Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0177467","usgsCitation":"Huntsman, B.M., Falke, J.A., Savereide, J.W., and Bennett, K.E., 2017, The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape: PLoS ONE, v. 12, no. 5, p. 1-21, https://doi.org/10.1371/journal.pone.0177467.","productDescription":"e0177467; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-077611","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":461565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0177467","text":"Publisher Index Page"},{"id":353885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River Basin","volume":"12","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-22","publicationStatus":"PW","scienceBaseUri":"5afee879e4b0da30c1bfc457","contributors":{"authors":[{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":734441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Katrina E.","contributorId":204592,"corporation":false,"usgs":false,"family":"Bennett","given":"Katrina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188608,"text":"70188608 - 2017 - Methane fluxes from tropical coastal lagoons surrounded bymangroves, Yucatán, Mexico","interactions":[],"lastModifiedDate":"2017-06-16T15:17:01","indexId":"70188608","displayToPublicDate":"2017-05-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Methane fluxes from tropical coastal lagoons surrounded bymangroves, Yucatán, Mexico","docAbstract":"Methane concentrations in the water column and emissions to the atmosphere were determined for three tropical coastal lagoons surrounded by mangrove forests on the Yucatán Peninsula, Mexico. Surface water dissolved methane was sampled at different seasons over a period of 2 years in areas representing a wide range of salinities and anthropogenic impacts. The highest surface water methane concentrations (up to 8378 nM) were measured in a polluted canal associated with Terminos Lagoon. In Chelem Lagoon, methane concentrations were typically lower, except in the polluted harbor area (1796 nM). In the relatively pristine Celestún Lagoon, surface water methane concentrations ranged from 41 to 2551 nM. Methane concentrations were negatively correlated with salinity in Celestún, while in Chelem and Terminos high methane concentrations were associated with areas of known pollution inputs, irrespective of salinity. The diffusive methane flux from surface lagoon water to the atmosphere ranged from 0.0023 to 15 mmol CH4 m−2 d−1. Flux chamber measurements revealed that direct methane release as ebullition was up to 3 orders of magnitude greater than measured diffusive flux. Coastal mangrove lagoons may therefore be an important natural source of methane to the atmosphere despite their relatively high salinity. Pollution inputs are likely to substantially enhance this flux. Additional statistically rigorous data collected globally are needed to better consider methane fluxes from mangrove-surrounded coastal areas in response to sea level changes and anthropogenic pollution in order to refine projections of future atmospheric methane budgets.
","language":"English","doi":"10.1002/2017JG003761","usgsCitation":"Chuang, P., Young, M.B., Dale, A.W., Miller, L., Herrera-Silveira, J.A., and Paytan, A., 2017, Methane fluxes from tropical coastal lagoons surrounded bymangroves, Yucatán, Mexico: Journal of Geophysical Research: Biogeosciences, v. 122, no. 5, p. 1156-1174, https://doi.org/10.1002/2017JG003761.","productDescription":"19 p. 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We explored whether environmental DNA (eDNA) analysis might prove useful for determining the species of salmon redds. We collected eDNA samples from the interstitial spaces of redds of Chinook Salmon Oncorhynchus tshawytscha, redds of Coho Salmon O. kisutch, and areas of undisturbed gravel (n = 10, each), as well as from the water column adjacent to each of those sites in the Sandy River basin, Oregon, USA during the fall of 2013. The concentrations of Chinook and Coho eDNA were quantified within each sample using real-time PCR. The water in the interstitial spaces of redds contained significantly higher eDNA concentrations of the species that made the redd than (1) the other species and (2) the adjacent water column. In contrast, neither Chinook nor Coho eDNA was significantly more concentrated than the other in the water from the interstitial spaces of undisturbed gravel. The interstitial water of undisturbed gravel contained significantly higher eDNA concentrations of Coho than the adjacent water column. In contrast, Chinook eDNA concentration was similar in the interstitial water of undisturbed gravel and the adjacent water column. Both species’ redds had significantly higher concentrations of their respective species’ eDNA than did undisturbed gravel, but conclusions were confounded by differences in the timing and locations of sampling. This initial investigation highlights the potential value and some of the complexity of using eDNA analysis to indicate redd species.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02755947.2017.1335254","collaboration":"Matthew B. 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Burke","contributorId":192862,"corporation":false,"usgs":false,"family":"Strobel","given":"Burke","email":"","affiliations":[],"preferred":false,"id":697933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":697932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":149254,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","email":"dpilliod@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":697931,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187794,"text":"70187794 - 2017 - Evaluating the impact of irrigation on surface water – groundwater interaction and stream temperature in an agricultural watershed","interactions":[],"lastModifiedDate":"2017-05-19T13:36:19","indexId":"70187794","displayToPublicDate":"2017-05-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of irrigation on surface water – groundwater interaction and stream temperature in an agricultural watershed","docAbstract":"Changes in groundwater discharge to streams caused by irrigation practices can influence stream temperature. Observations along two currently flood-irrigated reaches in the 640-square-kilometer upper Smith River watershed, an important agricultural and recreational fishing area in west-central Montana, showed a downstream temperature decrease resulting from groundwater discharge to the stream. A watershed-scale coupled surface water and groundwater flow model was used to examine changes in streamflow, groundwater discharge to the stream and stream temperature resulting from irrigation practices. The upper Smith River watershed was used to develop the model framework including watershed climate, topography, hydrography, vegetation, soil properties and current irrigation practices. Model results were used to compare watershed streamflow, groundwater recharge, and groundwater discharge to the stream for three scenarios: natural, pre-irrigation conditions (PreIrr); current irrigation practices involving mainly stream diversion for flood and sprinkler irrigation (IrrCurrent); and a hypothetical scenario with only groundwater supplying sprinkler irrigation (IrrGW). Irrigation increased groundwater recharge relative to natural PreIrr conditions because not all applied water was removed by crop evapotranspiration. Groundwater storage and groundwater discharge to the stream increased relative to natural PreIrr conditions when the source of irrigation water was mainly stream diversion as in the IrrCurrent scenario. The hypothetical IrrGW scenario, in which groundwater withdrawals were the sole source of irrigation water, resulted in widespread lowering of the water table and associated decreases in groundwater storage and groundwater discharge to the stream. A mixing analysis using model predicted groundwater discharge along the reaches suggests that stream diversion and flood irrigation, represented in the IrrCurrent scenario, has led to cooling of stream temperatures relative to natural PreIrr conditions improving fish thermal habitat. However, the decrease in groundwater discharge in the IrrGW scenario resulting from large-scale groundwater withdrawal for irrigation led to warmer than natural stream temperatures and possible degradation of fish habitat.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.04.205","usgsCitation":"Essaid, H.I., and Caldwell, R.R., 2017, Evaluating the impact of irrigation on surface water – groundwater interaction and stream temperature in an agricultural watershed: Science of the Total Environment, v. 599-600, p. 581-596, https://doi.org/10.1016/j.scitotenv.2017.04.205.","productDescription":"16 p.","startPage":"581","endPage":"596","ipdsId":"IP-083683","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.04.205","text":"Publisher Index Page"},{"id":341512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.324462890625,\n 46.027481852486645\n ],\n [\n -110.32470703125,\n 46.027481852486645\n ],\n [\n -110.32470703125,\n 46.73986059969267\n ],\n [\n -111.324462890625,\n 46.73986059969267\n ],\n [\n -111.324462890625,\n 46.027481852486645\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"599-600","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59200448e4b0ac16dbdeb77a","contributors":{"authors":[{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":695649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":695650,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187797,"text":"70187797 - 2017 - Thermal effect of climate change on groundwater-fed ecosystems","interactions":[],"lastModifiedDate":"2017-11-27T13:53:53","indexId":"70187797","displayToPublicDate":"2017-05-19T00:00:00","publicationYear":"2017","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":"Thermal effect of climate change on groundwater-fed ecosystems","docAbstract":"Groundwater temperature changes will lag surface temperature changes from a changing climate. Steady state solutions of the heat-transport equations are used to identify key processes that control the long-term thermal response of springs and other groundwater discharge to climate change, in particular changes in (1) groundwater recharge rate and temperature and (2) land-surface temperature transmitted through the vadose zone. Transient solutions are developed to estimate the time required for new thermal signals to arrive at ecosystems. The solution is applied to the volcanic Medicine Lake highlands, California, USA, and associated springs complexes that host groundwater-dependent ecosystems. In this system, upper basin groundwater temperatures are strongly affected only by recharge conditions. However, as the vadose zone thins away from the highlands, changes in the average annual land-surface temperature also influence groundwater temperatures. Transient response to temperature change depends on both the conductive time scale and the rate at which recharge delivers heat. Most of the thermal response of groundwater at high elevations will occur within 20 years of a shift in recharge temperatures, but the large lower elevation springs will respond more slowly, with about half of the conductive response occurring within the first 20 years and about half of the advective response to higher recharge temperatures occurring in approximately 60 years.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR020007","usgsCitation":"Burns, E.R., Zhu, Y., Zhan, H., Manga, M., Williams, C.F., Ingebritsen, S.E., and Dunham, J.B., 2017, Thermal effect of climate change on groundwater-fed ecosystems: Water Resources Research, v. 53, no. 4, p. 3341-3351, https://doi.org/10.1002/2016WR020007.","productDescription":"11 p.","startPage":"3341","endPage":"3351","ipdsId":"IP-078258","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":461585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr020007","text":"Publisher Index Page"},{"id":341520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.283333,\n 41.766667\n ],\n [\n -121.283333,\n 41.766667\n ],\n [\n -121.283333,\n 40.9\n ],\n [\n -122.283333,\n 40.9\n ],\n [\n -122.283333,\n 41.766667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"59200447e4b0ac16dbdeb776","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Yonghui 0000-0002-6608-5188","orcid":"https://orcid.org/0000-0002-6608-5188","contributorId":192155,"corporation":false,"usgs":false,"family":"Zhu","given":"Yonghui","email":"","affiliations":[],"preferred":false,"id":695658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhan, Hongbin 0000-0003-2060-4904","orcid":"https://orcid.org/0000-0003-2060-4904","contributorId":192156,"corporation":false,"usgs":false,"family":"Zhan","given":"Hongbin","email":"","affiliations":[],"preferred":false,"id":695659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manga, Michael","contributorId":145531,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":695660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":695661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":695662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":695663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187791,"text":"70187791 - 2017 - Estimated seepage rates from selected ditches, ponds, and lakes at the Camas National Wildlife Refuge, eastern Idaho","interactions":[],"lastModifiedDate":"2017-09-05T12:52:23","indexId":"70187791","displayToPublicDate":"2017-05-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimated seepage rates from selected ditches, ponds, and lakes at the Camas National Wildlife Refuge, eastern Idaho","docAbstract":"The Camas National Wildlife Refuge (Refuge) in eastern Idaho, established in 1937, contains wetlands, ponds, and wet meadows that are essential resting and feeding habitat for migratory birds and nesting habitat for waterfowl. Initially, natural sources of water supported these habitats. However, during the past few decades, changes in climate and surrounding land use have altered and reduced natural groundwater and surface-water inflows, resulting in a 5-meter decline in the water table and an earlier, and more frequent, occurrence of no flow in Camas Creek at the Refuge. Due to these changes in water availability, water management that includes extensive groundwater pumping is now necessary to maintain the wetlands, ponds, and wet meadows.
These water management activities have proven to be inefficient and expensive, and the Refuge is seeking alternative water-management options that are more efficient and less expensive. More efficient water management at the Refuge may be possible through knowledge of the seepage rates from ditches, ponds, and lakes at the Refuge. With this knowledge, water-management efficiency may be improved by natural means through selective use of water bodies with the smallest seepage rates or through engineering efforts to minimize seepage losses from water bodies with the largest seepage rates.
The U.S. Geological Survey performed field studies in 2015 and 2016 to estimate seepage rates for selected ditches, ponds, and lakes at the Refuge. Estimated seepage rates from ponds and lakes ranged over an order of magnitude, from 3.4 ± 0.2 to 103.0 ± 0.5 mm/d, with larger seepage rates calculated for Big Pond and Redhead Pond, intermediate seepage rates calculated for Two-way Pond, and smaller seepages rates calculated for the south arm of Sandhole Lake. Estimated seepage losses from two reaches of Main Diversion Ditch were 21 ± 2 and 17 ± 2 percent/km. These losses represent seepage rates of about 890 and 860 mm/d, which are one- to two-orders-of-magnitude larger than seepage rates from the ponds and lake.
The depth-integrated vertical hydraulic conductivity (Kv) for sediment underlying the ponds and lake was the primary control of seepage rates. The Kv's were 30 and 34 m/d for Big Pond, 14 and 18 m/d for Toomey Pond, 8 and 10 m/d for Two-way Pond, and 47 m/d for the north arm of Sandhole Lake.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.02.063","usgsCitation":"Rattray, G.W., 2017, Estimated seepage rates from selected ditches, ponds, and lakes at the Camas National Wildlife Refuge, eastern Idaho: Journal of Environmental Management, v. 203, no. 1, p. 578-591, https://doi.org/10.1016/j.jenvman.2017.02.063.","productDescription":"14 p.","startPage":"578","endPage":"591","ipdsId":"IP-083400","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":341508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Camas National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.24765777587889,\n 43.989603470452224\n ],\n [\n -112.2531509399414,\n 43.989603470452224\n ],\n [\n -112.25349426269531,\n 43.98589821991874\n ],\n [\n -112.2637939453125,\n 43.985774707584255\n ],\n [\n -112.26362228393555,\n 43.98206921804778\n ],\n [\n -112.25349426269531,\n 43.98219273809204\n ],\n [\n -112.2531509399414,\n 43.97873407971019\n ],\n [\n -112.25812911987305,\n 43.97836349721919\n ],\n [\n -112.25812911987305,\n 43.971074904863265\n ],\n [\n -112.26430892944336,\n 43.9711984477796\n ],\n [\n -112.2670555114746,\n 43.968356895686235\n ],\n [\n -112.2670555114746,\n 43.96551520764685\n ],\n [\n -112.26808547973633,\n 43.96514454266273\n ],\n [\n -112.27117538452148,\n 43.965268097914425\n ],\n [\n -112.27254867553711,\n 43.96625653067646\n ],\n [\n -112.27666854858398,\n 43.96613297748065\n ],\n [\n -112.27855682373045,\n 43.96477387536573\n ],\n [\n -112.29263305664062,\n 43.96514454266273\n ],\n [\n -112.29246139526367,\n 43.9576071863508\n ],\n [\n -112.30327606201172,\n 43.95773075727856\n ],\n [\n -112.30293273925781,\n 43.94302401260679\n ],\n [\n -112.29297637939453,\n 43.94277680933283\n ],\n [\n -112.29297637939453,\n 43.92843726069337\n ],\n [\n -112.3080825805664,\n 43.92843726069337\n ],\n [\n -112.3077392578125,\n 43.92497547227071\n ],\n [\n -112.31306076049803,\n 43.924851833243785\n ],\n [\n -112.31254577636719,\n 43.90655042390404\n ],\n [\n -112.30258941650389,\n 43.90667410096243\n ],\n [\n -112.30241775512695,\n 43.91038429322458\n ],\n [\n -112.28799819946289,\n 43.91026062387522\n ],\n [\n -112.28765487670898,\n 43.90667410096243\n ],\n [\n -112.28284835815428,\n 43.90655042390404\n ],\n [\n -112.28216171264647,\n 43.90296367743057\n ],\n [\n -112.27752685546875,\n 43.90321104619439\n ],\n [\n -112.2776985168457,\n 43.89962409851726\n ],\n [\n -112.24662780761719,\n 43.89925302263017\n ],\n [\n -112.24679946899414,\n 43.917309366668476\n ],\n [\n -112.24250793457031,\n 43.917309366668476\n ],\n [\n -112.2421646118164,\n 43.921018895951235\n ],\n [\n -112.22705841064453,\n 43.92077160119423\n ],\n [\n -112.22705841064453,\n 43.92769546584876\n ],\n [\n -112.2169303894043,\n 43.92806636442745\n ],\n [\n -112.2169303894043,\n 43.94079914613631\n ],\n [\n -112.22328186035156,\n 43.957483615166055\n ],\n [\n -112.24782943725586,\n 43.957854327949335\n ],\n [\n -112.24731445312499,\n 43.9788576066932\n ],\n [\n -112.24285125732422,\n 43.97836349721919\n ],\n [\n -112.24267959594727,\n 43.98206921804778\n ],\n [\n -112.22963333129883,\n 43.98206921804778\n ],\n [\n -112.23066329956055,\n 43.99306149560464\n ],\n [\n -112.24782943725586,\n 43.99306149560464\n ],\n [\n -112.24765777587889,\n 43.989603470452224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"203","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59200449e4b0ac16dbdeb77c","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695642,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187778,"text":"70187778 - 2017 - Effect of salinity on mercury methylating benthic microbes and their activities in Great Salt Lake, Utah","interactions":[],"lastModifiedDate":"2017-05-18T14:19:06","indexId":"70187778","displayToPublicDate":"2017-05-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Effect of salinity on mercury methylating benthic microbes and their activities in Great Salt Lake, Utah","docAbstract":"Surface water and biota from Great Salt Lake (GSL) contain some of the highest documented concentrations of total mercury (THg) and methylmercury (MeHg) in the United States. In order to identify potential biological sources of MeHg and controls on its production in this ecosystem, THg and MeHg concentrations, rates of Hg(II)-methylation and MeHg degradation, and abundances and compositions of archaeal and bacterial 16 rRNA gene transcripts were determined in sediment along a salinity gradient in GSL. Rates of Hg(II)-methylation were inversely correlated with salinity and were at or below the limits of detection in sediment sampled from areas with hypersaline surface water. The highest rates of Hg(II)-methylation were measured in sediment with low porewater salinity, suggesting that benthic microbial communities inhabiting less saline environments are supplying the majority of MeHg in the GSL ecosystem. The abundance of 16S rRNA gene transcripts affiliated with the sulfate reducer Desulfobacterium sp. was positively correlated with MeHg concentrations and Hg(II)-methylation rates in sediment, indicating a potential role for this taxon in Hg(II)-methylation in low salinity areas of GSL. Reactive inorganic Hg(II) (a proxy used for Hg(II) available for methylation) and MeHg concentrations were inversely correlated with salinity. Thus, constraints imposed by salinity on Hg(II)-methylating populations and the availability of Hg(II) for methylation are inferred to result in higher MeHg production potentials in lower salinity environments. Benthic microbial MeHg degradation was also most active in lower salinity environments. Collectively, these results suggest an important role for sediment anoxia and microbial sulfate reducers in the production of MeHg in low salinity GSL sub-habitats and may indicate a role for salinity in constraining Hg(II)-methylation and MeHg degradation activities by influencing the availability of Hg(II) for methylation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.12.157","usgsCitation":"Boyd, E., Yu, R., Barkay, T., Hamilton, T.L., Baxter, B.K., Naftz, D.L., and Marvin-DiPasquale, M., 2017, Effect of salinity on mercury methylating benthic microbes and their activities in Great Salt Lake, Utah: Science of the Total Environment, v. 581-582, p. 495-506, https://doi.org/10.1016/j.scitotenv.2016.12.157.","productDescription":"12 p.","startPage":"495","endPage":"506","ipdsId":"IP-080435","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":469838,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.12.157","text":"External Repository"},{"id":341480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.2415771484375,\n 40.60144147645398\n ],\n [\n -111.84356689453125,\n 40.60144147645398\n ],\n [\n -111.84356689453125,\n 41.75287318430239\n ],\n [\n -113.2415771484375,\n 41.75287318430239\n ],\n [\n -113.2415771484375,\n 40.60144147645398\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"581-582","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591eb2e1e4b0a7fdb4418b83","contributors":{"authors":[{"text":"Boyd, Eric S.","contributorId":192130,"corporation":false,"usgs":false,"family":"Boyd","given":"Eric S.","affiliations":[],"preferred":false,"id":695581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Ri-Qing","contributorId":192131,"corporation":false,"usgs":false,"family":"Yu","given":"Ri-Qing","email":"","affiliations":[],"preferred":false,"id":695582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barkay, Tamar","contributorId":192132,"corporation":false,"usgs":false,"family":"Barkay","given":"Tamar","email":"","affiliations":[],"preferred":false,"id":695583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamilton, Trinity L.","contributorId":192133,"corporation":false,"usgs":false,"family":"Hamilton","given":"Trinity","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":695584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baxter, Bonnie K.","contributorId":192134,"corporation":false,"usgs":false,"family":"Baxter","given":"Bonnie","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":695585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marvin-DiPasquale, Mark 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":149175,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":695580,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269685,"text":"70269685 - 2017 - Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States","interactions":[],"lastModifiedDate":"2025-07-31T13:22:08.551955","indexId":"70269685","displayToPublicDate":"2017-05-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States","docAbstract":"Remote sensing-based field-scale evapotranspiration (ET) maps are useful for characterizing water use patterns and assessing crop performance. The relative impact of climate variability and water management decisions are better studied and quantified using historical data that are derived using a set of consistent datasets and methodology. Historical (1984–2014) Landsat-based ET maps were generated for major irrigation districts in California, i.e., Palo Verde and eight other sub-basins in parts of the middle and lower Central Valley. A total of 3396 Landsat images were processed using the Operational Simplified Surface Energy Balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study sites over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively good correspondence (R2 up to 0.88, root mean square error as low as 14 mm/month) between SSEBop ET and validation datasets. In a pairwise comparison, annual variability of agro-hydrologic parameters of actual evapotranspiration (ETa), land surface temperature (Ts), and runoff (Q) were found to be more variable than their corresponding climatic counterparts of atmospheric water demand (ETo), air temperature (Ta), and precipitation (P), revealing process differences between regional climatic drivers and localized agro-hydrologic responses. However, only Ta showed a consistent increase (up to 1.2 K) over study sites during the 31 years, whereas other climate variables such as ETo and P showed a generally neutral trend. This study demonstrates a useful application of “Big Data” science where large volumes of historical Landsat and weather datasets were used to quantify and understand the relative importance of water management and climate variability in crop water use dynamics in regards to the linkages among water management decisions, hydrologic processes and economic transactions. Irrigation district-wide ETa estimates were used to compute historical crop water use volumes and monetary equivalents of water savings for the Palo Verde Irrigation District (PVID). During the peak crop fallowing year in PVID, the water saved reached a maximum of ~ 107,200 acre-feet in 2011 with an estimated monetary payout value of $20.5 million. A significant decreasing trend in actual ET despite an increasing atmospheric demand in PVID highlights the role of management decisions in affecting local hydrologic processes. This study has importance for planning water resource allocation, managing water rights, sustaining agricultural production, and quantifying impacts of climate and land use/land cover changes on water resources. With increased computational efficiency, similar studies can be conducted in other parts of the world to help policy and decision makers understand and quantify various aspects of water resources management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.05.005","usgsCitation":"Senay, G.B., Schauer, M., Friedrichs, M., Velpuri, N., and Singh, R., 2017, Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States: Remote Sensing of Environment, v. 202, p. 98-112, https://doi.org/10.1016/j.rse.2017.05.005.","productDescription":"15 p.","startPage":"98","endPage":"112","ipdsId":"IP-084512","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":493296,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.05.005","text":"Publisher Index Page"},{"id":493191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.40977836532282,\n 42.04933677309765\n ],\n [\n -123.16675091874134,\n 36.46673710104686\n ],\n [\n -118.58307879273526,\n 32.705501119947826\n ],\n [\n -113.73717874196483,\n 32.12914120007623\n ],\n [\n -113.88408063137007,\n 35.268837865873046\n ],\n [\n -114.8258516238531,\n 35.43740401775197\n ],\n [\n -117.48081678552326,\n 37.20400442230724\n ],\n [\n -120.03564230020528,\n 39.18700095919894\n ],\n [\n -120.18220374157768,\n 41.98136883976758\n ],\n [\n -125.40977836532282,\n 42.04933677309765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"202","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":944425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":216909,"corporation":false,"usgs":true,"family":"Schauer","given":"Matthew","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X mfriedrichs@usgs.gov","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":5847,"corporation":false,"usgs":true,"family":"Friedrichs","given":"MacKenzie","email":"mfriedrichs@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":944427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":216911,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga Manohar ","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Ramesh 0000-0002-8164-3483","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":210983,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944429,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188554,"text":"70188554 - 2017 - Arsenic and mercury contamination related to historical goldmining in the Sierra Nevada, California","interactions":[],"lastModifiedDate":"2017-06-23T16:05:05","indexId":"70188554","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1758,"text":"Geochemistry: Exploration, Environment, Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic and mercury contamination related to historical goldmining in the Sierra Nevada, California","docAbstract":"Arsenic (As) is a naturally occurring constituent in low-sulphide gold-quartz vein deposits, the dominant deposit type for lode mines in the Sierra Nevada Foothills (SNFH) gold (Au) province of California. Concentrations of naturally occurring mercury (Hg) in the SNFH Au province are low, but extensive use and loss of elemental Hg during amalgamation processing of ore from lode and placer Au deposits led to widespread contamination of Hg in the Sierra Nevada foothills and downstream areas, such as the Sacramento–San Joaquin Delta and San Francisco Bay. This review paper provides an overview of As and Hg contamination related to historical Au mining in the Sierra Nevada of California. It summarizes the geology, mineralogy, and geochemistry of the Au deposits, and provides information on specific areas where detailed studies have been done in association with past, ongoing, and planned remediation activities related to the environmental As and Hg contamination.
Arsenic is a naturally occurring constituent in low-sulphide Au-quartz vein deposits, the dominant deposit type for lode mines in the Sierra Nevada Foothills (SNFH) Au province (Ashley 2002). Because of elevated concentrations of As in accessory iron-sulphide minerals including arsenopyrite (FeAsS) and arsenian pyrite (Fe(S,As)2), As is commonly a contaminant of concern in lode Au mine waste, including waste rock and mill tailings. The principal pathways of human As exposure from mine waste include ingestion of soil or drinking water, and inhalation of dust in contaminated areas (Mitchell 2014).
Concentrations of naturally occurring Hg in the SNFH Au province are low, but extensive use and loss of elemental Hg during amalgamation processing of ore from lode and placer Au deposits (Churchill 2000) led to widespread contamination of Hg in the Sierra Nevada foothills and downstream areas, such as the Sacramento–San Joaquin Delta and San Francisco Bay (Alpers et al. 2005a). Conversion of Hg to monomethylmercury (MeHg) by sulphate-reducing and iron-reducing microbes facilitates its bioaccumulation (Wiener et al. 2003). The human Hg exposure pathway of main concern is ingestion of MeHg from sport (non-commercial) fish, especially higher trophic levels such as bass species (Davis et al. 2008). Wildlife exposure to MeHg is also a concern because of chronic and reproductive effects, for example in fish-eating and invertebrate-foraging birds (e.g. Wiener et al. 2003; Eagles-Smith et al. 2009; Ackerman et al. 2016).
The gut microbiome of herbivorous animals consists of organisms that efficiently digest the structural carbohydrates of ingested plant material. Green turtles (Chelonia mydas) provide an interesting model of change in these microbial communities because they undergo a pronounced shift from a surface-pelagic distribution and omnivorous diet to a neritic distribution and herbivorous diet. As an alternative to direct sampling of the gut, we investigated the cloacal microbiomes of juvenile green turtles before and after recruitment to neritic waters to observe any changes in their microbial community structure. Cloacal swabs were taken from individual turtles for analysis of the 16S rRNA gene sequences using Illumina sequencing. One fecal sample was also obtained, allowing for a preliminary comparison with the bacterial community of the cloaca. We found significant variation in the juvenile green turtle bacterial communities between pelagic and neritic habitats, suggesting that environmental and dietary factors support different bacterial communities in green turtles from these habitats. This is the first study to characterize the cloacal microbiome of green turtles in the context of their ontogenetic shifts, which could provide valuable insight into the origins of their gut bacteria and how the microbial community supports their shift to herbivory.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0177642","usgsCitation":"Price, J.T., Paladino, F.V., Lamont, M.M., Witherington, B.E., Bates, S.T., and Soule, T., 2017, Characterization of the juvenile green turtle (Chelonia mydas) microbiome throughout an ontogenetic shift from pelagic to neritic habitats: PLoS ONE, v. 12, no. 5, p. 1-13, https://doi.org/10.1371/journal.pone.0177642.","productDescription":"e0177642; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-078134","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469842,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0177642","text":"Publisher Index Page"},{"id":341390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.703125,\n 28\n ],\n [\n -84.7705078125,\n 28\n ],\n [\n -84.7705078125,\n 30.80791068136646\n ],\n [\n -90.703125,\n 30.80791068136646\n ],\n [\n -90.703125,\n 28\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-11","publicationStatus":"PW","scienceBaseUri":"591c0fc5e4b0a7fdb43ddee2","contributors":{"authors":[{"text":"Price, James T.","contributorId":192082,"corporation":false,"usgs":false,"family":"Price","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":695413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paladino, Frank V.","contributorId":192083,"corporation":false,"usgs":false,"family":"Paladino","given":"Frank","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":695414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":695412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witherington, Blair E.","contributorId":192084,"corporation":false,"usgs":false,"family":"Witherington","given":"Blair","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":695415,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bates, Scott T.","contributorId":138707,"corporation":false,"usgs":false,"family":"Bates","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":12503,"text":"University of Minnesota - Saint Paul","active":true,"usgs":false}],"preferred":false,"id":695416,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soule, Tanya","contributorId":192085,"corporation":false,"usgs":false,"family":"Soule","given":"Tanya","email":"","affiliations":[],"preferred":false,"id":695417,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187710,"text":"70187710 - 2017 - Habitat degradation affects the summer activity of polar bears","interactions":[],"lastModifiedDate":"2018-04-21T13:18:43","indexId":"70187710","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Habitat degradation affects the summer activity of polar bears","docAbstract":"Understanding behavioral responses of species to environmental change is critical to forecasting population-level effects. Although climate change is significantly impacting species’ distributions, few studies have examined associated changes in behavior. Polar bear (Ursus maritimus) subpopulations have varied in their near-term responses to sea ice decline. We examined behavioral responses of two adjacent subpopulations to changes in habitat availability during the annual sea ice minimum using activity data. Location and activity sensor data collected from 1989 to 2014 for 202 adult female polar bears in the Southern Beaufort Sea (SB) and Chukchi Sea (CS) subpopulations were used to compare activity in three habitat types varying in prey availability: (1) land; (2) ice over shallow, biologically productive waters; and (3) ice over deeper, less productive waters. Bears varied activity across and within habitats with the highest activity at 50–75% sea ice concentration over shallow waters. On land, SB bears exhibited variable but relatively high activity associated with the use of subsistence-harvested bowhead whale carcasses, whereas CS bears exhibited low activity consistent with minimal feeding. Both subpopulations had fewer observations in their preferred shallow-water sea ice habitats in recent years, corresponding with declines in availability of this substrate. The substantially higher use of marginal habitats by SB bears is an additional mechanism potentially explaining why this subpopulation has experienced negative effects of sea ice loss compared to the still-productive CS subpopulation. Variability in activity among, and within, habitats suggests that bears alter their behavior in response to habitat conditions, presumably in an attempt to balance prey availability with energy costs.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-017-3839-y","usgsCitation":"Ware, J.V., Rode, K.D., Bromaghin, J.F., Douglas, D.C., Wilson, R.H., Regehr, E.V., Amstrup, S.C., Durner, G.M., Pagano, A.M., Olson, J., Robbins, C.T., and Jansen, H.T., 2017, Habitat degradation affects the summer activity of polar bears: Oecologia, v. 184, no. 1, p. 87-99, https://doi.org/10.1007/s00442-017-3839-y.","productDescription":"13 p.","startPage":"87","endPage":"99","ipdsId":"IP-073535","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438339,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B27SCH","text":"USGS data release","linkHelpText":"Summer Activity Sensor Data from Collars Deployed on Female Polar Bears in the Chukchi Sea 1989 to 1995 and Southern Beaufort Sea 1989 to 2014"},{"id":341342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Chukchi Sea, Southern Beaufort Sea","volume":"184","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-28","publicationStatus":"PW","scienceBaseUri":"591c0fc8e4b0a7fdb43ddeea","contributors":{"authors":[{"text":"Ware, Jasmine V.","contributorId":192039,"corporation":false,"usgs":false,"family":"Ware","given":"Jasmine","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":695205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":695208,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":695209,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":695210,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695211,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695212,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Olson, Jay","contributorId":150116,"corporation":false,"usgs":false,"family":"Olson","given":"Jay","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":695213,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robbins, Charles T.","contributorId":124585,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":695214,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jansen, Heiko T","contributorId":192040,"corporation":false,"usgs":false,"family":"Jansen","given":"Heiko","email":"","middleInitial":"T","affiliations":[],"preferred":false,"id":695215,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70187709,"text":"70187709 - 2017 - Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios","interactions":[],"lastModifiedDate":"2017-11-10T14:27:56","indexId":"70187709","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios","docAbstract":"In large-scale conservation decisions, scenario planning identifies key uncertainties of ecosystem function linked to ecological drivers affected by management, incorporates ecological feedbacks, and scales up to answer questions robust to alternative futures. Wetland restoration planning requires an understanding of how proposed changes in surface hydrology, water storage, and landscape connectivity affect aquatic animal composition, productivity, and food-web function. In the Florida Everglades, reintroduction of historical hydrologic patterns is expected to increase productivity of all trophic levels. Highly mobile indicator species such as wading birds integrate secondary productivity from aquatic prey (small fishes and crayfish) over the landscape. To evaluate how fish, crayfish, and wading birds may respond to alternative hydrologic restoration plans, we compared predicted small fish density, crayfish density and biomass, and wading bird occurrence for existing conditions to four restoration scenarios that varied water storage and removal of levees and canals (i.e. decompartmentalization). Densities of small fish and occurrence of wading birds are predicted to increase throughout most of the Everglades under all restoration options because of increased flows and connectivity. Full decompartmentalization goes furthest toward recreating hypothesized historical patterns of fish density by draining excess water ponded by levees and hydrating areas that are currently drier than in the past. In contrast, crayfish density declined and species composition shifted under all restoration options because of lengthened hydroperiods (i.e. time of inundation). Under full decompartmentalization, the distribution of increased prey available for wading birds shifted south, closer to historical locations of nesting activity in Everglades National Park.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12518","usgsCitation":"Beerens, J.M., Trexler, J.C., and Catano, C.P., 2017, Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios: Restoration Ecology, v. 25, no. S1, p. S86-S98, https://doi.org/10.1111/rec.12518.","productDescription":"13 p.","startPage":"S86","endPage":"S98","ipdsId":"IP-070475","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://onlinelibrary.wiley.com/doi/10.1111/rec.12518/abstract","text":"External Repository"},{"id":341344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"S1","publicComments":"Special Issue: Synthesis of Everglades research and ecosystem services (SERES) project","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-10","publicationStatus":"PW","scienceBaseUri":"591c0fc8e4b0a7fdb43ddeec","contributors":{"authors":[{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":695201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":695202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catano, Christopher P.","contributorId":138935,"corporation":false,"usgs":false,"family":"Catano","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":695203,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187134,"text":"sir20175023 - 2017 - U.S. Geological Survey Karst Interest Group Proceedings, San Antonio, Texas, May 16–18, 2017","interactions":[],"lastModifiedDate":"2025-03-06T13:23:23.159237","indexId":"sir20175023","displayToPublicDate":"2017-05-15T09:15:00","publicationYear":"2017","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":"2017-5023","title":"U.S. Geological Survey Karst Interest Group Proceedings, San Antonio, Texas, May 16–18, 2017","docAbstract":"Karst aquifer systems are present throughout parts of the United States and some of its territories, and have developed in carbonate rocks (primarily limestone and dolomite) and evaporites (gypsum, anhydrite, and halite) that span an interval of time encompassing more than 550 million years. The depositional environments, diagenetic processes, post-depositional tectonic events, and geochemical weathering processes that form karst aquifers are varied and complex. These factors involve biological, chemical, and physical changes that when combined with the diverse climatic regimes in which karst development has taken place, result in the unique dual- or triple-porosity nature of karst aquifers. These complex hydrogeologic systems typically represent challenging and unique conditions to scientists attempting to study groundwater flow and contaminant transport in these terrains.
The dissolution of carbonate rocks and the subsequent development of distinct and beautiful landscapes, caverns, and springs have resulted in the most exceptional karst areas being designated as national or state parks. Tens of thousands of similar areas in the United States have been developed into commercial caverns and known privately owned caves. Both public and private properties provide access for scientists to study the flow of groundwater in situ. Likewise, the range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than for any other aquifer type. Karst aquifers and landscapes that form in tropical areas, such as the cockpit karst along the north coast of Puerto Rico, differ greatly from karst landforms in more arid climates, such as the Edwards Plateau in west-central Texas or the Guadalupe Mountains near Carlsbad, New Mexico, where hypogenic processes have played a major role in speleogenesis. Many of these public and private lands also contain unique flora and fauna associated with these karst hydrogeologic systems. As a result, numerous federal, state, and local agencies have a strong interest in the study of karst terrains.
Many of the major springs and aquifers in the United States have developed in carbonate rocks, such as the Floridan aquifer system in Florida and parts of Alabama, Georgia, and South Carolina; the Ozark Plateaus aquifer system in parts of Arkansas, Kansas, Missouri, and Oklahoma; and the Edwards-Trinity aquifer system in west-central Texas. These aquifers, and the springs that discharge from them, serve as major water-supply sources and form unique ecological habitats. Competition for the water resources of karst aquifers is common, and urban development and the lack of attenuation of contaminants in karst areas due to dissolution features that form direct pathways into karst aquifers can impact the ecosystem and water quality associated with these aquifers.
The concept for developing a platform for interaction among scientists within the U.S. Geological Survey (USGS) working on karst-related studies evolved from the November 1999 National Groundwater Meeting of the USGS. As a result, the Karst Interest Group (KIG) was formed in 2000. The KIG is a loose-knit, grass-roots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst science. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. Additionally, the KIG encourages collaborative studies between the different mission areas of the USGS as well as with other federal and state agencies, and with researchers from academia and institutes.
To accomplish its mission, the KIG has organized a series of workshops that have been held near nationally important karst areas. To date (2017) seven KIG workshops, including the workshop documented in this report, have been held. The workshops typically include oral and poster sessions on selected karst-related topics and research, as well as field trips to local karst areas. To increase non-USGS participation an effort was made for the workshops to be held at a university or institute beginning with the fourth workshop. Proceedings of the workshops are published by the USGS and are available online at the USGS publications warehouse https://pubs.er.usgs.gov/ by using the search term “karst interest group.”
The first KIG workshop was held in St. Petersburg, Florida, in 2001, in the vicinity of the large springs and other karst features of the Floridan aquifer system. The second KIG workshop was held in 2002, in Shepherdstown, West Virginia, in proximity to the carbonate aquifers of the northern Shenandoah Valley, and highlighted an invited presentation on karst literature by the late Barry F. Beck of P.E. LaMoreaux and Associates. The third KIG workshop was held in 2005, in Rapid City, South Dakota, near evaporite karst features in limestones of the Madison Group in the Black Hills of South Dakota. The Rapid City KIG workshop included field trips to Wind Cave National Park and Jewel Cave National Monument, and featured a presentation by Thomas Casadevall, then USGS Central Region Director, on the status of Earth science at the USGS.
The fourth KIG workshop in 2008 was hosted by the Hoffman Environmental Research Institute and Center for Cave and Karst Studies at Western Kentucky University in Bowling Green, Kentucky, near Mammoth Cave National Park and karst features of the Chester Upland and Pennyroyal Plateau. The workshop featured a late-night field trip into Mammoth Cave led by Rickard Toomey and Rick Olsen, National Park Service. The fifth KIG workshop in 2011 was a joint meeting of the USGS KIG and University of Arkansas HydroDays, hosted by the Department of Geosciences at the University of Arkansas in Fayetteville. The workshop featured an outstanding field trip to the unique karst terrain along the Buffalo National River in the southern Ozarks, and a keynote presentation on paleokarst in the United States was delivered by Art and Peggy Palmer. The sixth KIG workshop was hosted by the National Cave and Karst Research Institute (NCKRI) in 2014, in Carlsbad, New Mexico. George Veni, Director of the NCKRI, served as a co-chair of the workshop with Eve Kuniansky of the USGS. The workshop featured speaker Dr. Penelope Boston, Director of Cave and Karst Studies at New Mexico Tech, Socorro, and Academic Director at the NCKRI, who addressed the future of karst research. The field trip on evaporite karst of the lower Pecos Valley was led by Lewis Land (NCKRI karst hydrologist), and the field trip on the geology of Carlsbad Caverns National Park was led by George Veni.
This current seventh KIG workshop is being held in San Antonio at the University of Texas at San Antonio (UTSA). This 2017 workshop is being hosted by the Department of Geological Sciences’ Student Geological Society (SGS), and student chapters of the American Association of Petroleum Geologists (AAPG) and Association of Engineering Geologists (AEG), with support by the UTSA Department of Geological Sciences and Center for Water Research. The UTSA student chapter presidents, Jose Silvestre (SGS), John Cooper (AAPG), and Tyler Mead (AEG) serve as co-chairs of the 2017 workshop with Eve Kuniansky of the USGS. The technical session committee is chaired by Eve Kuniansky, USGS, and includes Michael Bradley, Tom Byl, Rebecca Lambert, John Lane, and James Kaufmann, all USGS, and Patrick Tucci, retired USGS. The logistics committee includes Amy Clark, Yongli Gao, and Lance Lambert (Department Chair), UTSA Department of Geological Sciences; and Ryan Banta and Allan Clark, USGS, San Antonio, Texas. The field trip committee is chaired by Allan Clark and includes Amy Clark, Yongli Gao, and Keith Muehlestein, UTSA; Marcus Gary, Edwards Aquifer Authority and University of Texas at Austin; Ron Green, Southwest Research Institute; Geary Schindel, Edwards Aquifer Authority; and George Veni, NCKRI. Additionally, two organizations have assisted the UTSA student chapters in hosting the meeting by donating funds to the chapters: the Edwards Aquifer Authority, San Antonio, Texas, and the Barton Springs Edwards Aquifer Authority, Austin, Texas. Additionally, Yongli Gao, Center for Water Research and Department of Geological Sciences, UTSA, helped develop sessions on cave and karst research in China for this workshop. These proceedings could not have been accomplished without the assistance of Lawrence E. Spangler as co-editor who not only has subject matter expertise, but also serves as an editor with the USGS Science Publishing Network. We sincerely hope that this workshop continues to promote future collaboration among scientists of varied and diverse backgrounds, and improves our understanding of karst aquifer systems in the United States and its territories.
The extended abstracts of USGS authors were peer reviewed and approved for publication by the USGS. Articles submitted by university researchers and other federal and state agencies did not go through the formal USGS peer review and approval process, and therefore may not adhere to USGS editorial standards or stratigraphic nomenclature. However, all articles had a minimum of two peer reviews and were edited for consistency of appearance in the proceedings. The use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The USGS Water Availability and Use Science Program funded the publication costs of the proceedings.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175023","collaboration":"Prepared in cooperation with the Department of Geological Sciences at the University of Texas at San Antonio and hosted by the Student Geological Society and student chapters of the Association of Petroleum Geologists and the Association of Engineering Geologists","usgsCitation":"Kuniansky, E.L., and Spangler, L.E., eds., 2017, U.S. Geological Survey Karst Interest Group Proceedings, San Antonio, Texas, May 16–18, 2017: U.S. Geological Survey Scientific Investigations Report 2017–5023, 245 p., https://doi.org/10.3133/sir20175023.","productDescription":"iv, 245 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080449","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":340331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5023/coverthb2.jpg"},{"id":340332,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5023/sir20175023.pdf","text":"Report","size":"8.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5023"},{"id":438341,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DZ06H6","text":"USGS data release","linkHelpText":"Data Rease for \"Isotopic constraints on middle Pleistocene cave evolution, paleohydrologic flow, and environmental conditions from Fitton Cave speleothems, Buffalo National River, Arkansas\""}],"contact":"Water Mission Area
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Tri-axial accelerometers have been used to remotely identify the behaviors of a wide range of taxa. Assigning behaviors to accelerometer data often involves the use of captive animals or surrogate species, as their accelerometer signatures are generally assumed to be similar to those of their wild counterparts. However, this has rarely been tested. Validated accelerometer data are needed for polar bears Ursus maritimus to understand how habitat conditions may influence behavior and energy demands. We used accelerometer and water conductivity data to remotely distinguish 10 polar bear behaviors. We calibrated accelerometer and conductivity data collected from collars with behaviors observed from video-recorded captive polar bears and brown bears U. arctos, and with video from camera collars deployed on free-ranging polar bears on sea ice and on land. We used random forest models to predict behaviors and found strong ability to discriminate the most common wild polar bear behaviors using a combination of accelerometer and conductivity sensor data from captive or wild polar bears. In contrast, models using data from captive brown bears failed to reliably distinguish most active behaviors in wild polar bears. Our ability to discriminate behavior was greatest when species- and habitat-specific data from wild individuals were used to train models. Data from captive individuals may be suitable for calibrating accelerometers, but may provide reduced ability to discriminate some behaviors. The accelerometer calibrations developed here provide a method to quantify polar bear behaviors to evaluate the impacts of declines in Arctic sea ice.
","language":"English","publisher":"Inter Research","doi":"10.3354/esr00779","usgsCitation":"Pagano, A.M., Rode, K.D., Cutting, A., Owen, M., Jensen, S., Ware, J., Robbins, C., Durner, G.M., Atwood, T.C., Obbard, M., Middel, K., Thiemann, G., and Williams, T., 2017, Using tri-axial accelerometers to identify wild polar bear behaviors: Endangered Species Research, v. 32, p. 19-33, https://doi.org/10.3354/esr00779.","productDescription":"15 p.","startPage":"19","endPage":"33","ipdsId":"IP-075328","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00779","text":"Publisher Index 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Pullman","active":true,"usgs":false}],"preferred":false,"id":695226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695228,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Obbard, M.E.","contributorId":192049,"corporation":false,"usgs":false,"family":"Obbard","given":"M.E.","email":"","affiliations":[{"id":33441,"text":"Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Trent University, Peterborough, ON, Canada","active":true,"usgs":false}],"preferred":false,"id":695229,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Middel, K.R.","contributorId":192050,"corporation":false,"usgs":false,"family":"Middel","given":"K.R.","email":"","affiliations":[{"id":33441,"text":"Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Trent University, Peterborough, ON, Canada","active":true,"usgs":false}],"preferred":false,"id":695230,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Thiemann, G.W.","contributorId":192051,"corporation":false,"usgs":false,"family":"Thiemann","given":"G.W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":695231,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, T.M.","contributorId":192052,"corporation":false,"usgs":false,"family":"Williams","given":"T.M.","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":695232,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70187689,"text":"70187689 - 2017 - Challenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010","interactions":[],"lastModifiedDate":"2017-08-22T16:44:26","indexId":"70187689","displayToPublicDate":"2017-05-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010","docAbstract":"Hydrologic budgets to determine groundwater availability are important tools for water-resource managers. One challenging component for developing hydrologic budgets is quantifying water use through time because historical and site-specific water-use data can be sparse or poorly documented. This research developed a groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010 that related county-level aggregated water-use data to site-specific well locations and aquifer units. A simple population-based linear model, constrained to 0 million liters per day in 1900, provided the best means to extrapolate groundwater-withdrawal rates pre-1950s when there was a paucity of water-use data. To disaggregate county-level data to individual wells across a regional aquifer system, a programmatic hierarchical process was developed, based on the level of confidence that a well pumped groundwater for a specific use during a specific year. Statistical models tested on a subset of the best-available site-specific water-use data provided a mechanism to bracket historic groundwater use, such that groundwater-withdrawal rates ranged, on average, plus or minus 38% from modeled values. Groundwater withdrawn for public supply and domestic use accounted for between 48 and 74% of total groundwater use since 1901, highlighting that groundwater provides an important drinking-water resource. The compilation, analysis, and spatial and temporal extrapolation of water-use data remain a challenging task for water scientists, but is of paramount importance to better quantify groundwater use and availability.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-017-1593-1","usgsCitation":"Knierim, K.J., Nottmeier, A.M., Worland, S.C., Westerman, D.A., and Clark, B.R., 2017, Challenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010: Hydrogeology Journal, v. 25, no. 6, p. 1779-1793, https://doi.org/10.1007/s10040-017-1593-1.","productDescription":"15 p.","startPage":"1779","endPage":"1793","ipdsId":"IP-078969","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469848,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-017-1593-1","text":"Publisher Index Page"},{"id":438343,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GQ6VV1","text":"USGS data release","linkHelpText":"Groundwater withdrawal rates from the Ozark Plateaus aquifer system, 1900 to 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Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westerman, Drew A. 0000-0002-8522-776X dawester@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-776X","contributorId":4526,"corporation":false,"usgs":true,"family":"Westerman","given":"Drew","email":"dawester@usgs.gov","middleInitial":"A.","affiliations":[{"id":129,"text":"Arkansas Water Science 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States","interactions":[],"lastModifiedDate":"2017-05-24T10:05:54","indexId":"70187690","displayToPublicDate":"2017-05-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5397,"text":"Geoderma Regional","active":true,"publicationSubtype":{"id":10}},"title":"Carbon cycling in the mantled karst of the Ozark Plateaus, central United States","docAbstract":"The nature of carbon (C) cycling in the unsaturated zone where groundwater is in contact with abundant gas-filled voids is poorly understood. The objective of this study was to trace inorganic-C cycling in a karst landscape using stable-C isotopes, with emphasis on a shallow groundwater flow path through the soil, to an underlying cave, and to the spring outlet of a cave stream in the Ozark Plateaus of northwestern Arkansas. Carbon dioxide (CO2) concentration and isotopic composition (δ13C-CO2) in gas and dissolved inorganic carbon (DIC) concentration and isotopic composition (δ13C-DIC) in water were measured in samples collected from two suction-cup soil samplers above the cave, three sites in the cave, and at the spring outlet of the cave stream. Soil-gas CO2 concentration (median 2,578 ppm) and δ13C-CO2 (median − 21.5‰) were seasonally variable, reflecting the effects of surface temperature changes on soil-CO2 production via respiration and organic-matter decomposition. Cave-air CO2 (median 1,026 ppm) was sourced from the soil zone and the surface atmosphere, with seasonally changing proportions of each source controlled by surface temperature-driven air density gradients. Soil-DIC concentration (median 1.7 mg L− 1) was lower and soil-δ13C-DIC (median − 19.5‰) was lighter compared to the cave (median 23.3 mg L− 1 and − 14.3‰, respectively) because carbonate-bedrock dissolution provided an inorganic source of C to the cave. Carbon species in the soil had a unique, light stable-C isotopic signature compared to the cave. Discrimination of soil-C sources to karst groundwater was achieved, which is critical for developing hydrologic budgets using environmental tracers such as C.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geodrs.2017.05.004","usgsCitation":"Knierim, K.J., Pollock, E.D., Covington, M.D., Hays, P.D., and Brye, K.R., 2017, Carbon cycling in the mantled karst of the Ozark Plateaus, central United States: Geoderma Regional, v. 10, p. 64-76, https://doi.org/10.1016/j.geodrs.2017.05.004.","productDescription":"13 p.","startPage":"64","endPage":"76","ipdsId":"IP-066344","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469852,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geodrs.2017.05.004","text":"Publisher Index Page"},{"id":438344,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610XJ5","text":"USGS data release","linkHelpText":"Carbonate geochemistry dataset of the soil and an underlying cave in the Ozark Plateaus, central United States"},{"id":341306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe34e4b0a7fdb43c8beb","contributors":{"authors":[{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Erik D.","contributorId":192014,"corporation":false,"usgs":false,"family":"Pollock","given":"Erik","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":695090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covington, Matthew D.","contributorId":192015,"corporation":false,"usgs":false,"family":"Covington","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":695091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brye, Kristofor R.","contributorId":192016,"corporation":false,"usgs":false,"family":"Brye","given":"Kristofor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":695161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187124,"text":"ds1049 - 2017 - Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface","interactions":[],"lastModifiedDate":"2017-07-24T13:40:45","indexId":"ds1049","displayToPublicDate":"2017-05-12T08:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1049","title":"Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface","docAbstract":"Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island from May 6-20, 2015. The USGS is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echo sounders and Global Positioning Systems, which were mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach. Additional bathymetry and elevation data were collected using backpack Global Positioning Systems on flood shoals and in shallow channels within the wilderness breach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1049","usgsCitation":"Nelson, T.R., Miselis, J.L., Hapke, C.J., Brenner, O.T., Henderson, R.E., Reynolds, B.J., Wilson, K.E., 2017, Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface: U.S. Geological Survey Data Series 1049, https://doi.org/10.3133/ds1049.\n\n","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073892","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":341095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1049/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"}},{"id":341094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1049/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.35,\n 40.55\n ],\n [\n -72.7,\n 40.55\n ],\n [\n -72.7,\n 40.866667\n ],\n [\n -73.35,\n 40.866667\n ],\n [\n -73.35,\n 40.55\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
Uneven distribution of rainfall and freshwater scarcity in populated areas in the Island of Maui, Hawaii, renders water resources management a challenge in this complex and ill-defined hydrological system. A previous study in the Galapagos Islands suggests that noble gas temperatures (NGTs) record seasonality in that fractured, rapid infiltration groundwater system rather than the commonly observed mean annual air temperature (MAAT) in sedimentary systems where infiltration is slower thus, providing information on recharge sources and potential flow paths. Here we report noble gas results from the basal aquifer, springs, and rainwater in Maui to explore the potential for noble gases in characterizing this type of complex fractured hydrologic systems. Most samples display a mass-dependent depletion pattern with respect to surface conditions consistent with previous observations both in the Galapagos Islands and Michigan rainwater. Basal aquifer and rainwater noble gas patterns are similar and suggest direct, fast recharge from precipitation to the basal aquifer. In contrast, multiple springs, representative of perched aquifers, display highly variable noble gas concentrations suggesting recharge from a variety of sources. The distinct noble gas patterns for the basal aquifer and springs suggest that basal and perched aquifers are separate entities. Maui rainwater displays high apparent NGTs, incompatible with surface conditions, pointing either to an origin at high altitudes with the presence of ice or an ice-like source of undetermined origin. Overall, noble gas signatures in Maui reflect the source of recharge rather than the expected altitude/temperature relationship commonly observed in sedimentary systems.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016WR020172","usgsCitation":"Niu, Y., Castro, M.C., Hall, C., Gingerich, S.B., Scholl, M.A., and Warrier, R.B., 2017, Noble gas signatures in the Island of Maui, Hawaii: Characterizing groundwater sources in fractured systems: Water Resources Research, v. 53, no. 5, p. 3599-3614, https://doi.org/10.1002/2016WR020172.","productDescription":"16 p.","startPage":"3599","endPage":"3614","ipdsId":"IP-084259","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":341185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": 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Therefore, it is critical to do as much as possible to prevent the spread of two species of dreissenid mussels, both non-native and highly invasive aquatic species already well-established in the eastern half of the United States. This book addresses the occurrences of the two dreissenid mussels in the West, the quagga mussel and the zebra mussel, that are both known to negatively impact water delivery systems and natural ecosystems. It is edited by two researchers whom have extensive experience working with the mussels in the West and is composed of 34 chapters, or articles, written by a variety of experts.
Book information: Biology and Management of Invasive Quagga and Zebra Mussels in the Western United States. Edited by Wai Hing Wong and Shawn L. Gerstenberger. Boca Raton (Florida): CRC Press (Taylor & Francis Group). $149.95. xx + 545 p.; ill.; index. ISBN: 978-1-4665-9561-3. [Compact Disc included.] 2015.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/692233","usgsCitation":"Benson, A.J., 2017, Book review: Biology and management of invasive quagga and zebra mussels in the western United States: The Quarterly Review of Biology, v. 92, no. 2, p. 209-210, https://doi.org/10.1086/692233.","productDescription":"2 p.","startPage":"209","endPage":"210","ipdsId":"IP-084644","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":341243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b0e4b044b359e48686","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":694944,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187642,"text":"70187642 - 2017 - Atmospheric deposition to forests in the eastern USA","interactions":[],"lastModifiedDate":"2017-05-12T09:42:09","indexId":"70187642","displayToPublicDate":"2017-05-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric deposition to forests in the eastern USA","docAbstract":"Atmospheric mercury (Hg) deposition to forests is important because half of the land cover in the eastern USA is forest. Mercury was measured in autumn litterfall and weekly precipitation samples at a total of 27 National Atmospheric Deposition Program (NADP) monitoring sites in deciduous and mixed deciduous-coniferous forests in 16 states in the eastern USA during 2007–2014. These simultaneous, uniform, repeated, annual measurements of forest Hg include the broadest area and longest time frame to date. The autumn litterfall-Hg concentrations and litterfall mass at the study sites each year were combined with annual precipitation-Hg data. Rates of litterfall-Hg deposition were higher than or equal to precipitation-Hg deposition rates in 70% of the annual data, which indicates a substantial contribution from litterfall to total atmospheric-Hg deposition. Annual litterfall-Hg deposition in this study had a median of 11.7 μg per square meter per year (μg/m2/yr) and ranged from 2.2 to 23.4 μg/m2/yr. It closely matched modeled dry-Hg deposition, based on land cover at selected NADP Hg-monitoring sites. Mean annual atmospheric-Hg deposition at forest study sites exhibited a spatial pattern partly explained by statistical differences among five forest-cover types and related to the mapped density of Hg emissions. Forest canopies apparently recorded changes in atmospheric-Hg concentrations over time because litterfall-Hg concentrations decreased year to year and litterfall-Hg concentrations were significantly higher in 2007–2009 than in 2012–2014. These findings reinforce reported decreases in Hg emissions and atmospheric elemental-Hg concentrations during this same time period. Methylmercury (MeHg) was detected in all litterfall samples at all sites, compared with MeHg detections in less than half the precipitation samples at selected sites during the study. These results indicate MeHg in litterfall is a pathway into the terrestrial food web where it can accumulate in the prey of songbirds, bats, and raptors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.05.004","usgsCitation":"Risch, M.R., DeWild, J.F., Gay, D.A., Zhang, L., Boyer, E.W., and Krabbenhoft, D.P., 2017, Atmospheric deposition to forests in the eastern USA: Environmental Pollution, v. 228, p. 8-18, https://doi.org/10.1016/j.envpol.2017.05.004.","productDescription":"11 p. 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jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gay, David A.","contributorId":177963,"corporation":false,"usgs":false,"family":"Gay","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Leiming 0000-0001-5437-5412","orcid":"https://orcid.org/0000-0001-5437-5412","contributorId":191971,"corporation":false,"usgs":false,"family":"Zhang","given":"Leiming","email":"","affiliations":[],"preferred":false,"id":694913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":694914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":677,"text":"Wisconsin Water Science Center","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}],"preferred":true,"id":694915,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187620,"text":"70187620 - 2017 - Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia","interactions":[],"lastModifiedDate":"2017-05-12T10:37:16","indexId":"70187620","displayToPublicDate":"2017-05-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia","docAbstract":"Burnsville Cove in Bath and Highland Counties (Virginia, USA) is a karst region in the Valley and Ridge Province of the Appalachian Mountains. The region contains many caves in Silurian to Devonian limestone, and is well suited for examining geologic controls on cave location and cave passage morphology. In Burnsville Cove, many caves are located preferentially near the axes of synclines and anticlines. For example, Butler Cave is an elongate cave where the trunk channel follows the axis of Sinking Creek syncline and most of the side passages follow joints at right angles to the syncline axis. In contrast, the Water Sinks Subway Cave, Owl Cave, and Helictite Cave have abundant maze patterns, and are located near the axis of Chestnut Ridge anticline. The maze patterns may be related to fact that the anticline axis is the site of the greatest amount of flexure, leading to more joints and (or) greater enlargement of joints. Many of the larger caves of Burnsville Cove (e.g., Breathing Cave, Butler Cave–Sinking Creek Cave System, lower parts of the Water Sinks Cave System) are developed in the Silurian Tonoloway Limestone, the stratigraphic unit with the greatest surface exposure in the area. Other caves are developed in the Silurian to Devonian Keyser Limestone of the Helderberg Group (e.g., Owl Cave, upper parts of the Water Sinks Cave System) and in the Devonian Shriver Chert and (or) Licking Creek Limestone of the Helderberg Group (e.g., Helictite Cave). Within the Tonoloway Limestone, the larger caves are developed in the lower member of the Tonoloway Limestone immediately below a bed of silica-cemented sandstone. In contrast, the larger caves in the Keyser Limestone are located preferentially in limestone beds containing stromatoporoid reefs, and some of the larger caves in the Licking Creek Limestone are located in beds of cherty limestone below the Devonian Oriskany Sandstone. Geologic controls on cave passage morphology include joints, bedding planes, and folds. The influence of joints results in tall and narrow cave passages, whereas the influence of bedding planes results in cave passages with flat ceilings and (or) floors. The influence of folds is less common, but a few cave passages follow fold axes and have distinctive arched ceilings.
","largerWorkTitle":"From the Blue Ridge to the Beach: Geological Field Excursions across Virginia","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/2017.0047(04)","usgsCitation":"Swezey, C.S., Haynes, J.T., Lucas, P.C., and Lambert, R.A., 2017, Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia: GSA Field Guides, v. 47, p. 89-123, https://doi.org/10.1130/2017.0047(04).","productDescription":"35 p.","startPage":"89","endPage":"123","ipdsId":"IP-081746","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":438346,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YMM9EM","text":"USGS data release","linkHelpText":"Data Release for Luminescence: Butler Cave, Burnsville Cove, Bath and Highland Counties, VA"},{"id":341195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","county":"Bath County, Highland County","otherGeospatial":"Burnsville Cove","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.680556,\n 38.141667\n ],\n [\n -79.5625,\n 38.141667\n ],\n [\n -79.5625,\n 38.241667\n ],\n [\n -79.680556,\n 38.241667\n ],\n [\n -79.680556,\n 38.141667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b3e4b044b359e48690","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":694787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haynes, John T.","contributorId":54842,"corporation":false,"usgs":true,"family":"Haynes","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":694788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Philip C.","contributorId":191928,"corporation":false,"usgs":false,"family":"Lucas","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":694789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lambert, Richard A.","contributorId":191929,"corporation":false,"usgs":false,"family":"Lambert","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694952,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186810,"text":"sir20175018 - 2017 - Evaluation of radon occurrence in groundwater from 16 geologic units in Pennsylvania, 1986–2015, with application to potential radon exposure from groundwater and indoor air","interactions":[],"lastModifiedDate":"2017-05-11T10:56:21","indexId":"sir20175018","displayToPublicDate":"2017-05-11T08:45:00","publicationYear":"2017","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":"2017-5018","title":"Evaluation of radon occurrence in groundwater from 16 geologic units in Pennsylvania, 1986–2015, with application to potential radon exposure from groundwater and indoor air","docAbstract":"Results from 1,041 groundwater samples collected during 1986‒2015 from 16 geologic units in Pennsylvania, associated with 25 or more groundwater samples with concentrations of radon-222, were evaluated in an effort to identify variations in radon-222 activities or concentrations and to classify potential radon-222 exposure from groundwater and indoor air. Radon-222 is hereafter referred to as “radon.” Radon concentrations in groundwater greater than or equal to the proposed U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for public-water supply systems of 300 picocuries per liter (pCi/L) were present in about 87 percent of the water samples, whereas concentrations greater than or equal to the proposed alternative MCL (AMCL) for public water-supply systems of 4,000 pCi/L were present in 14 percent. The highest radon concentrations were measured in groundwater from the schists, gneisses, and quartzites of the Piedmont Physiographic Province.
In this study, conducted by the U.S. Geological Survey in cooperation with the Pennsylvania Department of Health and the Pennsylvania Department of Environmental Protection, groundwater samples were aggregated among 16 geologic units in Pennsylvania to identify units with high median radon concentrations in groundwater. Graphical plots and statistical tests were used to determine variations in radon concentrations in groundwater and indoor air. Median radon concentrations in groundwater samples and median radon concentrations in indoor air samples within the 16 geologic units were classified according to proposed and recommended regulatory limits to explore potential radon exposure from groundwater and indoor air. All of the geologic units, except for the Allegheny (Pa) and Glenshaw (Pcg) Formations in the Appalachian Plateaus Physiographic Province, had median radon concentrations greater than the proposed EPA MCL of 300 pCi/L, and the Peters Creek Schist (Xpc), which is in the Piedmont Physiographic Province, had a median radon concentration greater than the EPA proposed AMCL of 4,000 pCi/L. Median concentrations of radon in groundwater and indoor air were determined to differ significantly among the geologic units (Kruskal-Wallis test, significance probability, p<0.001), and Tukey’s test indicated that radon concentrations in groundwater and indoor air in the Peters Creek Schist (Xpc) were significantly higher than those in the other units. Also, the Peters Creek Schist (Xpc) was determined to be the area with highest potential of radon exposure from groundwater and indoor air and one of two units with the highest percentage of population assumed to be using domestic self-supplied water (81 percent), which puts the population at greater potential of exposure to radon from groundwater.
Potential radon exposure determined from classification of geologic units by median radon concentrations in groundwater and indoor air according to proposed and recommended regulatory limits is useful for drawing general conclusions about the presence, variation, and potential radon exposure in specific geologic units, but the associated data and maps have limitations. The aggregated indoor air radon data have spatial accuracy limitations owing to imprecision of geocoded test locations. In addition, the associated data describing geologic units and the public water supplier’s service areas have spatial and interpretation accuracy limitations. As a result, data and maps associated with this report are not recommended for use in predicting individual concentrations at specific sites nor for use as a decision-making tool for property owners to decide whether to test for radon concentrations at specific locations. Instead, the data and maps are meant to promote awareness regarding potential radon exposure in Pennsylvania and to point out data gaps that exist throughout the State.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175018","collaboration":"Prepared in cooperation with the Pennsylvania Department of Health and the Pennsylvania Department of Environmental Protection","usgsCitation":"Gross, E.L., 2017, Evaluation of radon occurrence in groundwater from 16 geologic units in Pennsylvania, 1986–2015, with application to potential radon exposure from groundwater and indoor air: U.S. Geological Survey Scientific Investigations Report 2017–5018, 24 p., https://doi.org/10.3133/sir20175018.","productDescription":"vi, 24 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081317","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":339920,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5018/coverthb.jpg"},{"id":340851,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Soil drainage is a widely used agricultural practice in the midwest USA to remove excess soil water to potentially improve the crop yield. Research shows an increasing trend in baseflow and streamflow in the midwest over the last 60 years, which may be related to artificial drainage. Subsurface drainage (i.e., tile) in particular may have strongly contributed to the increase in these flows, because of its extensive use and recent gain in the popularity as a yield-enhancement practice. However, how evapotranspiration (ET) is impacted by tile drainage on a regional level is not well-documented. To explore spatial and temporal ET patterns and their relationship to tile drainage, we applied an energy balance-based multisensor data fusion method to estimate daily 30-m ET over an intensively tile-drained area in South Dakota, USA, from 2005 to 2013. Results suggest that tile drainage slightly decreases the annual cumulative ET, particularly during the early growing season. However, higher mid-season crop water use suppresses the extent of the decrease of the annual cumulative ET that might be anticipated from widespread drainage. The regional water balance analysis during the growing season demonstrates good closure, with the average residual from 2005 to 2012 as low as -3 mm. As an independent check of the simulated ET at the regional scale, the water balance analysis lends additional confidence to the study. The results of this study improve our understanding of the influence of agricultural drainage practices on regional ET, and can affect future decision making regarding tile drainage systems.
","language":"English","publisher":"IEEE","doi":"10.1109/JSTARS.2017.2680411","usgsCitation":"Yang, Y., Anderson, M.C., Gao, F., Hain, C., Kustas, W.P., Meyers, T.P., Crow, W., Finocchiaro, R.G., Otkin, J., Sun, L., and Yang, Y., 2017, Impact of tile drainage on evapotranspiration in South Dakota, USA, based on high spatiotemporal resolution evapotranspiration time series from a multi-satellite data fusion system: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 10, no. 6, p. 2250-2564, https://doi.org/10.1109/JSTARS.2017.2680411.","productDescription":"15 p.","startPage":"2250","endPage":"2564","ipdsId":"IP-079712","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469857,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/470bf08e5c7a445296ba2463f1e54c42","text":"External Repository"},{"id":341160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59154631e4b01a342e6912d4","contributors":{"authors":[{"text":"Yang, Yun","contributorId":191965,"corporation":false,"usgs":false,"family":"Yang","given":"Yun","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Martha C.","contributorId":96579,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","email":"","middleInitial":"C.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hain, Christopher","contributorId":191966,"corporation":false,"usgs":false,"family":"Hain","given":"Christopher","email":"","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":694895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kustas, William P.","contributorId":29962,"corporation":false,"usgs":false,"family":"Kustas","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694896,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyers, Tilden P.","contributorId":146138,"corporation":false,"usgs":false,"family":"Meyers","given":"Tilden","email":"","middleInitial":"P.","affiliations":[{"id":16598,"text":"NOAA/ATDD","active":true,"usgs":false}],"preferred":false,"id":694898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Finocchiaro, Raymond G. rfinocchiaro@usgs.gov","contributorId":3673,"corporation":false,"usgs":true,"family":"Finocchiaro","given":"Raymond","email":"rfinocchiaro@usgs.gov","middleInitial":"G.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":694900,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Crow, Wade","contributorId":94563,"corporation":false,"usgs":false,"family":"Crow","given":"Wade","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694899,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Otkin, Jason","contributorId":106176,"corporation":false,"usgs":false,"family":"Otkin","given":"Jason","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":694901,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sun, Liang","contributorId":119410,"corporation":false,"usgs":false,"family":"Sun","given":"Liang","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694902,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yang, Yang","contributorId":85292,"corporation":false,"usgs":false,"family":"Yang","given":"Yang","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":694903,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70178728,"text":"sir20165156 - 2017 - Magnitude of flood flows for selected annual exceedance probabilities for streams in Massachusetts","interactions":[],"lastModifiedDate":"2017-05-10T16:40:49","indexId":"sir20165156","displayToPublicDate":"2017-05-10T17:10:00","publicationYear":"2017","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":"2016-5156","title":"Magnitude of flood flows for selected annual exceedance probabilities for streams in Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the Massachusetts Department of Transportation, determined the magnitude of flood flows at selected annual exceedance probabilities (AEPs) at streamgages in Massachusetts and from these data developed equations for estimating flood flows at ungaged locations in the State. Flood magnitudes were determined for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs at 220 streamgages, 125 of which are in Massachusetts and 95 are in the adjacent States of Connecticut, New Hampshire, New York, Rhode Island, and Vermont. AEP flood flows were computed for streamgages using the expected moments algorithm weighted with a recently computed regional skewness coefficient for New England.
Regional regression equations were developed to estimate the magnitude of floods for selected AEP flows at ungaged sites from 199 selected streamgages and for 60 potential explanatory basin characteristics. AEP flows for 21 of the 125 streamgages in Massachusetts were not used in the final regional regression analysis, primarily because of regulation or redundancy. The final regression equations used generalized least squares methods to account for streamgage record length and correlation. Drainage area, mean basin elevation, and basin storage explained 86 to 93 percent of the variance in flood magnitude from the 50- to 0.2-percent AEPs, respectively. The estimates of AEP flows at streamgages can be improved by using a weighted estimate that is based on the magnitude of the flood and associated uncertainty from the at-site analysis and the regional regression equations. Weighting procedures for estimating AEP flows at an ungaged site on a gaged stream also are provided that improve estimates of flood flows at the ungaged site when hydrologic characteristics do not abruptly change.
Urbanization expressed as the percentage of imperviousness provided some explanatory power in the regional regression; however, it was not statistically significant at the 95-percent confidence level for any of the AEPs examined. The effect of urbanization on flood flows indicates a complex interaction with other basin characteristics. Another complicating factor is the assumption of stationarity, that is, the assumption that annual peak flows exhibit no significant trend over time. The results of the analysis show that stationarity does not prevail at all of the streamgages. About 27 percent of streamgages in Massachusetts and about 42 percent of streamgages in adjacent States with 20 or more years of systematic record used in the study show a significant positive trend at the 95-percent confidence level. The remaining streamgages had both positive and negative trends, but the trends were not statistically significant. Trends were shown to vary over time. In particular, during the past decade (2004–2013), peak flows were persistently above normal, which may give the impression of positive trends. Only continued monitoring will provide the information needed to determine whether recent increases in annual peak flows are a normal oscillation or a true trend.
The analysis used 37 years of additional data obtained since the last comprehensive study of flood flows in Massachusetts. In addition, new methods for computing flood flows at streamgages and regionalization improved estimates of flood magnitudes at gaged and ungaged locations and better defined the uncertainty of the estimates of AEP floods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165156","collaboration":"Prepared in cooperation with the Massachusetts Department of Transportation","usgsCitation":"Zarriello, P.J., 2017, Magnitude of flood flows at selected annual exceedance probabilities for streams in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5156, 54 p., https://doi.org/10.3133/sir20165156.","productDescription":"Report: ix, 54 p.; Tables; 1 Appendix","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065274","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":341058,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table11.csv","text":"Table 11","size":"47.9 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Magnitude and variance of selected flood 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studies"},{"id":341060,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table13.csv","text":"Table 13","size":"28.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Comparison of newly estimated flood flows to prior studies"},{"id":341047,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table03.csv","text":"Table 3 ","size":"85.5 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Flood flows for Massachusetts and adjacent States through water year 2013"},{"id":340865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5156/coverthb.jpg"},{"id":340867,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_appendix03.xlsx","text":"Appendix 3 ","size":"92.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5156 Appendix 3","linkHelpText":"- Workbook for estimating flood flows at gaged and ungaged sites in Massachusetts "},{"id":340870,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table04.xlsx","text":"Table 4","size":"71.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5156 Table 4","linkHelpText":"- Streamgage and basin characteristics"},{"id":341059,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table04.csv","text":"Table 4 ","size":"30.1 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Streamgage and basin characteristics"},{"id":340866,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156.pdf","text":"Report","size":"5.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5156"}],"country":"United 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532