-day periods. The first deployment occurred during flooded conditions, while the three subsequent deployments were conducted during progressively drier periods. Time after flooding corresponded with increases in NO3 −-N, K+ and Zn+2, decreases in H2PO4 −-P, Fe+3, Mn+2, and B(OH)4-B, a decrease followed by an increase in NH4 +-N, Ca+2, Mg+2 and Al+3, and an increase followed by a decrease for SO4 −2-S. Plant community type had weak to no effects on nutrient supply rates compared to the stronger effects of flooding duration. Our results suggest that seasonal dynamics in floodplain nutrient availability are similarly driven by flood pulses in different community types. However, reed canarygrass invasion has potential to increase availability of some nutrients, while restoration of forest cover may promote recovery of nutrient availability to that observed in reference mature forests.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-015-0675-x","collaboration":"University of Wisconsin-La Crosse","usgsCitation":"Kreiling, R., De Jager, N.R., Swanson, W., Eric A. Strauss, and Meredith Thomsen, 2015, Effects of flooding on ion exchange rates in an Upper Mississippi River floodplain forest impacted by herbivory, invasion, and restoration: Wetlands, v. 35, no. 5, p. 1005-1012, https://doi.org/10.1007/s13157-015-0675-x.","productDescription":"8 p.","startPage":"1005","endPage":"1012","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063008","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":308202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-04","publicationStatus":"PW","scienceBaseUri":"55fa92b7e4b05d6c4e501a7e","contributors":{"authors":[{"text":"Kreiling, Rebecca 0000-0002-9295-4156 rkreiling@usgs.gov","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":147679,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","email":"rkreiling@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":572312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Whitney","contributorId":147680,"corporation":false,"usgs":false,"family":"Swanson","given":"Whitney","email":"","affiliations":[{"id":16896,"text":"Biology Department and River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":572313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eric A. Strauss","contributorId":147681,"corporation":false,"usgs":false,"family":"Eric A. Strauss","affiliations":[{"id":16896,"text":"Biology Department and River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":572314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meredith Thomsen","contributorId":147682,"corporation":false,"usgs":false,"family":"Meredith Thomsen","affiliations":[{"id":16896,"text":"Biology Department and River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":572315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157231,"text":"70157231 - 2015 - Climate change and physical disturbance cause similar community shifts in biological soil crusts","interactions":[],"lastModifiedDate":"2015-10-05T16:04:25","indexId":"70157231","displayToPublicDate":"2015-09-01T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and physical disturbance cause similar community shifts in biological soil crusts","docAbstract":"Biological soil crusts (biocrusts)—communities of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface—are fundamental components of drylands worldwide, and destruction of biocrusts dramatically alters biogeochemical processes, hydrology, surface energy balance, and vegetation cover. While there has been long-standing concern over impacts of 5 physical disturbances on biocrusts (e.g., trampling by livestock, damage from vehicles), there is also increasing concern over the potential for climate change to alter biocrust community structure. Using long-term data from the Colorado Plateau, USA, we examined the effects of 10 years of experimental warming and altered precipitation (in full-factorial design) on biocrust communities, and compared the effects of altered climate with those of long-term physical 10 disturbance (>10 years of replicated human trampling). Surprisingly, altered climate and physical disturbance treatments had similar effects on biocrust community structure. Warming, altered precipitation frequency [an increase of small (1.2 mm) summer rainfall events], and physical disturbance from trampling all promoted early successional community states marked by dramatic declines in moss cover and increased cyanobacteria cover, with more variable effects 15 on lichens. While the pace of community change varied significantly among treatments, our results suggest that multiple aspects of climate change will affect biocrusts to the same degree as physical disturbance. This is particularly disconcerting in the context of warming, as temperatures for drylands are projected to increase beyond those imposed by the climate treatments used in our study.
","language":"English","publisher":"National Academy of Sciences","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1509150112","usgsCitation":"Ferrenberg, S., Reed, S.C., and Belnap, J., 2015, Climate change and physical disturbance cause similar community shifts in biological soil crusts: PNAS, v. 112, no. 39, p. 12116-12121, https://doi.org/10.1073/pnas.1509150112.","productDescription":"6 p.","startPage":"12116","endPage":"12121","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066539","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471818,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1509150112","text":"External Repository"},{"id":308199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"39","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-14","publicationStatus":"PW","scienceBaseUri":"55fa92b1e4b05d6c4e501a60","contributors":{"authors":[{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572331,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}