While we have a good understanding in many systems of the effects of single variable changes on organisms, we understand far less about how variables act in concert to affect living systems, where interactions among variables can lead to unanticipated results. We used mixed-effect models to evaluate the effects of multiple variables that we expected to play a role in the early reproductive stages of a North Pacific seabird, the black-legged kittiwake Rissa tridactyla, during 1992-2008 using data collected on known-aged individuals. Our work revealed the potential for contrasting stressor effects across successive stages of reproduction. Bird age, timing of egg laying, and winter ENSO conditions best explained individual laying success, such that laying success was greater when parents were older, the average winter ENSO index was positive (as occurs during El Niño episodes), and the median laying date for the colony was earlier. Age and salmon run timing (a proxy for predator presence at the colony) best explained hatching success, such that hatching success was greater when parents were older and when salmon runs were early. Identifying such differential effects of multiple stressors across consecutive reproductive stages can greatly enhance our ability to interpret trends and manage populations in the face of changes currently occurring in living systems.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13162","usgsCitation":"McKnight, A., Irons, D., Loftin, C., McKinney, S., and Olsen, B., 2020, Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla: Marine Ecology Progress Series, v. 633, p. 207-223, https://doi.org/10.3354/meps13162.","productDescription":"17 p.","startPage":"207","endPage":"223","ipdsId":"IP-088508","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"633","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKnight, Aly","contributorId":272505,"corporation":false,"usgs":false,"family":"McKnight","given":"Aly","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irons, David B.","contributorId":272506,"corporation":false,"usgs":false,"family":"Irons","given":"David B.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKinney, Shawn T.","contributorId":272507,"corporation":false,"usgs":false,"family":"McKinney","given":"Shawn T.","affiliations":[],"preferred":false,"id":832008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, Brian J.","contributorId":272508,"corporation":false,"usgs":false,"family":"Olsen","given":"Brian J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":832009,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211640,"text":"70211640 - 2020 - Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","interactions":[],"lastModifiedDate":"2020-08-06T19:55:59.712564","indexId":"70211640","displayToPublicDate":"2020-01-09T09:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","title":"Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis)","docAbstract":"Invasive species are a major threat to the persistence of native species, particularly in systems where ephemeral aquatic habitats have been replaced by permanent water and predators, such as fish, have been introduced. Within the Altar Valley, Arizona, the invasive American bullfrog, Lithobates catesbeianus (formerly Rana catesbeianus), has been successfully eradicated to help recover Chiricahua leopard frogs (Lithobates chiricahuensis). However, other nonnative predators including sunfish (Lepomis) are present in some permanent water bodies. During four consecutive years (2014–2017), we detected both the federally threatened Chiricahua leopard frog and sunfish at one permanent water body in the Altar Valley. This suggests that despite the potential negative effect of predatory fish on amphibians, there may be conditions where the Chiricahua leopard frog can co-occur with this nonnative predator. A better understanding of rare situations of co-occurrence with nonnative predators may contribute to our understanding of why co-occurrence happens in some, but not all, systems and whether conservation strategies can be developed in situations where eradication of nonnative predators is infeasible.
","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-64-1-69","usgsCitation":"Howell, P., Sigafus, B.H., Hossack, B.R., and Muths, E.L., 2020, Co-occurence of Chiricahua leopard frogs (Lithobates chiricahuensis) with sunfish (Lepomis): The Southwestern Naturalist, v. 64, no. 1, p. 69-72, https://doi.org/10.1894/0038-4909-64-1-69.","productDescription":"4 p.","startPage":"69","endPage":"72","numberOfPages":"4","ipdsId":"IP-091934","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":377105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Alter Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.785888671875,\n 31.51767878128718\n ],\n [\n -111.19537353515624,\n 31.51767878128718\n ],\n [\n -111.19537353515624,\n 32.16631295696736\n ],\n [\n -111.785888671875,\n 32.16631295696736\n ],\n [\n -111.785888671875,\n 31.51767878128718\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":794900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":794902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3121 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3121","contributorId":236995,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":794903,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207989,"text":"70207989 - 2020 - Challenges for leveraging citizen science to support statistically robust monitoring programs","interactions":[],"lastModifiedDate":"2020-01-23T06:36:56","indexId":"70207989","displayToPublicDate":"2020-01-09T06:35:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for leveraging citizen science to support statistically robust monitoring programs","docAbstract":"Large samples and long time series are often needed for effective broad-scale monitoring of status and trends in wild populations. Obtaining those sample sizes can be more feasible when volunteers contribute to the dataset, but volunteer-selected sites are not always representative of a population. Previous work to account for biased site selection has relied on knowledge of covariates to explain differences between site types, but such knowledge is often unavailable. For cases where relevant covariates have not been defined, we used a simulation study to identify the consequences of including non-probabilistically selected sites (NP sites) in addition to sites selected from a probability-based design (P sites), test modeling frameworks that might correct for biases, and evaluate whether those frameworks could allow NP sites to reduce the sampling requirement for P sites and potentially reduce costs of monitoring. We informed the simulation with pilot data from surveys of monarch butterflies and their obligate larval host plant, milkweed. We found strong biases in NP sites versus P sites in density and trends of monarchs and milkweed. Modeling frameworks that accounted for site type with a group effect or that strongly downweighted NP sites successfully produced unbiased estimates. However, sampling more NP sites typically did not improve accuracy or precision, and adding NP sites sometimes required also adding P sites to prevent biases. Further work on novel modeling frameworks would be useful to allow citizen-science data to contribute useful information to conservation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2020.108411","usgsCitation":"Weiser, E.L., Diffendorfer, J., Lopez-Hoffman, L., Semmens, D., and Thogmartin, W.E., 2020, Challenges for leveraging citizen science to support statistically robust monitoring programs: Biological Conservation, v. 242, 108411, 10 p., https://doi.org/10.1016/j.biocon.2020.108411.","productDescription":"108411, 10 p.","ipdsId":"IP-112580","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":458175,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2020.108411","text":"Publisher Index Page"},{"id":371491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"242","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":780046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":780048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":780050,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207244,"text":"sir20195141 - 2020 - Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","interactions":[],"lastModifiedDate":"2022-04-25T20:16:09.086144","indexId":"sir20195141","displayToPublicDate":"2020-01-08T16:45:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5141","displayTitle":"Water-Balance Techniques for Determining Available Soil-Water Storage for Selected Sandy and Clay Soil Study Sites in Cass County, North Dakota, 2016–17","title":"Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service, collected field and remotely sensed data on precipitation, evapotranspiration (ET), and soil-water content to determine available soil-water storage (AWS) at six study sites on sandy and clay soils in Cass County, North Dakota. Data were collected at all the study sites from May 1–October 31, 2016, and from May 1–October 24, 2017. Estimated daily AWS was determined using daily meteorological and potential evapotranspiration (PET) data obtained from various climate stations, and estimated monthly AWS was determined using monthly meteorological and PET data and monthly ET data determined using the Operational Simplified Surface Energy Balance model. AWS during 2016 and 2017 was determined at daily and monthly time steps because of data availability and to assess results using varying time steps. Comparisons of measured and estimated daily values of AWS at the Brewer Lake site indicated poor agreement during May–October 2016 and May–October 2017. Comparisons of measured and estimated daily values of AWS at the Embden East and Embden West sites indicated poor and fair agreement respectively. At the Lynchburg Crop and Lynchburg Grass sites, comparisons of measured and estimated daily values of AWS indicated fair and good relations, respectively, even with the possible effects of soil cracks. Mean estimated values of daily runoff plus soil percolation for the four sandy soil sites indicated that a maximum of about 19 percent of the estimated runoff plus soil percolation could be considered runoff and that the remaining 81 percent could be considered soil percolation, and for the two clay soil sites about 13 percent of the runoff plus soil percolation could have been considered runoff and about 87 percent could have been considered soil percolation. Results indicated little difference between using monthly PET or monthly ET in water-balance equations to estimate monthly AWS for the grouped sandy soil sites, and only slightly better results were obtained using monthly PET than monthly ET to estimate monthly AWS for the grouped clay soil study sites. Overall, the monthly water-balance models did not perform as well as the daily water-balance models for determining AWS at the six study sites. Additional data collection from a longer-period study and adjustments to the models may improve results from the monthly water-balance techniques.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195141","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service","usgsCitation":"Vining, K.C., 2020, Water-balance techniques for determining available soil-water storage for selected sandy and clay soil study sites in Cass County, North Dakota, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5141, 39 p., https://doi.org/10.3133/sir20195141.","productDescription":"Report: vii, 39 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-098347","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399616,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109584.htm"},{"id":371052,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG2ILI","text":"USGS data 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Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
We describe 2 artificial stream experiments that exposed aquatic insect communities to zinc (Zn), copper (Cu), and cadmium (year 2014) and to Zn, Cu, and nickel (year 2015). The testing strategy was to concurrently expose insect communities to single metals and mixtures. Single-metal tests were repeated to evaluate the reproducibility of the methods and year-to-year variability. Metals were strongly accumulated in sediments, periphyton, and insect (caddisfly) tissues, with the highest concentrations occurring in periphyton. Sensitive mayflies declined in metal treatments, and effect concentrations could be predicted effectively from metal concentrations in either periphyton or water. Most responses were similar in the replicated tests, but median effect concentration values for the mayfly Rhithrogena sp. varied 20-fold between the tests, emphasizing the difficulty comparing sensitivities across studies and the value of repeated testing. Relative to the single-metal responses, the toxicity of the mixtures was either approximately additive or less than additive when calculated as the product of individual responses (response addition). However, even less-than-additive relative responses were sometimes greater than responses to similar concentrations tested singly. The ternary mixtures resulted in mayfly declines at concentrations that caused no declines in the concurrent single-metal tests. When updating species-sensitivity distributions (SSDs) with these results, the mayfly responses were among the most sensitive 10th percentile of available data for all 4 metals, refuting older literature placing mayflies in the insensitive portion of metal SSDs. Testing translocated aquatic insect communities in 30-d artificial streams is an efficient approach to generate multiple species effect values under quasi-natural conditions that are relevant to natural streams.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4663","usgsCitation":"Mebane, C.A., Schmidt, T., Miller, J.L., and Balistrieri, L.S., 2020, Bioaccumulation and toxicity of cadmium, copper, nickel, and zinc and their mixtures to aquatic insect communities: Environmental Toxicology and Chemistry, v. 39, no. 4, p. 812-833, https://doi.org/10.1002/etc.4663.","productDescription":"22 p.","startPage":"812","endPage":"833","ipdsId":"IP-110553","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458177,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4663","text":"Publisher Index Page"},{"id":401151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":843833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Janet L.","contributorId":218842,"corporation":false,"usgs":false,"family":"Miller","given":"Janet","email":"","middleInitial":"L.","affiliations":[{"id":39922,"text":"No affilcation","active":true,"usgs":false}],"preferred":false,"id":843834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210164,"text":"70210164 - 2020 - Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA","interactions":[],"lastModifiedDate":"2020-05-19T14:55:14.610714","indexId":"70210164","displayToPublicDate":"2020-01-08T09:49:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA","docAbstract":"Nitrogen pollution in watersheds containing significant\ncropland area is generally problematic. Conservation practices intended\nto reduce nitrate-N (NO3--N) export from watersheds are being implemented\nby many regions without necessary tools to assess effectiveness of these\nabatement tools. A commonly used herbicide metolachlor degrades in the\nvadose zone of croplands to form two metabolites (metolachlor ethane\nsulfonic acid (MESA) and metolachlor oxanilic acid (MOXA)) which are both\nhighly soluble in soils. Study of metabolite fates in a first order\nwatershed provided evidence that transport of these metabolites to stream\nwater is highly correlated to transport of the agricultural NO3--N that\nalso forms in the cropland vadose zone. Linear models describing the\nrelationships of stream flux of MESA and MOXA to NO3--N flux generated\ngoodness of fit values of 0.93 and 0.82 respectively. These findings\nsupport a conclusion that both MESA and MOXA act as excellent transport\nanalogs of NO3- and become strongly correlated to agricultural NO3--N\nleaching from the cropland vadose zone. Moreover, their use as\nconservative tracers in agricultural watersheds can provide valuable\ninformation concerning movement and fate of agricultural nitrogen at\nwatershed scales of observation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136590","usgsCitation":"Rice, C., Hively, W.D., McCarty, G.W., and Hapeman, C., 2020, Fluxes of agricultural nitrogen and metolachlor metabolites are highly correlated in a first order stream in Maryland, USA: Science of the Total Environment, v. 716, 136590, 7 p., https://doi.org/10.1016/j.scitotenv.2020.136590.","productDescription":"136590, 7 p.","ipdsId":"IP-113701","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":458180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.136590","text":"Publisher Index 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\"}}]}","volume":"716","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rice, Cliff 0000-0002-7702-9376","orcid":"https://orcid.org/0000-0002-7702-9376","contributorId":224744,"corporation":false,"usgs":false,"family":"Rice","given":"Cliff","email":"","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":789364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":210993,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":789365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":789366,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hapeman, Cathleen","contributorId":224745,"corporation":false,"usgs":false,"family":"Hapeman","given":"Cathleen","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":789367,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219522,"text":"70219522 - 2020 - Components and predictors of biological soil crusts vary at the regional vs. plant community scales","interactions":[],"lastModifiedDate":"2021-04-12T13:30:31.762854","indexId":"70219522","displayToPublicDate":"2020-01-08T08:28:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Components and predictors of biological soil crusts vary at the regional vs. plant community scales","docAbstract":"Although biological soil crusts (biocrusts) occur globally in arid and semi-arid environments, most of our knowledge of biocrust cover and ecology is from a relatively small number of locations worldwide. Some plant communities are known to have high cover of biocrusts, but the abundance of biocrusts is largely undocumented in most plant communities. Using a data driven approach, we identified 16 plant communities based on plant cover from the Assessment, Inventory, and Monitoring Strategy data from the Bureau of Land Management (AIM, 5,200 plots). We found that abundance of lichens and mosses varies among communities, but that both components of biocrusts are present in all plant communities. Biocrusts are indicators of two of these communities: one that is defined by high cover of mosses and basin big sagebrush and one that is defined by high cover of lichens and shadscale saltbush. Using non-parametric multiplicative regression, we evaluated a suite of abiotic and disturbance variables to assess the degree to which climate and soils are associated with the abundance of lichens and mosses at the regional scale. At the regional scale, soil depth and maximum vapor pressure deficit were found to be strongly associated with the abundance of lichens and January minimum temperature dictated the abundance of mosses. At the scale of plant communities, community specific metrics of soils and climate were better able to explain the abundance of biocrusts. Our demonstration of the presence of biocrusts across the western US suggests that studies on ecosystem function could include these organisms because they are present in all plant communities, maintain arguably stronger associations with climatic variation, are directly associated with soils, and contribute to ecosystem functions that are not solely maintained by vascular plants.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2019.00449","usgsCitation":"Condon, L.A., and Pyke, D.A., 2020, Components and predictors of biological soil crusts vary at the regional vs. plant community scales: Frontiers in Ecology and Evolution, v. 7, 449, 10 p., https://doi.org/10.3389/fevo.2019.00449.","productDescription":"449, 10 p.","ipdsId":"IP-101902","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00449","text":"Publisher Index Page"},{"id":385005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","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":813925,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209229,"text":"70209229 - 2020 - Characterization of the genetic structure of four sucker species in the Klamath River. Final Report","interactions":[],"lastModifiedDate":"2020-03-26T06:42:12","indexId":"70209229","displayToPublicDate":"2020-01-08T06:47:21","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Characterization of the genetic structure of four sucker species in the Klamath River. Final Report","docAbstract":"Four species of suckers (family Catostomidae) inhabit the Klamath River Basin of Oregon and California: Lost River suckers (LRS; Deltistes luxatus), shortnose suckers (SNS; Chasmistes brevirostris), Klamath largescale suckers (KLS; Catostomus snyderi), and Klamath smallscale suckers (KSS; Catostomus rimiculus). All but Klamath smallscale suckers are endemic and restricted to the Klamath River Basin where they occur sympatrically in large lakes and reservoirs, including the Lost River and Klamath Lake subbasins (Figure 1; USFWS 2012).\nPopulation declines, primarily due to loss or degradation of spawning, rearing, and adult habitat, have resulted in Lost River and shortnose suckers being listed as endangered throughout their entire range under the U.S. Endangered Species Act (USFWS 1988).\n\nContinued population declines coupled with failed adult recruitment prompted the USFWS to initiate an assisted rearing program in 2015 as a part of their recovery strategy (Childress et al. 2019). The program was designed to maintain as much genetic diversity as possible while improving recruitment by averting high early life stage mortality (Day et al. 2017). However, while assisted rearing efforts are targeted towards endangered LRS and SNS, species differentiation of larval and juvenile suckers is problematic in the Klamath River Basin. This, in turn, complicates the management of these species as well as the population modeling used to evaluate recovery efforts. Maintaining as much as possible of the genetic resources, or “evolutionary legacy” of a species is a goal common to conservation and endangered species recovery strategies. Inappropriate assumptions regarding species’ evolutionary lineages, and genetic characteristics may lead to the mismanagement of an endangered species through a failure to recognize and appropriately manage species boundaries and genetic population structure.\n\nDespite a considerable amount of research, the partitioning of genetic diversity within and among the four species of suckers in the Klamath River Basin remains unclear. Previously developed genetic markers are effective at differentiating some species, but fail to effectively differentiate all four species of suckers in the basin (Tranah et al. 2001; Wagman 2003; Tranah and May 2006; Hoy and Ostberg 2015; Dowling et al. 2016). Peer-reviewed publications describing the morphological characteristics of (Markle et al. 2005) and genetic relationships\n \namong (Dowling et al. 2016; Tranah and May 2006) Klamath River Basin suckers have not resolved uncertainties regarding the systematic relationships among the four currently recognized taxa. Specifically, genetic and morphological data generally support LRS and KSS as being distinct entities, but genetic evidence does not support a distinction between KLS and SNS. All three publications above refer to unpublished information regarding ecological differences between KLS and SNS as evidence to support the existence of two entities. However, the authors also acknowledge that overlap in morphological characters (Markle et al. 2005) and a lack of genetic differentiation (Dowling et al. 2016; Tranah and May 2006) between KLS and SNS raises the question of their specific identity. This is particularly problematic in the Lost River subbasin, where overlap in morphological characters between KLS and SNS is greatest.\n\nIn our opinion, the basis of the strong genetic similarity between KLS and SNS has not been resolved. Morphological characters mostly support the existence of two distinct species, while genetic characters do not (i.e., genetic divergence between KLS and SNS is less than divergence among populations of each species; (Smith et al. 2015). Some have suggested that introgressive hybridization may have resulted in a lack of genetic differentiation between KLS and SNS and a breakdown of monophyletic species (Dowling et al. 2016; Tranah and May 2006), and that this hybridization may be an important process in","language":"English","publisher":"U.S. Fish and Wildlife Service","collaboration":"Bureau of Reclamation","usgsCitation":"Smith, M., Von Bargen, J., Smith, C.A., Miller, M.A., Rasmussen, J., and Hewitt, D.A., 2020, Characterization of the genetic structure of four sucker species in the Klamath River. Final Report, 32 p.","productDescription":"32 p.","ipdsId":"IP-115877","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":373490,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/aftc/Reports.cfm"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.695068359375,\n 40.88029480552824\n ],\n [\n -120.9375,\n 40.88029480552824\n ],\n [\n -120.9375,\n 42.83569550641452\n ],\n [\n -123.695068359375,\n 42.83569550641452\n ],\n [\n -123.695068359375,\n 40.88029480552824\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Matt","contributorId":223557,"corporation":false,"usgs":false,"family":"Smith","given":"Matt","email":"","affiliations":[{"id":40741,"text":"USFWS, Abernathy Fish Technology Center, Longview, WA","active":true,"usgs":false}],"preferred":false,"id":785470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Von Bargen, Jennifer","contributorId":223558,"corporation":false,"usgs":false,"family":"Von Bargen","given":"Jennifer","email":"","affiliations":[{"id":40741,"text":"USFWS, Abernathy Fish Technology Center, Longview, WA","active":true,"usgs":false}],"preferred":false,"id":785471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Christian A.","contributorId":200768,"corporation":false,"usgs":false,"family":"Smith","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":785472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Michael A.","contributorId":85920,"corporation":false,"usgs":false,"family":"Miller","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":785473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Josh","contributorId":223559,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Josh","email":"","affiliations":[{"id":40742,"text":"USFWS, Klamath Falls Fish and Wildlife Office, Klamath Falls, OR","active":true,"usgs":false}],"preferred":false,"id":785474,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":785475,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208607,"text":"70208607 - 2020 - Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","interactions":[],"lastModifiedDate":"2020-02-21T11:50:49","indexId":"70208607","displayToPublicDate":"2020-01-08T06:45:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","docAbstract":"This study uses the explores the viability of a proxy model calibration strategy through assessment of the spatiotemporal variability of surface-depression storage and runoff generated with the U.S. Geological Survey’s National Hydrologic Model (NHM) infrastructure for hydrologic response units (HRUs; n=109,951) across the conterminous United States (CONUS). Simulated values for each HRU of daily surface-depression storage (treated as a decimal fraction of total possible volume) and monthly normalized runoff (0 to 1) values were calculated using Spearman’s rho at monthly and annual aggregations. Locations where values are correlated show where previously-developed proxy calibration strategies are likely to be effective. In addition, differences in the correlation for monthly and annual time scale aggregations show which time scale drives surface-depression storage processes in the NHM. Results show overall long-term (annual) correlation is more common than short-term (monthly) correlation over the CONUS; however, summary statistics for eighty-six ecoregions show five with higher ranges of monthly relative to annual Spearman’s rank coefficient values. This landscape-scale analysis shows simulations aggregated to an annual time scale are generally more dominant for the CONUS; however, simulations aggregated to monthly, short-term time scales are more dominant in focused areas where surface-depression storage processes are investigated.","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12826","usgsCitation":"Driscoll, J.M., Hay, L., Vanderhoof, M.K., and Viger, R.J., 2020, Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States: Journal of the American Water Resources Association, v. 56, no. 1, p. 16-29, https://doi.org/10.1111/1752-1688.12826.","productDescription":"14 p.","startPage":"16","endPage":"29","ipdsId":"IP-093569","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":458188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12826","text":"Publisher Index Page"},{"id":372483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n 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Branch","active":true,"usgs":true}],"preferred":true,"id":782704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":782706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":782707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208949,"text":"70208949 - 2020 - Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California","interactions":[],"lastModifiedDate":"2020-03-09T06:45:36","indexId":"70208949","displayToPublicDate":"2020-01-08T06:43:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California","docAbstract":"We deployed a network of 68 three-component geophones on the slow moving Two\n\tTowers earthflow in northern California. We compute horizontal-to-vertical spectral ratios\n\t(HVSRs) from the ambient seismic field. The HVSRs have two prominent peaks, one near\n\t1.23 Hz and another between 4 and 8 Hz at most stations. The 1.23 Hz resonance is a property of the background noise field and may be due to a velocity contrast at a few hundred\n\tmeters depth. We interpret the higher frequency peaks as being related to slide deposits and invert the spectral ratios for shallow velocity structure using in situ thickness measurements\n\tas a priori constraints on the inversion. The thickness of the shallowest, low-velocity layer\n\tis systematically larger than landslide thicknesses inferred from inclinometer data acquired\n\tsince 2013. Given constraints from field observations and boreholes, the inversion may reflect the thickness of deposits of an older slide that is larger in spatial extent and depth than\n\tthe currently active slide. Because the HVSR peaks measured at Two Towers are caused by shallow slide deposits and represent frequencies that will experience amplification during\n\tearthquakes, the depth of the actively sliding mass may be less relevant for assessing potential slide volume and associated hazard than the thicknesses determined by our inversions.\n\tMore generally, our results underscore the utility of combining both geotechnical measurements and subsurface imaging for landslide characterization and hazard assessment.","language":"English","publisher":"GSW","doi":"10.1785/0220190206","usgsCitation":"Thomas, A.M., Spica, Z., Bodmer, M., Schulz, W.H., and Roering, J., 2020, Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California: Seismological Research Letters, v. 91, no. 2A, p. 913-920, https://doi.org/10.1785/0220190206.","productDescription":"8 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canopy","interactions":[],"lastModifiedDate":"2020-02-28T06:31:32","indexId":"70208745","displayToPublicDate":"2020-01-08T06:28:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy","docAbstract":"Modelling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy-balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in RMSE). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned, and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parametrizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parametrizations without necessitating complex high-resolution models.","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026129","usgsCitation":"Mazzotti, G., Essery, R., Moeser, C.D., and Jonas, T., 2020, Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy: Water Resources Research, v. 56, no. 1, e2019WR026129, 22 p., https://doi.org/10.1029/2019WR026129.","productDescription":"e2019WR026129, 22 p.","ipdsId":"IP-112070","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":458191,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.research.ed.ac.uk/en/publications/941ef274-b54b-48d0-8263-ae1287bd8584","text":"External Repository"},{"id":372718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[9.59423,47.52506],[9.63293,47.3476],[9.47997,47.10281],[9.93245,46.92073],[10.4427,46.89355],[10.36338,46.48357],[9.92284,46.3149],[9.18288,46.44021],[8.96631,46.03693],[8.48995,46.00515],[8.31663,46.16364],[7.75599,45.82449],[7.27385,45.77695],[6.84359,45.99115],[6.5001,46.42967],[6.02261,46.27299],[6.03739,46.72578],[6.76871,47.28771],[6.73657,47.5418],[7.1922,47.44977],[7.46676,47.62058],[8.3173,47.61358],[8.52261,47.83083],[9.59423,47.52506]]]},\"properties\":{\"name\":\"Switzerland\"}}]}","volume":"56","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazzotti, Giulia","contributorId":222821,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Giulia","email":"","affiliations":[{"id":40604,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland and Laboratory of Hydraulics, Hydrology and Glaciology, ETHZ, Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":783256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essery, Richard","contributorId":222822,"corporation":false,"usgs":false,"family":"Essery","given":"Richard","email":"","affiliations":[{"id":40605,"text":"School of Geosciences, University of Edinburgh, Edinburgh, UK","active":true,"usgs":false}],"preferred":false,"id":783257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moeser, C. 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In addition, changes in hydrology and forest management have altered the structure and composition of the remaining forests. To ameliorate the detrimental impact of these changes on wildlife, conservation plans have emphasized restoration to increase interior forest habitat, while presuming negligible loss of extant forest in this ecoregion. Without conservation-protection, however, existing forests are subject to conversion to other uses. We assessed the conservation-protection status of land within the Mississippi Alluvial Valley and found that only 10% of total area was protected. Even so, 28% of extant forest was in the current conservation estate. Based on forest patch area, location, and hydrologic influence, we prioritized the attributed need of forest patches for additional conservation-protection. For forest bird conservation, we found 4712 forest patches warranted consideration for conservation-protection but only 109 of these forest patches met our conservation threshold of >2000 ha of core-forest that was >250 m from an edge. Overall, 35% of the area of forest patches considered for conservation-protection was protected within the conservation estate. However, those forest patches identified as most in need of conservation-protection had <10% of their area protected within the current conservation estate.","language":"English","publisher":"MDPI ","doi":"10.3390/f11010075","usgsCitation":"Elliott, A., Mini, A., McKnight, S.K., and Twedt, D.J., 2020, Conservation–Protection of forests for wildlife in the Mississippi Alluvial Valley: Forests, v. 11, no. 1, 75, 14 p., https://doi.org/10.3390/f11010075.","productDescription":"75, 14 p.","ipdsId":"IP-112335","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458192,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f11010075","text":"Publisher Index Page"},{"id":437174,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90V76SY","text":"USGS data release","linkHelpText":"Forests in the Mississippi Alluvial Valley Lacking Sufficient Conservation Protection"},{"id":371487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.1318359375,\n 37.125286284966805\n ],\n [\n -90.703125,\n 36.527294814546245\n ],\n [\n -91.7138671875,\n 34.95799531086792\n ],\n [\n -92.2412109375,\n 33.211116472416855\n ],\n [\n -92.0654296875,\n 31.840232667909365\n ],\n [\n -92.021484375,\n 30.06909396443887\n ],\n [\n -91.3623046875,\n 28.613459424004414\n ],\n [\n -88.9453125,\n 28.8831596093235\n ],\n [\n -88.9892578125,\n 30.221101852485987\n ],\n [\n -90.65917968749999,\n 30.713503990354965\n ],\n [\n -90.3955078125,\n 33.50475906922609\n ],\n [\n -88.9013671875,\n 36.24427318493909\n ],\n [\n -88.9013671875,\n 36.87962060502676\n ],\n [\n -90.1318359375,\n 37.125286284966805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, A. 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To register these chemicals as pesticides in North America, their environmental effects must be reviewed on a periodic basis. As a part of this effort, toxicity of TFM and niclosamide to duckweed (Lemna gibba), and of niclosamide to aquatic midge (Chironomus tentans), was assessed. Results of these studies suggest that for both lampricides, the no-observable and lowest observable effects concentrations (NOEC and LOEC) exceed expected environmental concentrations, with effects only in the highest concentrations tested and the longest exposure times. Duckweed exposed to TFM indicated 7-day LOECs ≥ 4.88 mg/L for average specific growth rate and yield, with the EC50 > 9.74 mg/L. For duckweed exposed to niclosamide, 7-day LOECs for average specific growth rate and yield ranged from 0.271 to 0.569 mg/L, with the IC50 0.725 mg/L or greater depending on the parameter measured. For midge larvae exposed to niclosamide-dosed sediment, the LOEC values based on survival and growth were 26.2 mg/kg and > 82.1 mg/kg, respectively, and the EC50 based on survival was 49.6 mg/kg. Based on these data, deleterious effects on aquatic plants and benthic invertebrates are unlikely to result from use of TFM and niclosamide for lamprey control, given that the effect concentrations are in excess of the expected environmental concentrations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2019.11.007","usgsCitation":"Leak, T., Aufderheide, J., Bergfield, A., and Hubert, T.D., 2020, Acute toxicity of the lampricides TFM and niclosamide: Effects on a vascular plant and a chironomid species: Journal of Great Lakes Research, v. 46, no. 1, p. 180-187, https://doi.org/10.1016/j.jglr.2019.11.007.","productDescription":"8 p.","startPage":"180","endPage":"187","ipdsId":"IP-094759","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":372592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Great Lakes Basin, Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.5048828125,\n 47.07012182383309\n ],\n [\n -92.6806640625,\n 46.89023157359399\n ],\n [\n -91.845703125,\n 45.336701909968134\n ],\n [\n -90.791015625,\n 42.87596410238256\n ],\n [\n -89.384765625,\n 42.032974332441405\n ],\n [\n -87.36328125,\n 41.178653972331674\n ],\n [\n -86.044921875,\n 41.50857729743935\n ],\n [\n -85.69335937499999,\n 43.13306116240612\n ],\n [\n -84.814453125,\n 43.929549935614595\n ],\n [\n -84.5068359375,\n 42.68243539838623\n ],\n [\n -83.671875,\n 41.47566020027821\n ],\n [\n -82.30957031249999,\n 40.245991504199026\n ],\n [\n -77.607421875,\n 42.16340342422401\n ],\n [\n -74.091796875,\n 43.77109381775651\n ],\n [\n -70.7958984375,\n 44.653024159812\n ],\n [\n -73.95996093749999,\n 46.22545288226939\n ],\n [\n -77.607421875,\n 44.77793589631623\n ],\n [\n -80.244140625,\n 46.6795944656402\n ],\n [\n -83.3642578125,\n 48.22467264956519\n ],\n [\n -86.8798828125,\n 49.439556958940855\n ],\n [\n -89.12109375,\n 49.009050809382046\n ],\n [\n -92.5048828125,\n 47.07012182383309\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Leak, Tom","contributorId":222717,"corporation":false,"usgs":false,"family":"Leak","given":"Tom","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aufderheide, John","contributorId":222718,"corporation":false,"usgs":false,"family":"Aufderheide","given":"John","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergfield, Alan","contributorId":222719,"corporation":false,"usgs":false,"family":"Bergfield","given":"Alan","email":"","affiliations":[{"id":40594,"text":"EAG Laboratories","active":true,"usgs":false}],"preferred":false,"id":783009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":783006,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215289,"text":"70215289 - 2020 - Biotic interactions help explain variation in elevational range limits of birds among Bornean mountains","interactions":[],"lastModifiedDate":"2020-10-14T22:40:56.836813","indexId":"70215289","displayToPublicDate":"2020-01-07T17:31:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Biotic interactions help explain variation in elevational range limits of birds among Bornean mountains","docAbstract":"Physiological tolerances and biotic interactions along habitat gradients are thought to influence species occurrence. Distributional differences caused by such forces are particularly noticeable on tropical mountains, where high species turnover along elevational gradients occurs over relatively short distances and elevational distributions of particular species can shift among mountains. Such shifts are interpreted as evidence of the importance of spatial variation in interspecific competition and habitat or climatic gradients. To assess the relative importance of competition and compression of habitat and climatic zones in setting range limits, we examined differences in elevational ranges of forest bird species among four Bornean mountains with distinct features.
Bornean mountains Kinabalu, Mulu, Pueh and Topap Oso.
Rain forest bird communities along elevational gradients.
We surveyed the elevational ranges of rain forest birds on four mountains in Borneo to test which environmental variables—habitat zone compression or presence of likely competitors—best predicted differences in elevational ranges of species among mountains. For this purpose, we used two complementary tests: a comparison of elevational range limits between pairs of mountains, and linear mixed models with naïve occupancy as the response variable.
We found that lowland species occur higher in elevation on two small mountains compared to Mt. Mulu. This result is inconsistent with the expectation that distributions of habitats are elevationally compressed on small mountains, but is consistent with the hypothesis that a reduction in competition (likely diffuse) on short mountains, which largely lack montane specialist species, allows lowland species to occur higher in elevation. The relative influence of competition changes with elevation, and the correlation between lower range limits of montane species and the distribution of their competitors was weaker than in lowland species.
These findings provide support for the importance of biotic interactions in setting elevational range limits of tropical bird species, although abiotic gradients explain the majority of distribution patterns. Thus, models predicting range shifts under climate change scenarios must include not only climatic variables, as is currently most common, but also information on potentially resulting changes in species interactions, especially for lowland species.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.13784","usgsCitation":"Burner, R., Boyce, A., Bernasconi, D., Styring, A.R., Shakya, S.B., Boer, C., Rahman, M.A., Martin, T.E., and Sheldon, F.H., 2020, Biotic interactions help explain variation in elevational range limits of birds among Bornean mountains: Journal of Biogeography, v. 47, no. 3, p. 760-771, https://doi.org/10.1111/jbi.13784.","productDescription":"12 p.","startPage":"760","endPage":"771","ipdsId":"IP-107210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":458196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.13784","text":"Publisher Index Page"},{"id":379392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia, Malaysia","otherGeospatial":"Borneo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 119.17968749999999,\n 5.659718554577286\n ],\n [\n 116.89453125,\n 7.493196470122287\n ],\n [\n 113.5546875,\n 4.609278084409835\n ],\n [\n 111.09374999999999,\n 2.7235830833483856\n ],\n [\n 109.1162109375,\n 1.9771465537125772\n ],\n [\n 108.5888671875,\n 0.17578097424708533\n ],\n [\n 110.0830078125,\n -3.2063329870791315\n ],\n [\n 112.939453125,\n -3.90809888189411\n ],\n [\n 115.224609375,\n -4.258768357307995\n ],\n [\n 116.3232421875,\n -4.039617826768424\n ],\n [\n 118.95996093749999,\n 1.142502403706165\n ],\n [\n 117.7734375,\n 3.2940822283128175\n ],\n [\n 119.61914062499999,\n 5.134714634014467\n ],\n [\n 119.17968749999999,\n 5.659718554577286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":243138,"corporation":false,"usgs":false,"family":"Burner","given":"Ryan C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":801602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Andy J.","contributorId":243139,"corporation":false,"usgs":false,"family":"Boyce","given":"Andy J.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":801603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernasconi, David","contributorId":243140,"corporation":false,"usgs":false,"family":"Bernasconi","given":"David","email":"","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Styring, Alison R.","contributorId":243175,"corporation":false,"usgs":false,"family":"Styring","given":"Alison","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":801653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shakya, Subir B.","contributorId":243141,"corporation":false,"usgs":false,"family":"Shakya","given":"Subir","email":"","middleInitial":"B.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boer, Chandradewana","contributorId":243142,"corporation":false,"usgs":false,"family":"Boer","given":"Chandradewana","email":"","affiliations":[{"id":48646,"text":"u m","active":true,"usgs":false}],"preferred":false,"id":801606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rahman, Mustafa Abdul","contributorId":243143,"corporation":false,"usgs":false,"family":"Rahman","given":"Mustafa","email":"","middleInitial":"Abdul","affiliations":[{"id":48647,"text":"college sabah","active":true,"usgs":false}],"preferred":false,"id":801607,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":801608,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sheldon, Frederick H.","contributorId":243144,"corporation":false,"usgs":false,"family":"Sheldon","given":"Frederick","email":"","middleInitial":"H.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":801609,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208125,"text":"70208125 - 2020 - Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","interactions":[],"lastModifiedDate":"2020-02-06T11:44:25","indexId":"70208125","displayToPublicDate":"2020-01-07T16:40:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","title":"Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay","docAbstract":"Understanding habitat associations is vital for conservation of at‐risk marsh‐endemic wildlife species, particularly those under threat from sea level rise. We modeled environmental and habitat associations of the marsh‐endemic, Federally endangered salt marsh harvest mouse (Reithrodontomys raviventris, RERA) and co‐occurrence with eight associated small mammal species from annual trap data, 1998–2014, in six estuarine marshes in North San Francisco Bay, California. Covariates included microhabitat metrics of elevation and vegetation species and cover; and landscape metrics of latitude–longitude, distance to anthropogenic features, and habitat patch size. The dominant cover was pickleweed (Salicornia pacifica) with 86% mean cover and 37 cm mean height, and bare ground with about 10% mean cover. We tested 38 variants of Bayesian network (BN) models to determine covariates that best account for presence of RERA and of all nine small mammal species. Best models had lowest complexity and highest classification accuracy. Among RERA presence models, three best BN models used covariates of latitude–longitude, distance to paved roads, and habitat patch size, with 0% error of false presence, 20% error of false nonpresence, and 20% overall error. The all‐species presence models suggested that within the pickleweed marsh environment, RERA are mostly habitat generalists. Accounting for presence of other species did not improve prediction of RERA. Habitat attributes compared between RERA and the next most frequently captured species, California vole (Microtus californicus), suggested substantial habitat overlap, with RERA habitat being somewhat higher in marsh elevation, greater in percent cover of the dominant plant species, closer to urban areas, further from agricultural areas, and, perhaps most significant, larger in continuous size of marsh patch. Findings will inform conservation management of the marsh environment for RERA by identifying best microhabitat elements, landscape attributes, and adverse interspecific interactions.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1002/ece3.5860","usgsCitation":"Marcot, B.G., Woo, I., Thorne, K., Freeman, C.M., and Guntenspergen, G.R., 2020, Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay: Ecology and Evolution, v. 0, no. 2, p. 662-677, https://doi.org/10.1002/ece3.5860.","productDescription":"16 p.","startPage":"662","endPage":"677","ipdsId":"IP-101159","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458198,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5860","text":"Publisher Index Page"},{"id":437176,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96Q5D2T","text":"USGS data release","linkHelpText":"Small mammal surveys from northern San Francisco Bay: 1998-2014"},{"id":371662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7117919921875,\n 37.82497195707114\n ],\n [\n -121.98669433593749,\n 37.82497195707114\n ],\n [\n -121.98669433593749,\n 38.190704293996504\n ],\n [\n -122.7117919921875,\n 38.190704293996504\n ],\n [\n -122.7117919921875,\n 37.82497195707114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"0","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcot, Bruce G.","contributorId":152612,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":780617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":780620,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205181,"text":"ofr20191089 - 2020 - Remnant hardwood forest mapping within the Upper Mississippi River floodplain","interactions":[],"lastModifiedDate":"2022-04-21T18:41:17.216501","indexId":"ofr20191089","displayToPublicDate":"2020-01-07T13:45:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1089","displayTitle":"Remnant Hardwood Forest Mapping within the Upper Mississippi River Floodplain","title":"Remnant hardwood forest mapping within the Upper Mississippi River floodplain","docAbstract":"The primary objective of the project was to locate previously unknown stands of mast-producing hardwood forest trees in the Upper Mississippi River floodplain using existing information. We located and mapped 399 previously unknown hardwood forest stands within the Mississippi River floodplain area of navigation pools 9, 10, and 11. Using color infrared images in combination with true-color imagery was useful for identifying hardwood forest stands. We recommend our result be refined by visiting the forest stands we identified to evaluate our classification rate and determine which stands are regenerating. In combination with regeneration information, our results can help better inform flood inundation modeling, which will help improve the efficacy of restoration design. Although we had some success using the best available information, to obtain more relevant observations, we recommend acquiring color infrared aerial imagery during the late fall season if providing detailed mapping of forest stands is a management priority. Imagery of this type collected in the fall, when trees may be distinguished by their differing senescence, has the potential to uniquely identify individual species or perhaps even individual trees. Gaining a better understanding of forest diversity and developing conservation strategies to preserve that diversity is timely because remaining aging trees, established before lock-and-dam installation on the Mississippi River, are nearing the end of their life expectancy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191089","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Hanson, J.L., King, R., Hoy, E.E., 2019, Remnant hardwood forest mapping within the Upper Mississippi River floodplain: U.S. Geological Survey Open-File Report 2019–1089, 10 p., https://doi.org/10.3133/ofr20191089.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-102264","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399413,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109582.htm"},{"id":370698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1089/ofr20191089.pdf","text":"Report","size":"4.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1089"},{"id":370697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1089/coverthb.jpg"},{"id":370699,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WNW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"FWS McGregor District Mast Hardwood Floodplain Forest Community"}],"country":"United States","state":"Iowa, Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.42822265625,\n 43.67581809328341\n ],\n [\n -91.5380859375,\n 43.6599240747891\n ],\n [\n -91.49414062499999,\n 43.48481212891603\n ],\n [\n -91.60400390625,\n 43.100982876188546\n ],\n [\n -91.2744140625,\n 42.65012181368022\n ],\n [\n -90.81298828125,\n 42.52069952914966\n ],\n [\n -90.37353515625,\n 42.52069952914966\n ],\n [\n -90.68115234375,\n 42.97250158602597\n ],\n [\n -90.72509765625,\n 43.30919109985686\n ],\n [\n -91.01074218749999,\n 43.61221676817573\n ],\n [\n -91.42822265625,\n 43.67581809328341\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Understanding influenza A virus (IAV) persistence in wetlands is limited by a paucity of field studies relating to the maintenance of infectivity over time. The duration of IAV infectivity in water has been assessed under variable laboratory conditions, but results are difficult to translate to more complex field conditions. We tested a field-based method to assess the viability of IAVs in an Alaska wetland during fall and winter which incorporated physical and chemical properties of the waterbody in which samples were held. Filtered pond water was inoculated with avian fecal samples collected from the environment, aliquoted into a series of duplicate sealed vials and submerged back in the wetland for up to 132 days (October 2018–March 2019). Sample aliquots were sequentially recovered and tested for IAVs by rRT-PCR and virus isolation. One sample remained rRT-PCR positive for the duration of the study and virus isolation positive for 118 days. The surrounding water temperature was 1°–6 °C with near neutral pH (6.6–7.3) for the duration of the study. This proof of concept study demonstrates a protocol for testing the persistence of infectious IAV naturally shed from waterfowl under ambient environmental conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jviromet.2020.113818","usgsCitation":"Reeves, A.B., Ramey, A.M., Koch, J.C., Poulson, R., and Stallknecht, D., 2020, Field-based method for assessing duration of infectivity for influenza A viruses in the environment: Journal of Virological Methods, v. 277, 113818, https://doi.org/10.1016/j.jviromet.2020.113818.","productDescription":"113818","ipdsId":"IP-112830","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":458201,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9289940","text":"External Repository"},{"id":437177,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B8XH6E","text":"USGS data release","linkHelpText":"Influenza A Virus Persistence Data from an Urban Wetland in Anchorage, Alaska, 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\"}}]}","volume":"277","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":793051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":793052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":793053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":793054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":793055,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210790,"text":"70210790 - 2020 - Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2020-06-25T14:54:58.664449","indexId":"70210790","displayToPublicDate":"2020-01-07T09:50:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi","docAbstract":"The high frequency of historical eruptions at Kīlauea Volcano presents an exceptional opportunity to address fundamental questions related to the transport, storage, and interaction of magmas within rift zones. The Nāpau Crater area on Kīlauea’s East Rift Zone (ERZ) experienced nine fissure eruptions within 50 years (1961–2011). Most of the magma intruded during these frequent eruptions remained stored within the rift zone, creating a potential magma mixing depot within the ERZ. The superbly monitored and sampled 2011 eruption (Puʻu ʻŌʻō episode 59) presents an extraordinary opportunity to evaluate magma mixing processes within the ERZ. Whole-rock, glass, and olivine compositions were determined, not only for lava from the 2011 eruption, but also for a new suite of Nāpau Crater area samples from the 1963, 1965, 1968, 1983, and 1997 eruptions, as well as the previously undocumented 1922 eruption. Whole-rock XRF data revealed two geochemically distinct magma batches for episode 59: one less evolved (∼6·6 wt % MgO, 0·46 wt % K2O) than the other (∼6·2 wt % MgO, 0·58 wt % K2O). Episode 59 lava is remarkably aphyric (∼0·1 vol. % phenocrysts), making use of mineralogy to identify parent magma affinities problematic. Linear compositional trends of whole-rock major and trace elements, and reversely zoned olivine crystals indicate episode 59 lavas underwent magma mixing. Least squares regression calculations and plots of major and trace element data, were used to evaluate whether the episode 59 samples are products of mixing summit-derived magma with residual magma from previous Nāpau Crater area eruptions. The regression results and trace element ratios are inconsistent with previously proposed mixing scenarios, but they do support mixing between summit-derived magma and residual magma from the 1983 and 1997 Nāpau Crater area eruptions. These magmas were stored in physically and chemically distinct pods at depths of 1·6–3·0 km prior to mixing with new magma intruded from the summit to produce the episode 59 lava. One pod contained a fractionated equivalent of 1983 lava, and the other a hybrid of compositions similar to 1983 and 1997 lavas. The petrology of episode 59 lava demonstrates that magmas from two previous eruptions (1983 and 1997) were available to mix with magma intruded from the summit region. This study clarifies the pre-eruptive history of the mixed episode 59 lava, and elucidates the evolution of the volcano's magmatic system in a region of frequent eruptions.","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egz064","usgsCitation":"Walker, B.H., Garcia, M.O., and Orr, T.R., 2020, Petrologic insights into rift zone magmatic interactions from the 2011 eruption of Kīlauea Volcano, Hawaiʻi: Journal of Petrology, v. 60, no. 11, p. 2051-2075, https://doi.org/10.1093/petrology/egz064.","productDescription":"25 p.","startPage":"2051","endPage":"2075","ipdsId":"IP-091040","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458203,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egz064","text":"Publisher Index Page"},{"id":375917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"East Rift Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3521728515625,\n 19.16592425362802\n ],\n [\n -155.01708984375,\n 19.16592425362802\n ],\n [\n -155.01708984375,\n 19.33706180106996\n ],\n [\n -155.3521728515625,\n 19.33706180106996\n ],\n [\n -155.3521728515625,\n 19.16592425362802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"60","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Brett H.","contributorId":225523,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"H.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":791433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Michael O.","contributorId":225524,"corporation":false,"usgs":false,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":791434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":791435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209618,"text":"70209618 - 2020 - Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery","interactions":[],"lastModifiedDate":"2020-04-16T13:04:55.09969","indexId":"70209618","displayToPublicDate":"2020-01-07T08:01:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery","docAbstract":"Currently there is little natural recruitment of white sturgeon (Acipenser transmontanus) in the Upper Columbia River located in British Columbia, Canada and Washington, USA. This review of life history, physiology, and behavior of white sturgeon, along with data from recent toxicological studies, suggest that trace metals, especially Cu, affect survival and behavior of early life stage fish. Sturgeon free embryos, first feeding embryos, and mixed feeding embryos utilize interstitial \nspaces between gravel. Although concentrations of Cu in the water column of the Upper Columbia River are typically less than US water quality criteria defined to protect aquatic life, samples at the sediment–water interface were as large as 24 µg/L and exceed the criteria. Toxicological studies reviewed here demonstrate mortality, loss of equilibrium, and immobility at Cu concentrations of 1.5 to <16 µg/L and reduced swimming activity was documented at 0.88 to 7 μg/L. Contaminated invertebrates and slag particles provide other routes of exposure. These additional routes of exposure can cause indirect effects from starvation due to potential lack of prey items and ingestion of contaminated prey or slag particles. The lack of food in stomachs during these critical early life stages may coincide with a threshold “point of no return” at which sturgeon will be unable to survive even if food becomes available following that early time frame. These findings become especially important as work progresses to enhance white sturgeon recruitment in the Upper Columbia River. To date, decisions against including trace metals as a factor in sturgeon recovery have focused on surface‐water concentrations and measurements of lethality (LC50) to establish threshold concentrations for sturgeon sensitivity. However, information provided here suggests that measurements from the sediment–water interface and effect concentrations (EC50) be considered with white sturgeon life history characteristics. These data support minimizing Cu exposure risk to enhance a successful white sturgeon recovery effort.","language":"English","publisher":"SETAC","doi":"10.1002/ieam.4240","collaboration":"","usgsCitation":"Puglis, H.J., Farag, A., and Mebane, C.A., 2020, Copper concentrations in the upper Columbia River as a limiting factor in White Sturgeon recruitment and recovery: Integrated Environmental Assessment and Management, v. 16, no. 3, p. 378-391, https://doi.org/10.1002/ieam.4240.","productDescription":"14 p.","startPage":"378","endPage":"391","ipdsId":"IP-098467","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":374050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Washington, British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.71850585937501,\n 49.23194729854554\n ],\n [\n -117.784423828125,\n 49.75287993415023\n ],\n [\n -118.828125,\n 49.78835749241399\n ],\n [\n -118.89404296875,\n 49.01625665778159\n ],\n [\n -120.73974609374999,\n 49.01625665778159\n ],\n [\n -120.62988281249999,\n 48.23199134320962\n ],\n [\n -120.421142578125,\n 46.475699386607516\n ],\n [\n -117.7734375,\n 46.66451741754235\n ],\n [\n -117.71850585937501,\n 49.23194729854554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farag, Aida 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":200690,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":787191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70207998,"text":"70207998 - 2020 - Zircon-hosted melt inclusion record of silicic magmatism in the Mesoproterozoic St. Francois Mountains terrane, Missouri: Origin of the Pea Ridge iron oxide-apatite rare earth element deposit and implications for regional crustal pathways of mineralization","interactions":[],"lastModifiedDate":"2020-01-23T06:25:56","indexId":"70207998","displayToPublicDate":"2020-01-07T06:23:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Zircon-hosted melt inclusion record of silicic magmatism in the Mesoproterozoic St. Francois Mountains terrane, Missouri: Origin of the Pea Ridge iron oxide-apatite rare earth element deposit and implications for regional crustal pathways of mineralization","docAbstract":"Voluminous silicic magmatism was coeval with iron ore mineralization in the St.\nFrancois Mountains terrane in southeast Missouri, part of the broader Mesoproterozoic\nGranite-Rhyolite province along the eastern margin of Laurentia. Some of the iron\ndeposits contain extraordinary endowments of critical elements, such as the Pea Ridge\niron oxide-apatite (IOA) deposit, which has an average grade of ~12 wt% rare earth\noxides in breccia pipes that flank the ore body. To assess the role of silicic magmatism in\nthe genesis of the Pea Ridge deposit, we present a high-spatial resolution study of zirconhosted\nmelt inclusions from rhyolitic ash-flow tuffs. Melt inclusion data are combined\nwith textural, geochemical, and geochronological analyses of zircon hosts to elucidate the\nmagmatic-hydrothermal evolution of the Pea Ridge system. Two contemporaneous silicic\nigneous centers in the St. Francois Mountains terrane, Bourbon and Eminence, were\nstudied for comparison. Pea Ridge melt inclusions are trachydacitic to rhyolitic (~63-79\nwt% SiO2, ~5.6-11.7 wt% Na2O+K2O) with very high Cl in the least-evolved and most\nalkaline melt inclusions (~2,000-5,000 ppm Cl). Rare earth elements (REE) in melt\ninclusions have identical chondrite-normalized patterns to the mineralized breccia pipes,\nbut with systematically lower absolute concentrations. Haplogranite ternary pressures\nrange from ~0.5-10 kbar, with an average of ~2-3 kbar (7-12 km depth), and liquidus\ntemperatures are ~850-950 °C, with an average of ~920 °C. Silicate and phosphate\nmineral inclusions have compositions that overlap minerals from the iron ore body and\nbreccia pipes, recording a transition from igneous to hydrothermal zircon growth.\nIgneous iron oxide inclusions have compositions that indicate Pea Ridge magmas were\nreduced to moderately oxidized (log fO2 of -0.8 to -1.84 NNO). Zircons from two Pea\nRidge samples have 207Pb/206Pb concordia ages of 1456 ± 9 Ma and 1467 ± 13 Ma that\noverlap published ages for the breccia pipes and iron ore zones of the Pea Ridge deposit.\nA population of texturally and chemically disrupted zircons have discordant domains that\ncorrespond to high Fe, U, and REE concentrations, consistent with the unique\ngeochemical attributes of the IOA-REE ore body. Inherited cores in Pea Ridge and\nBourbon zircons have concordant 207Pb/206Pb dates of 1550-1618 Ma, providing direct\nevidence of cratonic basement beneath these centers. Oxygen isotope data for inherited\nand autocrystic igneous zircons span from mantle to crustal values (18Ozircon=5.5-7.9‰).\nOur data are consistent with a model in which metasomatized mantle components were\nmixed with cratonic and accreted crustal material in a back-arc or rifted segment of a\nvolcanic arc, with ore fluids derived from Cl-rich melts to transport Fe and REE in a\nlong-lived (tens of Myr), pulsed, magmatic-hydrothermal system. Bourbon, which also\npossesses IOA mineralization, shares key petrologic similarities with the Pea Ridge\nsystem, whereas Eminence, which is not mineralized, has disparate geochemical and\nisotopic signatures that indicate it formed in a different crustal setting. The location of\nPea Ridge and Bourbon along a cratonic margin may have been important in focusing\nsilicic melts and mineralization in the upper crust, serving as a guide for future\nexploration efforts.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2019.12.032","usgsCitation":"Watts, K., and Mercer, C.N., 2020, Zircon-hosted melt inclusion record of silicic magmatism in the Mesoproterozoic St. Francois Mountains terrane, Missouri: Origin of the Pea Ridge iron oxide-apatite rare earth element deposit and implications for regional crustal pathways of mineralization: Geochimica et Cosmochimica Acta, v. 272, p. 54-77, https://doi.org/10.1016/j.gca.2019.12.032.","productDescription":"24 p.","startPage":"54","endPage":"77","ipdsId":"IP-111591","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":458206,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2019.12.032","text":"Publisher Index Page"},{"id":437178,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TFVXR5","text":"USGS data release","linkHelpText":"Geochemistry, geochronology, and isotope geochemistry data for zircons and zircon-hosted melt and mineral inclusions in the St. Francois Mountains terrane, Missouri"},{"id":371486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.2412109375,\n 36.58024660149866\n ],\n [\n -89.967041015625,\n 36.58024660149866\n ],\n [\n -89.967041015625,\n 38.34165619279595\n ],\n [\n -92.2412109375,\n 38.34165619279595\n ],\n [\n -92.2412109375,\n 36.58024660149866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"272","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":780089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780090,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239440,"text":"70239440 - 2020 - Introduction to this special section: Geothermal energy","interactions":[],"lastModifiedDate":"2023-01-13T12:49:12.91956","indexId":"70239440","displayToPublicDate":"2020-01-07T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to this special section: Geothermal energy","docAbstract":"Geothermal energy is a global renewable resource that has the potential to provide a significant portion of baseload energy in many regions. In the United States, it has the potential to provide 8.5% of the electric generation capacity by the middle of the century. In general, geothermal systems require heat, permeability, and water to be viable for energy generation. However, with current technologies, only heat is strictly necessary in a native system. Engineered geothermal systems (EGS) introduce water into the subsurface at elevated pressures and reduced temperatures and enhance permeability through hydraulic and/or shear fracturing. Additionally, although moderate- to high-temperature resources currently dominate geothermal energy production, low-temperature resources have been utilized for direct-use cases. When well balanced and maintained, geothermal resources can produce significant amounts of heat and achieve long-term sustainability on the order of an estimated tens to hundreds of years.
Trees in dry forests often regenerate in episodic pulses when wet periods coincide with ample seed production. Factors leading to success or failure of regeneration pulses are poorly understood. We investigated the impacts of stand thinning on survival and growth of the 2013 cohort of ponderosa pine (Pinus ponderosa Douglas ex P. Lawson & C. Lawson) seedlings in northern Arizona, United States. We measured seedling survival and growth over the first five growing seasons after germination in six stand basal areas (BAs; 0, 7, 14, 23, 34, and 66 (unthinned) m2·ha−1) produced by long-term experimental thinnings. Five-year survival averaged 2.5% and varied among BAs. Mean survival duration was longer in intermediate BAs (11 to 16 months) than in clearings and high BAs (5 months). The BAs of 7, 14, and 23 m2·ha−1 had >2600 5-year-old seedlings·ha−1. In contrast, regeneration was lower in the clearing (666 seedlings·ha−1) and failed completely in the 34 m2·ha−1 and unthinned treatments. Seedling survival was highest during wet years and lowest during drought years. Many surviving seedlings had no net height growth between years 4 and 5 because of stem browsing. Results indicate that natural regeneration of ponderosa pine is influenced by stand BA, drought, herbivory, and interactions between extreme climatic events.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfr-2019-0248","usgsCitation":"Kolb, T.E., Flathers, K., Bradford, J.B., Andrews, C.M., Asherin, L.A., and Moser, W.K., 2020, Stand density, drought, and herbivory constrain ponderosa pine regeneration pulse: Canadian Journal of Forest Research, v. 50, no. 9, p. 862-871, https://doi.org/10.1139/cjfr-2019-0248.","productDescription":"10 p.","startPage":"862","endPage":"871","ipdsId":"IP-113864","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501090,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/99208","text":"External Repository"},{"id":372654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Fort Valley Experimental Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.88236236572266,\n 35.22963547294416\n ],\n [\n -111.72168731689453,\n 35.22963547294416\n ],\n [\n -111.72168731689453,\n 35.35321610123823\n ],\n [\n -111.88236236572266,\n 35.35321610123823\n ],\n [\n -111.88236236572266,\n 35.22963547294416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kolb, Thomas E.","contributorId":189073,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":783164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flathers, Kelsey","contributorId":222783,"corporation":false,"usgs":false,"family":"Flathers","given":"Kelsey","email":"","affiliations":[{"id":40601,"text":"School of Forestry, Northern Arizona University, Flagstaff, Arizona 86001;","active":true,"usgs":false}],"preferred":false,"id":783165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":222784,"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":783166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrews, Caitlin M. 0000-0003-4593-1071 candrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4593-1071","contributorId":192985,"corporation":false,"usgs":true,"family":"Andrews","given":"Caitlin","email":"candrews@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":783163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Asherin, Lance A.","contributorId":190303,"corporation":false,"usgs":false,"family":"Asherin","given":"Lance","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":783167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moser, W. Keith","contributorId":222785,"corporation":false,"usgs":false,"family":"Moser","given":"W.","email":"","middleInitial":"Keith","affiliations":[{"id":40602,"text":"U.S.D.A. 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Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org, last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).
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The WLCI has been working in southwestern Wyoming since 2007 to coordinate science and management decisions among government and private entities that invest in conservation projects aimed at restoring and enhancing wildlife habitat. These investments support jobs and generate business activities within the Wyoming economy. WLCI conservation and restoration projects occur on both publicly managed and privately owned lands and are supported by leveraging funds from Federal bureaus, Wyoming State and local government agencies, and private contributions. During 2007–2018, the WLCI invested a total of more than $69,100,000 (in 2018 dollars) on conservation projects within the State of Wyoming. These pooled funds have been used to purchase conservation easements and hire business contractors to complete restoration projects, with 98 percent of project funds awarded to Wyoming-based businesses. Including both direct and secondary effects, the U.S. Geological Survey estimates that local spending on these conservation and restoration projects during 2007–2018 supported an estimated 1,055 job-years (the number of annualized full- and part-time jobs generated or supported), more than $30,500,000 in labor income, almost $40,900,000 in value added, and almost $68,200,000 in economic output within the Wyoming economy. These results demonstrate how investments in WLCI conservation projects support jobs, livelihoods, small businesses, and rural economies in Wyoming.
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U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118