The U.S. Geological Survey (USGS) has developed a dynamic food-web simulation model to provide decision support for Bureau of Reclamation (Reclamation) river restoration projects in the Methow River, Washington. This modeling effort was done to contribute to Reasonable and Prudent Alternative actions 56 and 57of the 2014 Federal Columbia River Power System Biological Opinion (FCRPS BO), which calls for exploration of modeling as a means to help evaluate Endangered Species Act (ESA)-listed fish response to river restoration efforts. In the Methow River, these species of concern include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha) and UCR summer steelhead (Oncorhynchus mykiss). Additionally, the Independent Scientific Advisory Board (ISAB) for the Columbia River has identified the need for modeling (Independent Scientific Advisory Board, 2011a)—including models that incorporate food-web dynamics (Independent Scientific Advisory Board, 2011b)—to better understand how restoration and management strategies might enhance salmon and steelhead populations.
\nDynamic food-web models, even relatively simple ones, can be valuable tools for exploring responses to river restoration. Although these models have rarely been applied to rivers and streams (but see Mcintire and Colby, 1978; Power and others, 1995), they are commonly used for management decisions in terrestrial and ocean ecosystems (Christensen and Pauly, 1993; Evans and others, 2013). One of the main strengths of these models is that they are rooted in the fundamental laws of thermodynamics (that is, mass balance). Moreover, these models can be easily adapted to different contexts by adding or subtracting different species from the web and by mechanistically linking the dynamics of web members to local environmental conditions, such as water temperature, stream discharge, and channel hydraulics (Power and others, 1995; Doyle, 2006). Alternative management actions can then be evaluated by changing these environmental conditions to simulate potential outcomes following restoration.
\nIn this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., and Bellmore, J.R., 2016, Aquatic trophic productivity model: A decision support model for river restoration planning in the Methow River, Washington: U.S. Geological Survey Open-File Report 2016‒1075, 85 p., https://dx.doi.org/10.3133/ofr20161075.","productDescription":"vi, 85 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1075/coverthb.jpg"},{"id":321409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1075/ofr20161075.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1075 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
During summer 2014, lake level, streamflow, and water temperature in and around Crystal Springs Lake in Portland, Oregon, were measured by the U.S. Geological Survey and the City of Portland Bureau of Environmental Services to better understand the effect of the lake on Crystal Springs Creek and Johnson Creek downstream. Johnson Creek is listed as an impaired water body for temperature by the Oregon Department of Environmental Quality (ODEQ), as required by section 303(d) of the Clean Water Act. A temperature total maximum daily load applies to all streams in the Johnson Creek watershed, including Crystal Springs Creek. Summer water temperatures downstream of Crystal Springs Lake and the Golf Pond regularly exceed the ODEQ numeric criterion of 64.4 °F (18.0 °C) for salmonid rearing and migration. To better understand temperature contributions of this system, the U.S. Geological Survey developed two-dimensional hydrodynamic water temperature models of Crystal Springs Lake and the Golf Pond. Model grids were developed to closely resemble the bathymetry of the lake and pond using data from a 2014 survey. The calibrated models simulated surface water elevations to within 0.06 foot (0.02 meter) and outflow water temperature to within 1.08 °F (0.60 °C). Streamflow, water temperature, and lake elevation data collected during summer 2014 supplied the boundary and reference conditions for the model. Measured discrepancies between outflow and inflow from the lake, assumed to be mostly from unknown and diffuse springs under the lake, accounted for about 46 percent of the total inflow to the lake.
\nModel simulations (scenarios) were run with lower water surface elevations in Crystal Springs Lake and increased shading to the lake to assess the relative effect the lake and pond characteristics have on water temperature. The Golf Pond was unaltered in all scenarios. The models estimated that lower lake elevations would result in cooler water downstream of the Golf Pond and shorter residence times in the lake. Increased shading to the lake would also provide substantial cooling. Most management scenarios resulted in a decrease in 7-day average of daily maximum values by about 2.0– 4.7 °F (1.1 –2.6 °C) for outflow from Crystal Springs Lake during the period of interest. Outflows from the Golf Pond showed a net temperature reduction of 0.5–2.7 °F (0.3–1.5 °C) compared to measured values in 2014 because of solar heating and downstream warming in the Golf Pond resulting from mixing with inflow from Reed Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161076","collaboration":"Prepared in cooperation with City of Portland Bureau of Environmental Services","usgsCitation":"Buccola, N.L., and Stonewall, A.J., 2016, Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon: U.S. Geological Survey Open-File Report 2016‒1076, 26 p.,\nhttps://dx.doi.org/10.3133/ofr20161076.","productDescription":"Report: vi, 26 p.; Tables 1-9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060388","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321392,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076_tables1-9.xlsx","text":"Tables 1-9","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1076 Tables 1-9"},{"id":321390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1076/coverthb.jpg"},{"id":321391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1076"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63982295989989,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.47522429601816\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
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Portland, Oregon 97201
http://or.water.usgs.gov
National Parks and other protected areas can be influenced by contamination from outside their boundaries. This is particularly true of smaller parks and those in riparian ecosystems, a habitat that in arid environments provides critical habitat for breeding, migratory, and wintering birds. Animals living in contaminated areas are susceptible to adverse health effects as a result of long-term exposure and bioaccumulation of heavy metals. We investigated the distribution and cascading extent of heavy metal accumulation in Song Sparrows (Melospiza melodia) at Tumacacori National Historic Park (TUMA) along the upper Santa Cruz River watershed in southern Arizona. This study had three goals: (1) quantify the concentrations and distributional patterns of heavy metals in blood and feathers of Song Sparrows at Tumacacori National Historic Park, (2) quantify hematocrit values, body conditions (that is, residual body mass), and immune conditions of Song Sparrows in the park (3) compare our findings with prior studies at the park to assess the extent of heavy metal accumulation in birds at downstream sites after the 2009 wastewater treatment plant upgrade, and (4) quantify concentrations and distributional patterns of heavy metals in blood and feathers of Song Sparrows among six study sites throughout the upper Santa Cruz River watershed. This study design would allow us to more accurately assess song sparrow condition and blood parameters among sites with differing potential sources of contamination exposure, and how each location could have contributed to heavy metal levels of birds in the park.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Engagement, education, and expectations - the future of parks and protected areas: Proceedings of the 2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites","language":"English","publisher":"George Wright Society","usgsCitation":"van Riper, C., and Lester, M.B., 2016, Changing levels of heavy metal accumulation in birds at Tumacacori National Historic Park along the Upper Santa Cruz River Watershed in southern Arizona, in Engagement, education, and expectations - the future of parks and protected areas: Proceedings of the 2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites, p. 123-128.","productDescription":"6 p.","startPage":"123","endPage":"128","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065932","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321385,"type":{"id":15,"text":"Index Page"},"url":"https://www.georgewright.org/proceedings2015"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573ed59be4b04a3a6a2462cc","contributors":{"authors":[{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":629770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lester, Michael B.","contributorId":92170,"corporation":false,"usgs":true,"family":"Lester","given":"Michael","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":629771,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171082,"text":"70171082 - 2016 - Salt marsh-mangrove ecotones: using structural gradients to investigate the effects of woody plant encroachment on plant-soil interactions and ecosystem carbon pools","interactions":[],"lastModifiedDate":"2016-08-25T08:31:35","indexId":"70171082","displayToPublicDate":"2016-05-19T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Salt marsh-mangrove ecotones: using structural gradients to investigate the effects of woody plant encroachment on plant-soil interactions and ecosystem carbon pools","docAbstract":"Insecticide use in urban areas results in the detection of these compounds in streams following stormwater runoff at concentrations likely to cause toxicity for stream invertebrates. In this 2013 study, stormwater runoff and streambed sediments were analyzed for 91 pesticides dissolved in water and 118 pesticides on sediment. Detections included 33 pesticides, including insecticides, fungicides, herbicides, degradates, and a synergist. Patterns in pesticide occurrence reveal transport of dissolved and sediment-bound pesticides, including pyrethroids, from upland areas through stormwater outfalls to receiving streams. Nearly all streams contained at least one insecticide at levels exceeding an aquatic-life benchmark, most often for bifenthrin and (or) fipronil. Multiple U.S. EPA benchmark or criterion exceedances occurred in 40 % of urban streams sampled. Bed sediment concentrations of bifenthrin were highly correlated (p < 0.001) with benthic invertebrate assemblages. Non-insects and tolerant invertebrates such as amphipods, flatworms, nematodes, and oligochaetes dominated streams with relatively high concentrations of bifenthrin in bed sediments, whereas insects, sensitive invertebrates, and mayflies were much more abundant at sites with no or low bifenthrin concentrations. The abundance of sensitive invertebrates, % EPT, and select mayfly taxa were strongly negatively correlated with organic-carbon normalized bifenthrin concentrations in streambed sediments. Our findings from western Clackamas County, Oregon (USA), expand upon previous research demonstrating the transport of pesticides from urban landscapes and linking impaired benthic invertebrate assemblages in urban streams with exposure to pyrethroid insecticides.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-016-5215-5","usgsCitation":"Carpenter, K.D., Kuivila, K., Hladik, M., Haluska, T., and Cole, M.B., 2016, Storm-event-transport of urban-use pesticides to streams likely impairs invertebrate assemblages: Environmental Monitoring and Assessment, v. 188, art345: 18 p., https://doi.org/10.1007/s10661-016-5215-5.","productDescription":"art345: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063257","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-016-5215-5","text":"Publisher Index 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B.","contributorId":169494,"corporation":false,"usgs":false,"family":"Cole","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25530,"text":"Cole Ecological, Inc.","active":true,"usgs":false}],"preferred":false,"id":629782,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174950,"text":"70174950 - 2016 - A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells","interactions":[],"lastModifiedDate":"2018-08-07T11:51:36","indexId":"70174950","displayToPublicDate":"2016-05-19T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells","docAbstract":"A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.05.011","usgsCitation":"Jurgens, B.C., Bohlke, J.K., Kauffman, L.J., Belitz, K., and Esser, B.K., 2016, A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells: Journal of Hydrology, v. 543, no. A, p. 109-126, https://doi.org/10.1016/j.jhydrol.2016.05.011.","productDescription":"18 p.","startPage":"109","endPage":"126","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":325571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.9\n ],\n [\n -122,\n 37.2\n ],\n [\n -120.2,\n 37.2\n ],\n [\n -120.2,\n 37.9\n ],\n [\n -122,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"543","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57934440e4b0eb1ce79e8bd2","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, John Karl 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":127841,"corporation":false,"usgs":true,"family":"Bohlke","given":"John","email":"jkbohlke@usgs.gov","middleInitial":"Karl","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":643298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":643300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":643301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171088,"text":"70171088 - 2016 - Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?","interactions":[],"lastModifiedDate":"2016-05-19T09:45:34","indexId":"70171088","displayToPublicDate":"2016-05-19T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?","docAbstract":"As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13208","usgsCitation":"Foster, J.R., Finley, A.O., D’Amato, A.W., Bradford, J.B., and Banerjee, S., 2016, Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?: Global Change Biology, v. 22, no. 6, p. 2138-2151, https://doi.org/10.1111/gcb.13208.","productDescription":"14 p.","startPage":"2138","endPage":"2151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069743","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Superior National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.48291015625,\n 47.76517619125415\n ],\n [\n -92.48291015625,\n 48.38361810886624\n ],\n [\n -90.02471923828125,\n 48.38361810886624\n ],\n [\n -90.02471923828125,\n 47.76517619125415\n ],\n [\n -92.48291015625,\n 47.76517619125415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-03","publicationStatus":"PW","scienceBaseUri":"573ed59ce4b04a3a6a2462e0","chorus":{"doi":"10.1111/gcb.13208","url":"http://dx.doi.org/10.1111/gcb.13208","publisher":"Wiley-Blackwell","authors":"Foster Jane R., Finley Andrew O., D'Amato Anthony W., Bradford John B., Banerjee Sudipto","journalName":"Global Change Biology","publicationDate":"3/3/2016","auditedOn":"6/21/2016"},"contributors":{"authors":[{"text":"Foster, Jane R.","contributorId":27792,"corporation":false,"usgs":true,"family":"Foster","given":"Jane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":629806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finley, Andrew O.","contributorId":39310,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":629807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":629808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banerjee, Sudipto","contributorId":73894,"corporation":false,"usgs":true,"family":"Banerjee","given":"Sudipto","email":"","affiliations":[],"preferred":false,"id":629809,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171437,"text":"70171437 - 2016 - Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012","interactions":[],"lastModifiedDate":"2016-06-01T16:09:56","indexId":"70171437","displayToPublicDate":"2016-05-19T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012","docAbstract":"Estimating rates of magma supply to the world's volcanoes remains one of the most fundamental aims of volcanology. Yet, supply rates can be difficult to estimate even at well-monitored volcanoes, in part because observations are noisy and are usually considered independently rather than as part of a holistic system. In this work we demonstrate a technique for probabilistically estimating time-variable rates of magma supply to a volcano through probabilistic constraint on storage and eruption rates. This approach utilizes Bayesian joint inversion of diverse datasets using predictions from a multiphysical volcano model, and independent prior information derived from previous geophysical, geochemical, and geological studies. The solution to the inverse problem takes the form of a probability density function which takes into account uncertainties in observations and prior information, and which we sample using a Markov chain Monte Carlo algorithm. Applying the technique to Kīlauea Volcano, we develop a model which relates magma flow rates with deformation of the volcano's surface, sulfur dioxide emission rates, lava flow field volumes, and composition of the volcano's basaltic magma. This model accounts for effects and processes mostly neglected in previous supply rate estimates at Kīlauea, including magma compressibility, loss of sulfur to the hydrothermal system, and potential magma storage in the volcano's deep rift zones. We jointly invert data and prior information to estimate rates of supply, storage, and eruption during three recent quasi-steady-state periods at the volcano. Results shed new light on the time-variability of magma supply to Kīlauea, which we find to have increased by 35–100% between 2001 and 2006 (from 0.11–0.17 to 0.18–0.28 km3/yr), before subsequently decreasing to 0.08–0.12 km3/yr by 2012. Changes in supply rate directly impact hazard at the volcano, and were largely responsible for an increase in eruption rate of 60–150% between 2001 and 2006, and subsequent decline by as much as 60% by 2012. We also demonstrate the occurrence of temporal changes in the proportion of Kīlauea's magma supply that is stored versus erupted, with the supply “surge” in 2006 associated with increased accumulation of magma at the summit. Finally, we are able to place some constraints on sulfur concentrations in Kīlauea magma and the scrubbing of sulfur by the volcano's hydrothermal system. Multiphysical, Bayesian constraint on magma flow rates may be used to monitor evolving volcanic hazard not just at Kīlauea but at other volcanoes around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.04.029","usgsCitation":"Anderson, K.R., and Poland, M.P., 2016, Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012: Earth and Planetary Science Letters, v. 447, p. 161-171, https://doi.org/10.1016/j.epsl.2016.04.029.","productDescription":"11 p.","startPage":"161","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071533","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.04.029","text":"Publisher Index Page"},{"id":322056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.31784057617188,\n 19.374636239520235\n ],\n [\n -155.31784057617188,\n 19.44652177370614\n ],\n [\n -155.21896362304688,\n 19.44652177370614\n ],\n [\n -155.21896362304688,\n 19.374636239520235\n ],\n [\n -155.31784057617188,\n 19.374636239520235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"447","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500734e4b0ee97d51bb3c8","chorus":{"doi":"10.1016/j.epsl.2016.04.029","url":"http://dx.doi.org/10.1016/j.epsl.2016.04.029","publisher":"Elsevier BV","authors":"Anderson Kyle R., Poland Michael P.","journalName":"Earth and Planetary Science Letters","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":630979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":630980,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174955,"text":"70174955 - 2016 - Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation","interactions":[],"lastModifiedDate":"2016-07-22T16:11:29","indexId":"70174955","displayToPublicDate":"2016-05-19T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation","docAbstract":"General circulation model (GCM) simulations of the mid-Pliocene Warm Period (mPWP, 3.264 to 3.025 Myr ago) do not reproduce the magnitude of Northern Hemisphere high latitude surface air and sea surface temperature (SAT and SST) warming that proxy data indicate. There is also large uncertainty regarding the state of sea ice cover in the mPWP. Evidence for both perennial and seasonal mPWP Arctic sea ice is found through analyses of marine sediments, whilst in a multi-model ensemble of mPWP climate simulations, half of the ensemble simulated ice-free summer Arctic conditions. Given the strong influence that sea ice exerts on high latitude temperatures, an understanding of the nature of mPWP Arctic sea ice would be highly beneficial.
\nUsing the HadCM3 GCM, this paper explores the impact of various combinations of potential mPWP orbital forcing, atmospheric CO2 concentrations and minimum sea ice albedo on sea ice extent and high latitude warming. The focus is on the Northern Hemisphere, due to availability of proxy data, and the large data–model discrepancies in this region. Changes in orbital forcings are demonstrated to be sufficient to alter the Arctic sea ice simulated by HadCM3 from perennial to seasonal. However, this occurs only when atmospheric CO2 concentrations exceed 300 ppm. Reduction of the minimum sea ice albedo from 0.5 to 0.2 is also sufficient to simulate seasonal sea ice, with any of the combinations of atmospheric CO2 and orbital forcing. Compared to a mPWP control simulation, monthly mean increases north of 60°N of up to 4.2 °C (SST) and 9.8 °C (SAT) are simulated.
\nWith varying CO2, orbit and sea ice albedo values we are able to reproduce proxy temperature records that lean towards modest levels of high latitude warming, but other proxy data showing greater warming remain beyond the reach of our model. This highlights the importance of additional proxy records at high latitudes and ongoing efforts to compare proxy signals between sites.
","language":"English","publisher":"North-Holland Pub. Co.","doi":"10.1016/j.epsl.2016.02.036","usgsCitation":"Howell, F.W., Haywood, A.M., Dowsett, H.J., and Pickering, S.J., 2016, Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation: Earth and Planetary Science Letters, v. 441, p. 133-142, https://doi.org/10.1016/j.epsl.2016.02.036.","productDescription":"10 p.","startPage":"133","endPage":"142","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073169","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.02.036","text":"Publisher Index Page"},{"id":325567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"441","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5793444ae4b0eb1ce79e8c10","chorus":{"doi":"10.1016/j.epsl.2016.02.036","url":"http://dx.doi.org/10.1016/j.epsl.2016.02.036","publisher":"Elsevier BV","authors":"Howell Fergus W., Haywood Alan M., Dowsett Harry J., Pickering Steven J.","journalName":"Earth and Planetary Science Letters","publicationDate":"5/2016"},"contributors":{"authors":[{"text":"Howell, Fergus W.","contributorId":173110,"corporation":false,"usgs":false,"family":"Howell","given":"Fergus","email":"","middleInitial":"W.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":643333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haywood, Alan M.","contributorId":86663,"corporation":false,"usgs":true,"family":"Haywood","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pickering, Steven J.","contributorId":147378,"corporation":false,"usgs":false,"family":"Pickering","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":643335,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170901,"text":"ds998 - 2016 - Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, July 2015","interactions":[],"lastModifiedDate":"2016-05-19T09:14:07","indexId":"ds998","displayToPublicDate":"2016-05-18T18:00:00","publicationYear":"2016","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":"998","title":"Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, July 2015","docAbstract":"Previous investigations indicate that concentrations of chlorinated volatile organic compounds (CVOCs) are substantial in groundwater beneath the 9-acre former landfill at Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington. The U.S. Geological Survey has continued to monitor groundwater geochemistry to ensure that conditions remain favorable for contaminant biodegradation as specified in the Record of Decision for the site.
\nThis report presents groundwater geochemical and selected CVOC data collected at Operable Unit 1 by the U.S. Geological Survey during July 6–8 and July 31, 2015 in support of long-term monitoring for natural attenuation. Water samples were collected from 13 wells, 9 piezometers, and 13 shallow groundwater passive-diffusion sampling sites in the nearby marsh. Samples from all wells and piezometers were analyzed for oxidation-reduction (redox) sensitive constituents. Samples from all piezometers and four wells also were analyzed for CVOCs and dissolved gases, as were all samples from the passive-diffusion sampling sites.
\nIn 2015, concentrations of redox-sensitive constituents measured at all wells and piezometers were consistent with those measured in previous years, with dissolved oxygen concentrations all less than 1 milligram per liter; little to no detectable nitrate; abundant dissolved manganese, iron, and methane; and commonly detected sulfide. In the upper aquifer of the northern plantation in 2015, CVOC concentrations at all piezometers were similar to those measured in previous years, and concentrations of the reductive dechlorination byproducts ethane and ethene were equivalent to the concentrations measured in 2014. In the upper aquifer of the southern plantation, CVOC concentrations measured in piezometers during 2015 continued to be variable as in previous years, and often very high, and reductive dechlorination byproducts were detected in one of the three wells and in piezometers. Beneath the marsh adjacent to the southern plantation, CVOC concentrations measured in 2015 continued to vary spatially and temporally, and were high. The total CVOC concentration, at what have been historically the most contaminated passive-diffusion sampler sites (S-4 T, S-4B T, and S-5 T), continued elevated trends, as did one of the new sampler sites (S-9 T) installed in 2015. For the intermediate aquifer in 2015, concentrations of reductive dechlorination byproducts ethane and ethene and CVOCs were consistent with those measured in previous years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds998","collaboration":"Prepared in cooperation with Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Huffman, R.L., 2016, Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, July 2015: U.S. Geological Survey Data Series 998, 55 p., https://dx.doi.org/10.3133/ds998.","productDescription":"iv, 55 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074626","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":321393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0998/coverthb.jpg"},{"id":321394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0998/ds998.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 998"}],"country":"United States","state":"Washington","otherGeospatial":"Division Keyport","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.88070678710938,\n 47.60986653003798\n ],\n [\n -122.88070678710938,\n 47.803008949806895\n ],\n [\n -122.58682250976562,\n 47.803008949806895\n ],\n [\n -122.58682250976562,\n 47.60986653003798\n ],\n [\n -122.88070678710938,\n 47.60986653003798\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The coral reef in Faga‘alu Bay, Tutuila, American Samoa, has suffered numerous natural and anthropogenic stresses. Areas once dominated by live coral are now mostly rubble surfaces covered with turf or macroalgae. In an effort to improve the health and resilience of the coral reef system, the U.S. Coral Reef Task Force selected Faga‘alu Bay as a priority study area. To support these efforts, the U.S. Geological Survey mapped nearly 1 km2 of seafloor to depths of about 60 m. Unconsolidated sediment (predominantly sand) constitutes slightly greater than 50 percent of the seafloor in the mapped area; reef and other hardbottom potentially available for coral recruitment constitute nearly 50 percent of the mapped area. Of this potentially available hardbottom, only slightly greater than 37 percent is covered with at least 10 percent coral, which is fairly evenly distributed between the reef flat, fore reef, and offshore bank/shelf.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161077","usgsCitation":"Cochran, S.A., Gibbs, A.E., D’Antonio, N.L., and Storlazzi, C.D., 2016, Benthic habitat map of U.S. Coral Reef Task Force Faga‘alu Bay priority study area, Tutuila, American Samoa: U.S. Geological Survey Open-File Report 2016–1077, 32 p., https://dx.doi.org/10.3133/ofr20161077.","productDescription":"Report: v, 32 p.; Metadata; Spatial Data","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072636","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321386,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1077/coverthb2.jpg"},{"id":321350,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1077"},{"id":321366,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_metadata.html","text":"Metadata","size":"65 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1077 Metadata"},{"id":321367,"rank":2,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_gis_data.zip","text":"Polygon shapefile of benthic habitats and associated files","size":"256 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1077 GIS data"}],"country":"United States","state":"American Samoa","otherGeospatial":"Faga'alu Bay, Tutuila","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.69046020507812,\n -14.277026769167454\n ],\n [\n -170.76547622680664,\n -14.332417680244378\n ],\n [\n -170.74419021606442,\n -14.367674440539975\n ],\n [\n -170.69578170776367,\n -14.326097485980599\n ],\n [\n -170.66900253295898,\n -14.288006232490893\n ],\n [\n -170.69046020507812,\n -14.277026769167454\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The U.S. Geological Survey’s (USGS) Water Availability and Use Science Program (WAUSP) goals are to provide a more accurate assessment of the status of the water resources of the United States and assist in the determination of the quantity and quality of water that is available for beneficial uses. These assessments would identify long-term trends or changes in water availability since the 1950s in the United States and help to develop the basis for an improved ability to forecast water avail- ability for future economic, energy-production, and environmental uses. The National Water Census (http://water.usgs.gov/watercensus/), a research program of the WAUSP, supports studies to develop new water accounting tools and assess water availability at the regional and national scales. Studies supported by this program target focus areas with identified water availability concerns and topical science themes related to the use of water within a specific type of environmental setting. The topical study described in this fact sheet will focus on understanding the relation between production of unconventional oil and gas (UOG) for energy and the water needed to produce and sustain this type of energy development. This relation applies to the life-cycle of renewable and nonrenewable forms of UOG energy and includes extraction, production, refinement, delivery, and disposal of waste byproducts. Water-use data and models derived from this topical study will be applied to other similar oil and gas plays within the United States to help resource managers assess and account for water used or needed in these areas. Additionally, the results from this topical study will be used to further refine the methods used in compiling water-use data for selected categories (for example, mining, domestic self-supplied, public supply, and wastewater) in the USGS’s 5-year national water-use estimates reports (http://water.usgs.gov/watuse/).
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The restoration of the Nisqually River Delta (Washington, U.S.A.) represents one of the largest efforts toward reestablishing the ecosystem function and resilience of modified habitat in the Puget Sound, particularly for anadromous salmonid species. The opportunity for outmigrating salmon to access and benefit from the expansion of available tidal habitat can be quantified by several physical attributes, which are related to the ecological and physiological responses of juvenile salmon. We monitored a variety of physical parameters to measure changes in opportunity potential from historic, pre-restoration, and post-restoration habitat conditions at several sites across the delta. These parameters included channel morphology, water quality, tidal elevation, and landscape connectivity. We conducted fish catch surveys across the delta to determine if salmon was utilizing restored estuary habitat. Overall major channel area increased 42% and major channel length increased 131% from pre- to post-restoration conditions. Furthermore, the results of our tidal inundation model indicated that major channels were accessible up to 75% of the time, as opposed to 30% pre-restoration. Outmigrating salmon utilized this newly accessible habitat as quickly as 1 year post-restoration. The presence of salmon in restored tidal channels confirmed rapid post-restoration increases in opportunity potential on the delta despite habitat quality differences between restored and reference sites.
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Center","active":true,"usgs":true}],"preferred":false,"id":639651,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70171041,"text":"70171041 - 2016 - Value-focused framework for defining landscape-scale conservation targets","interactions":[],"lastModifiedDate":"2016-05-18T09:42:13","indexId":"70171041","displayToPublicDate":"2016-05-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2142,"text":"Journal for Nature Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Value-focused framework for defining landscape-scale conservation targets","docAbstract":"Conservation of natural resources can be challenging in a rapidly changing world and require collaborative efforts for success. Conservation planning is the process of deciding how to protect, conserve, and enhance or minimize loss of natural and cultural resources. Establishing conservation targets (also called indicators or endpoints), the measurable expressions of desired resource conditions, can help with site-specific up to landscape-scale conservation planning. Using conservation targets and tracking them through time can deliver benefits such as insight into ecosystem health and providing early warnings about undesirable trends. We describe an approach using value-focused thinking to develop statewide conservation targets for Florida. Using such an approach allowed us to first identify stakeholder objectives and then define conservation targets to meet those objectives. Stakeholders were able to see how their shared efforts fit into the broader conservation context, and also anticipate the benefits of multi-agency and -organization collaboration. We developed an iterative process for large-scale conservation planning that included defining a shared framework for the process, defining the conservation targets themselves, as well as developing management and monitoring strategies for evaluation of their effectiveness. The process we describe is applicable to other geographies where multiple parties are seeking to implement collaborative, large-scale biological planning.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jnc.2016.04.005","usgsCitation":"Romanach, S.S., Benscoter, A.M., and Brandt, L., 2016, Value-focused framework for defining landscape-scale conservation targets: Journal for Nature Conservation, v. 32, p. 53-61, https://doi.org/10.1016/j.jnc.2016.04.005.","productDescription":"9 p.","startPage":"53","endPage":"61","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070143","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jnc.2016.04.005","text":"Publisher Index Page"},{"id":321378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573d841ce4b0dae0d5e4c05e","contributors":{"authors":[{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","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":629660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benscoter, Allison M.","contributorId":57781,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":629661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":629662,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171561,"text":"70171561 - 2016 - Where is the hot rock and where is the ground water— Using CSAMT to map beneath and around Mount St. Helens","interactions":[],"lastModifiedDate":"2021-08-25T15:15:08.645034","indexId":"70171561","displayToPublicDate":"2016-05-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Where is the hot rock and where is the ground water— Using CSAMT to map beneath and around Mount St. Helens","docAbstract":"We have observed several new features in recent controlled-source audio-frequency magnetotelluric (CSAMT) soundings on and around Mount St. Helens, Washington State, USA. We have identified the approximate location of a strong electrical conductor at the edges of and beneath the 2004–08 dome. We interpret this conductor to be hot brine at the hot-intrusive-cold-rock interface. This contact can be found within 50 meters of the receiver station on Spine 5, which extruded between April and July of 2005. We have also mapped separate regional and glacier-dome aquifers, which lie one atop the other, out to considerable distances from the volcano.
","language":"English","publisher":"Environmental & Engineering Geophysical Society","doi":"10.2113/JEEG21.2.79","usgsCitation":"Wynn, J., Mosbrucker, A.R., Pierce, H., and Spicer, K.R., 2016, Where is the hot rock and where is the ground water— Using CSAMT to map beneath and around Mount St. Helens: Journal of Environmental & Engineering Geophysics, v. 21, no. 2, p. 79-87, https://doi.org/10.2113/JEEG21.2.79.","productDescription":"9 p.","startPage":"79","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063937","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":322151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.728271484375,\n 45.77901739936284\n ],\n [\n -122.728271484375,\n 46.69843486113957\n ],\n [\n -121.607666015625,\n 46.69843486113957\n ],\n [\n -121.607666015625,\n 45.77901739936284\n ],\n [\n -122.728271484375,\n 45.77901739936284\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5752aa3ae4b053f0edd13ec4","contributors":{"authors":[{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":631795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":631796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, Herbert hpierce@usgs.gov","contributorId":170019,"corporation":false,"usgs":true,"family":"Pierce","given":"Herbert","email":"hpierce@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":631797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":631798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171044,"text":"70171044 - 2016 - Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA","interactions":[],"lastModifiedDate":"2016-11-09T10:34:31","indexId":"70171044","displayToPublicDate":"2016-05-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":863,"text":"Aquatic Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA","docAbstract":"We assessed the abundance, distribution, and ecology of the nonnative Siberian prawn Palaemon modestus in the lower Snake River, Washington, USA. Analysis of prawn passage abundance at three Snake River dams showed that populations are growing at exponential rates, especially at Little Goose Dam where over 464,000 prawns were collected in 2015. Monthly beam trawling during 2011–2013 provided information on prawn abundance and distribution in Lower Granite and Little Goose Reservoirs. Zero-inflated regression predicted that the probability of prawn presence increased with decreasing water velocity and increasing depth. Negative binomial models predicted higher catch rates of prawns in deeper water and in closer proximity to dams. Temporally, prawn densities decreased slightly in the summer, likely due to the mortality of older individuals, and then increased in autumn and winter with the emergence and recruitment of young of the year. Seasonal length frequencies showed that distinct juvenile and adult size classes exist throughout the year, suggesting prawns live from 1 to 2 years and may be able to reproduce multiple times during their life. Most juvenile prawns become reproductive adults in 1 year, and peak reproduction occurs from late July through October. Mean fecundity (189 eggs) and reproductive output (11.9 %) are similar to that in their native range. The current use of deep habitats by prawns likely makes them unavailable to most predators in the reservoirs. The distribution and role of Siberian prawns in the lower Snake River food web will probably continue to change as the population grows and warrants continued monitoring and investigation.
","language":"English","publisher":"Springer","doi":"10.1007/s10452-016-9581-4","usgsCitation":"Erhardt, J.M., and Tiffan, K.F., 2016, Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA: Aquatic Ecology, v. 50, no. 4, p. 607-621, https://doi.org/10.1007/s10452-016-9581-4.","productDescription":"15 p.","startPage":"607","endPage":"621","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072347","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":321375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.36669921875,\n 46.1912395780416\n ],\n [\n -118.36669921875,\n 46.848921470800455\n ],\n [\n -116.83959960937499,\n 46.848921470800455\n ],\n [\n -116.83959960937499,\n 46.1912395780416\n ],\n [\n -118.36669921875,\n 46.1912395780416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-10","publicationStatus":"PW","scienceBaseUri":"573d841be4b0dae0d5e4c04d","contributors":{"authors":[{"text":"Erhardt, John M. 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":5380,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629664,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171057,"text":"70171057 - 2016 - Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California","interactions":[],"lastModifiedDate":"2016-05-18T09:17:59","indexId":"70171057","displayToPublicDate":"2016-05-18T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California","docAbstract":"To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8050371","usgsCitation":"Soulard, C.E., Albano, C.M., Villarreal, M.L., and Walker, J.J., 2016, Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California: Remote Sensing, v. 8, no. 5, Article 371; 16 p., https://doi.org/10.3390/rs8050371.","productDescription":"Article 371; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070750","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8050371","text":"Publisher Index Page"},{"id":321373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.79904174804688,\n 37.821175249016726\n ],\n [\n -119.79904174804688,\n 37.970725990064786\n ],\n [\n -119.59991455078124,\n 37.970725990064786\n ],\n [\n -119.59991455078124,\n 37.821175249016726\n ],\n [\n -119.79904174804688,\n 37.821175249016726\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-29","publicationStatus":"PW","scienceBaseUri":"573d841be4b0dae0d5e4c049","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albano, Christine M.","contributorId":169455,"corporation":false,"usgs":false,"family":"Albano","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":629694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629698,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171046,"text":"70171046 - 2016 - Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass","interactions":[],"lastModifiedDate":"2017-11-22T17:34:52","indexId":"70171046","displayToPublicDate":"2016-05-18T10:15:00","publicationYear":"2016","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":"Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass","docAbstract":"The Landsat 8 mission provides new opportunities for quantifying the distribution of above-ground carbon at moderate spatial resolution across the globe, and in particular drylands. Furthermore, coupled with structural information from space-based and airborne laser altimetry, Landsat 8 provides powerful capabilities for large-area, long-term studies that quantify temporal and spatial changes in above-ground biomass and cover. With the planned launch of ICESat-2 in 2017 and thus the potential to couple Landsat 8 and ICESat-2 data, we have unprecedented opportunities to address key challenges in drylands, including quantifying fuel loads, habitat quality, biodiversity, carbon cycling, and desertification.
\nIn this study, we explore the strengths of Landsat 8's Operational Land Imager (OLI) in estimating vegetation structure in a dryland ecosystem, and compare these results to Landsat 5's Thematic Mapper (TM). We also demonstrate the potential of OLI when coupled with light detection and ranging (lidar) in estimating vegetation cover and biomass in a dryland ecosystem. The OLI and TM predictions were similarly positive, indicating data from these sensors may be used in tandem for long-term time-series analysis. Results indicate shrub and herbaceous cover are well predicted with multi-temporal OLI data, and a combination of OLI and lidar derivatives improves most of these estimates and reduces uncertainty. For example, significant improvements were made for shrub cover (R2 = 0.64 and 0.78 using OLI only and both OLI and lidar data, respectively). Importantly, a time series of OLI, with some improvement from lidar, provides strong estimates of herbaceous cover (68% of the variance is explained with OLI alone). In contrast, OLI data explain roughly 59% of the variance in total shrub biomass, however approximately 71% of the variance is explained when combined with lidar derivatives.
\nTo estimate the potential synergies of OLI and ICESat-2 we used simulated ICESat-2 photon data to predict vegetation structure. In a shrubland environment with a vegetation mean height of 1 m and mean vegetation cover of 33%, vegetation photons are able to explain nearly 50% of the variance in vegetation height. These results, and those from a comparison site, suggest that a lower detection threshold of ICESat-2 may be in the range of 30% canopy cover and roughly 1 m height in comparable dryland environments and these detection thresholds could be used to combine future ICESat-2 photon data with OLI spectral data for improved vegetation structure. Overall, the synergistic use of Landsat 8 and ICESat-2 may improve estimates of above-ground biomass and carbon storage in drylands that meet these minimum thresholds, increasing our ability to monitor drylands for fuel loading and the potential to sequester carbon.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.02.039","usgsCitation":"Glenn, N.F., Neuenschwander, A., Vierling, L.A., Spaete, L., Li, A., Shinneman, D.J., Pilliod, D.S., Arkle, R., and McIlroy, S., 2016, Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass: Remote Sensing of Environment, v. 185, p. 233-242, https://doi.org/10.1016/j.rse.2016.02.039.","productDescription":"10 p.","startPage":"233","endPage":"242","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065442","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573d841ce4b0dae0d5e4c05b","contributors":{"authors":[{"text":"Glenn, Nancy F.","contributorId":95321,"corporation":false,"usgs":true,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neuenschwander, Amy","contributorId":169442,"corporation":false,"usgs":false,"family":"Neuenschwander","given":"Amy","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":629669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":629670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spaete, Lucas","contributorId":169444,"corporation":false,"usgs":false,"family":"Spaete","given":"Lucas","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Aihua","contributorId":169445,"corporation":false,"usgs":false,"family":"Li","given":"Aihua","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629672,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","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":629673,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":629667,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arkle, Robert 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":149893,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","email":"rarkle@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":629674,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":169446,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","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":629675,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70171048,"text":"70171048 - 2016 - Ecosystem engineering of harvester ants: Effects on vegetation in a sagebrush-steppe ecosystem","interactions":[],"lastModifiedDate":"2020-12-21T16:21:16.835759","indexId":"70171048","displayToPublicDate":"2016-05-18T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem engineering of harvester ants: Effects on vegetation in a sagebrush-steppe ecosystem","docAbstract":"Harvester ants are influential in many ecosystems because they distribute and consume seeds, remove vegetation, and redistribute soil particles and nutrients. Understanding the interaction between harvester ants and plant communities is important for management and restoration efforts, particularly in systems altered by fire and invasive species such as the sagebrush-steppe. Our objective was to evaluate how vegetation cover changed as a function of distance from Owyhee harvester ant (Pogonomyrmex salinus) nests within a sagebrush-steppe ecosystem. We sampled 105 harvester ant nests within southern Idaho, USA, that occurred in different habitats: annual grassland, perennial grassland, and native shrubland. The influence of Owyhee harvester ants on vegetation was larger at the edge of ant nests, but the relationship was inconsistent among plant species. Percent cover was positively associated with distance from harvester ant nests for plant species that were considered undesirable food sources and were densely distributed. However, percent cover was negatively associated with distance-from-nests for patchily distributed and desirable plant species. For some plant species, there was no change in cover associated with distance-from-nests. Total vegetation cover was associated with distance-from-nests in the shrubland habitat but not in the 2 grasslands. The dominant plant species in the shrubland habitat was a densely distributed shrub (winterfat, Krascheninnikovia lanata) that was defoliated by harvester ants. Our results suggest that Owyhee harvester ants increase spatial heterogeneity in plant communities through plant clearing, but the direction and magnitude of effect will likely be contingent on the dominant vegetation groups. This information may inform future management and plant restoration efforts in sagebrush-steppe by directly considering the islands of influence associated with harvester ant engineering.
","language":"English","publisher":"BioOne","doi":"10.3398/064.076.0109","usgsCitation":"Gosselin, E., Holbrook, J.D., Huggler, K., Brown, E., Vierling, K.T., Arkle, R., and Pilliod, D.S., 2016, Ecosystem engineering of harvester ants: Effects on vegetation in a sagebrush-steppe ecosystem: Western North American Naturalist, v. 76, no. 1, p. 82-89, https://doi.org/10.3398/064.076.0109.","productDescription":"8 p.","startPage":"82","endPage":"89","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064940","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":488974,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol76/iss1/8","text":"External Repository"},{"id":321372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Morley Nelson Snake River Birds of Prey National Conservation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.3397216796875,\n 43.074906886631524\n ],\n [\n -115.9112548828125,\n 43.074906886631524\n ],\n [\n -115.9112548828125,\n 43.38309377382831\n ],\n [\n -116.3397216796875,\n 43.38309377382831\n ],\n [\n -116.3397216796875,\n 43.074906886631524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573d841be4b0dae0d5e4c051","contributors":{"authors":[{"text":"Gosselin, Elyce","contributorId":169447,"corporation":false,"usgs":false,"family":"Gosselin","given":"Elyce","email":"","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":629677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Joseph D.","contributorId":140098,"corporation":false,"usgs":false,"family":"Holbrook","given":"Joseph","email":"","middleInitial":"D.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":629678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huggler, Katey","contributorId":169448,"corporation":false,"usgs":false,"family":"Huggler","given":"Katey","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":629679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Emily","contributorId":169449,"corporation":false,"usgs":false,"family":"Brown","given":"Emily","email":"","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":629680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vierling, Kerri T.","contributorId":140099,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":629681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arkle, Robert 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":149893,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","email":"rarkle@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":629682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":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":629676,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171055,"text":"70171055 - 2016 - A review of the relationships between drought and forest fire in the United States","interactions":[],"lastModifiedDate":"2016-06-16T11:18:51","indexId":"70171055","displayToPublicDate":"2016-05-18T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"A review of the relationships between drought and forest fire in the United States","docAbstract":"The historical and pre-settlement relationships between drought and wildfire are well documented in North America, with forest fire occurrence and area clearly increasing in response to drought. There is also evidence that drought interacts with other controls (forest productivity, topography, fire weather, management activities) to affect fire intensity, severity, extent, and frequency. Fire regime characteristics arise across many individual fires at a variety of spatial and temporal scales, so both weather and climate—including short- and long-term droughts—are important and influence several, but not all, aspects of fire regimes. We review relationships between drought and fire regimes in United States forests, fire-related drought metrics and expected changes in fire risk, and implications for fire management under climate change. Collectively, this points to a conceptual model of fire on real landscapes: fire regimes, and how they change through time, are products of fuels and how other factors affect their availability (abundance, arrangement, continuity) and flammability (moisture, chemical composition). Climate, management, and land use all affect availability, flammability, and probability of ignition differently in different parts of North America. From a fire ecology perspective, the concept of drought varies with scale, application, scientific or management objective, and ecosystem.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13275","usgsCitation":"Littell, J.S., Peterson, D.L., Riley, K.L., Liu, Y., and Luce, C.H., 2016, A review of the relationships between drought and forest fire in the United States: Global Change Biology, v. 22, no. 7, p. 2353-2369, https://doi.org/10.1111/gcb.13275.","productDescription":"17 p.","startPage":"2353","endPage":"2369","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070107","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":321369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-19","publicationStatus":"PW","scienceBaseUri":"573d841ae4b0dae0d5e4c036","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":629688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, David L.","contributorId":94643,"corporation":false,"usgs":false,"family":"Peterson","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":629689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riley, Karin L.","contributorId":169453,"corporation":false,"usgs":false,"family":"Riley","given":"Karin","email":"","middleInitial":"L.","affiliations":[{"id":25512,"text":"US Forest Service Fire Science Lab","active":true,"usgs":false}],"preferred":false,"id":629690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Yongquiang","contributorId":169454,"corporation":false,"usgs":false,"family":"Liu","given":"Yongquiang","email":"","affiliations":[{"id":25513,"text":"USDA Forest Service Southern Research Station","active":true,"usgs":false}],"preferred":false,"id":629691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luce, Charles H.","contributorId":65980,"corporation":false,"usgs":true,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":629692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170977,"text":"fs20163033 - 2016 - Building science-based groundwater tools and capacity in Armenia for the Ararat Basin","interactions":[],"lastModifiedDate":"2017-10-12T19:58:10","indexId":"fs20163033","displayToPublicDate":"2016-05-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3033","title":"Building science-based groundwater tools and capacity in Armenia for the Ararat Basin","docAbstract":"The U.S. Geological Survey (USGS) and U.S. Agency for International Development (USAID) began a study in 2016 to help build science-based groundwater tools and capacity for the Ararat Basin in Armenia. The growth of aquaculture and other uses in the Ararat Basin has been accompanied by increased withdrawals of groundwater, which has resulted in a reduction of artesian conditions (decreased springflow, well discharges, and water levels) including loss of flowing wells in many places (Armenia Branch of Mendez England and Associates, 2014; Yu and others, 2015). This study is in partnership with USAID/Armenia in the implementation of its Science, Technology, Innovation, and Partnerships (STIP) effort through the Advanced Science and Partnerships for Integrated Resource Development (ASPIRED) program and associated partners, including the Government of Armenia, Armenia’s Hydrogeological Monitoring Center, and the USAID Global Development Lab and its GeoCenter. Scientific tools will be developed through this study that groundwater-resource managers, such as those in the Ministry of Nature Protection, in Armenia can use to understand and predict the consequences of their resource management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163033","collaboration":"United States Agency for International Development","usgsCitation":"Carter, J.M., Valder, J.F., Anderson, M.T., Meyer, Patrick, and Eimers, J.L., 2016, Building science-based groundwater tools and capacity in Armenia for the Ararat Basin: U.S. Geological Survey Fact Sheet 2016–3033, 4 p., https://dx.doi.org/10.3133/fs20163033.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075909","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":321330,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3033/fs20163033.pdf","text":"Fact Sheet","size":"1.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2016–3033"},{"id":321329,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3033/coverthb.jpg"}],"country":"Armenia, Turkey","otherGeospatial":"Ararat Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 44.75,\n 40.5\n ],\n [\n 44.75,\n 39.4\n ],\n [\n 43.75,\n 39.4\n ],\n [\n 43.75,\n 40.5\n ],\n [\n 44.75,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
This study examined links among fluvial, aeolian, and hillslope geomorphic processes that affect archeological sites and surrounding landscapes in the Colorado River corridor downstream from Glen Canyon Dam, Arizona. We assessed the potential for Colorado River sediment to enhance the preservation of river-corridor archeological resources through aeolian sand deposition or mitigation of gully erosion. By identifying locally prevailing wind directions, locations of modern sandbars, and likely aeolian-transport barriers, we determined that relatively few archeological sites are now ideally situated to receive aeolian sand supply from sandbars deposited by recent controlled floods. Whereas three-fourths of the 358 river-corridor archeological sites we examined include Colorado River sediment as an integral component of their geomorphic context, only 32 sites currently appear to have a high degree of connectivity (coupled interactions) between modern fluvial sandbars and sand-dominated landscapes downwind. This represents a substantial decrease from past decades, as determined by aerial-photograph analysis. Thus, we infer that recent controlled floods have had a limited, and declining, influence on archeological-site preservation.
\nWithin the study area, overland-flow (gully) erosion is less severe in sand landscapes with active aeolian sand than in landscapes that lack aeolian transport; gullies terminate more commonly in active sand (sand that is mobile by wind rather than stabilized by biologic soil crust). We infer that these characteristics largely result from aeolian sand transport being an effective gully-limiting and gully-annealing mechanism. Aeolian sand activity in the river corridor varies substantially as a function of reach morphology and dominant wind direction relative to the river-corridor orientation, factors that control accommodation space for river-derived sand and the modern sand supply to aeolian dunes. These attributes, together with an inverse correlation between aeolian sand activity and gully occurrence, define varying degrees of net long-term gully-erosion risk for sediment deposits and associated archeological sites in different regions of the river corridor. Over most of the river corridor, including some of the archeologically richest regions, sand is too inactive with respect to aeolian transport to anneal gullies effectively. At eight selected archeological sites that we studied with high-resolution terrestrial lidar scans for more than a year, sand loss by overland flow (gully erosion) and aeolian deflation generally exceeded deposition, such that erosion dominated over most monitoring intervals—even at four sites with strong connectivity to modern sand supply.
\nThe Glen Canyon reach of the river corridor appears especially vulnerable to gully erosion. Among the sites that we monitored in detail, erosion generally dominated over deposition to a greater degree at four Glen Canyon sites with no modern sand supply than at four Marble–Grand Canyon sites with aeolian sand supply from controlled-flood sandbars. Although gross annual-scale erosion rates were similar among the Glen Canyon sites and among the Marble–Grand Canyon sites, a relative lack of depositional processes led to greater net erosion at the Glen Canyon sites. Having found no differences in weather patterns to suggest greater erosive forcing in Glen Canyon, and no conclusively influential differences in the slope or watershed area contributing to gully formation, we attribute the greater erosion at the Glen Canyon sites to a combination of inherent geomorphic context (high terraces that do not receive modern sediment supply) and pronounced effects of postdam sediment-supply limitation.
\nWe conclude that most of the river-corridor archeological sites are at elevated risk of net erosion under present dam operations. In the present flow regime, controlled floods do not simulate the magnitude or frequency of natural floods, and are not large enough to deposit sand at elevations that were flooded at annual to decadal intervals in predam time. For archeological sites that depend upon river-derived sand, we infer elevated erosion risk owing to a combination of reduced sand supply (both fluvial and aeolian) through (1) the lower-than-natural flood magnitude, frequency, and sediment supply of the controlled-flooding protocol; (2) reduction of open, dry sand area available for wind redistribution under current normal (nonflood) dam operations, which do not include flows as low as natural seasonal low flows and do include substantial daily flow fluctuations; and (3) impeded aeolian sand entrainment and transport owing to increased riparian vegetation growth in the absence of larger, more-frequent floods. If dam operations were to increase the supply of sand available for windblown transport—for example, through larger floods, sediment augmentation, or increased fluvial sandbar exposure by low flows—and also decrease riparian vegetation, the prevalence of active aeolian sand could increase over time, and the propensity for unmitigated gully erosion could decrease. Although the evolution of river-corridor landscapes and archeological sites has been altered fundamentally by the lack of large, sediment-rich floods (flows on the order of 5,000 m3/s), some combination of sediment-rich flows above 1,270 m3/s, seasonal flows below 226 m3/s, and riparian-vegetation removal might increase the preservation potential for sand-dependent archeological resources in the Colorado River corridor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1825","usgsCitation":"East, A.E., Collins, B.D., Sankey, J.B., Corbett, S.C., Fairley, H.C., and Caster, J., 2016, Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona: U.S. Geological Survey Professional Paper 1825, 104 p., https://dx.doi.org/10.3133/pp1825.","productDescription":"ix, 104 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066266","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1825/coverthb.jpg"},{"id":321262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1825/pp1825.pdf","text":"Report","size":"30.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP1825"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River corridor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.555,\n 37.05\n ],\n [\n -114.555,\n 35.45\n ],\n [\n -110.75,\n 35.45\n ],\n [\n -110.75,\n 37.05\n ],\n [\n -114.555,\n 37.05\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m). The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).
\nTwo different clear-water flight missions were conducted over the U.S. Navy's South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.
\nWe also conducted a near-simultaneous single-beam jet-ski-based sonar survey of selected transects ranging from 1 to 33 m depth in the same area. The near-concurrent jet ski data were used to evaluate the EAARL-B performance over the depth range from 0.9 to 10 m. The more timely jet ski data were necessary because the primary reference dataset was 9 years old, and areas shallower than 6.5 m are dominated by shifting sand. We determined the jet ski data were not useful as a calibration reference in water deeper than 10 m due to large uncertainty in the vertical measurement introduced by the lack of any sensor orientation data, that is, for pitch, roll, and heading to correct the measured slant range to a vertical measurement.
\nThe resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161048","usgsCitation":"Wright, C.W., Kranenburg, C.J., Troche, R.J., Mitchell, R.W., and, Nagle, D.B., 2016, Depth calibration of the experimental advanced airborne research lidar, EAARL-B: U.S. Geological Survey Open-File Report 2016–1048, 23 p., https://dx.doi.org/10.3133/ofr20161048.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061552","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1048/coverthb.jpg"},{"id":320951,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"Data Release"},{"id":320938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1048/ofr20161048.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1048"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
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(727) 502-8000
http://coastal.er.usgs.gov/
Geolocators are useful for tracking movements of long-distance migrants, but potential negative effects on birds have not been well studied. We tested for effects of geolocators (0.8–2.0 g total, representing 0.1–3.9 % of mean body mass) on 16 species of migratory shorebirds, including five species with 2–4 subspecies each for a total of 23 study taxa. Study species spanned a range of body sizes (26–1091 g) and eight genera, and were tagged at 23 breeding and eight nonbreeding sites. We compared breeding performance and return rates of birds with geolocators to control groups while controlling for potential confounding variables.
\nWe detected negative effects of tags for three small-bodied species. Geolocators reduced annual return rates for two of 23 taxa: by 63 % for semipalmated sandpipers and by 43 % for the arcticola subspecies of dunlin. High resighting effort for geolocator birds could have masked additional negative effects. Geolocators were more likely to negatively affect return rates if the total mass of geolocators and color markers was 2.5–5.8 % of body mass than if tags were 0.3–2.3 % of body mass. Carrying a geolocator reduced nest success by 42 % for semipalmated sandpipers and tripled the probability of partial clutch failure in semipalmated and western sandpipers. Geolocators mounted perpendicular to the leg on a flag had stronger negative effects on nest success than geolocators mounted parallel to the leg on a band. However, parallel-band geolocators were more likely to reduce return rates and cause injuries to the leg. No effects of geolocators were found on breeding movements or changes in body mass. Among-site variation in geolocator effect size was high, suggesting that local factors were important.
\nNegative effects of geolocators occurred only for three of the smallest species in our dataset, but were substantial when present. Future studies could mitigate impacts of tags by reducing protruding parts and minimizing use of additional markers. Investigators could maximize recovery of tags by strategically deploying geolocators on males, previously marked individuals, and successful breeders, though targeting subsets of a population could bias the resulting migratory movement data in some species.
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