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Models predicted that: (i) atmospheric turbulence changes at centimeter scales or smaller at the point where molecular viscosity converts kinetic energy into heat<sup>1</sup>, (ii) the speed of sound varies at the surface with frequency<sup>2,3</sup>, and (iii) high frequency waves are strongly attenuated with distance in CO<sub>2</sub><sup>2–4</sup>. However, theoretical models were uncertain because of a lack of experimental data at low pressure, and the difficulty to characterize turbulence or attenuation in a closed environment. Here using Perseverance microphone recordings, we present the first characterization of Mars’ acoustic environment and pressure fluctuations in the audible range and beyond, from 20 Hz to 50 kHz. We find that atmospheric sounds extend measurements of pressure variations down to 1,000 times smaller scales than ever observed before, revealing a dissipative regime extending over 5 orders of magnitude in energy. Using point sources of sound (Ingenuity rotorcraft, laser-induced sparks), we highlight two distinct values for the speed of sound that are ~10 m/s apart below and above 240 Hz, a unique characteristic of low-pressure CO<sub>2</sub>-dominated atmosphere. We also provide the acoustic attenuation with distance above 2 kHz, allowing us to elucidate the large contribution of the CO<sub>2</sub> vibrational relaxation in the audible range. These results establish a ground truth for modelling of acoustic processes, which is critical for studies in atmospheres like Mars and Venus ones.</p>","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41586-022-04679-0","usgsCitation":"Maurice, S., Chide, B., Murdoch, N., Lorenz, R.D., Mimoun, D., Wiens, R.C., Stott, A.E., Jacob, X., Bertrand, T., Montmessin, F., Lanza, N.L., Alvarez-Llamas, C., Angel, S.M., Aung, M., Balaram, J., Beyssac, O., Cousin, A., Delory, G., Forni, O., Fouchet, T., Gasnault, O., Grip, H., Hecht, M., Hoffman, J., Laserna, J., Lasue, J., Maki, J.N., McClean, J., Meslin, P.#., Le Mouélic, S., Munguira, A., Newman, C.E., Rodriguez Manfredi, J.A., Moros, J., Ollila, A., Pilleri, P., Schröder, S., de la Torre Juarez, M., Tzanetos, T., Stack, K., Farley, K., Williford, K.H., Acosta-Maeda, T., Anderson, R., Applin, D., Arana, G., Bassas-Portus, M., Beal, R., Beck, P., Benzerara, K., Bernard, S., Bernardi, P., Bosak, T., Bousquet, B., Brown, A., Cadu, A., Caïs, P., Castro, K., Clavé, E., Clegg, S.M., Cloutis, E., Connell, S., Debus, A., Dehouck, E., Delapp, D., Donny, C., Dorresoundiram, A., Dromart, G., Dubois, B., Fabre, C., Fau, A., Fischer, W.F., Francis, R., Frydenvang, J., Gabriel, T.S., Gibbons, E., Gontijo, I., Johnson, J., Kalucha, H., Kelly, E., Knutsen, E., Lacombe, G., Legett, C., Leveille, R., Lewin, E., Lopez-Reyes, G., Lorigny, E., Madariaga, J.M., Madsen, M.B., Madsen, S., Mandon, L., Mangold, N., Mann, M., Manrique, J., Martinez-Frias, J., Mayhew, L., Meunier, F., McConnochie, T., McLennan, S., Montagnac, G., Mousset, V., Nelson, T.A., Newell, R.T., Parot, Y., Pilorget, C., Pinet, P., Pont, G., Quantin-Nataf, C., Quertier, B., Rapin, W., Reyes-Newell, A., Robinson, S., Rochas, L., Royer, C., Rull, F., Sautter, V., Sharma, S., Shridar, V., Sournac, A., Toplis, M., Torre-Fdez, I., Turenne, N., Udry, A., Veneranda, M., Venhaus, D., Vogt, D., and Willis, P., 2022, In situ recording of Mars soundscape: Nature, 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Reduced rainfall can also reduce soil moisture, which can increase the risk of wildfire. Cloud-water interception, or fog drip, is the process by which cloud-water droplets are captured on the leaves and branches of plants with some of the captured cloud water subsequently dripping to the ground. Studies in Hawaiʻi indicate that fog drip can contribute substantially to total precipitation and may have the potential to lessen the negative effects of drought or a drying climate on freshwater availability and wildfire risk. Wildfire danger assessments in the continental United States have used estimates of soil moisture, evapotranspiration, and climatic water deficit (that is, the evaporative demand that exceeds available water) to improve the identification of areas at risk for wildfires. In this study, water-budget models developed for the islands of Kauaʻi, Oʻahu, Molokaʻi, Maui, and Hawaiʻi were used to quantify the effects of severe drought, future climate conditions, and reducing or eliminating fog drip on groundwater recharge, soil moisture, evapotranspiration, and climatic water deficit. Island-wide summaries of groundwater recharge, soil moisture, evapotranspiration, and climatic water deficit were developed to (1) illustrate changes between recent, drought, and future climate conditions, (2) illustrate the effects of reducing or eliminating fog drip for recent, drought, and future climate conditions, and (3) highlight areas of increased potential risk for wildfire during drought and future climate conditions. The results of these analyses can be used by natural resource managers in Hawaiʻi.","language":"English","publisher":"Pacific Islands Climate Adaptation Science Center","usgsCitation":"Mair, A., and Oki, D.S., 2022, Estimating soil moisture, actual evapotranspiration, climatic water deficit, and groundwater recharge during periods of drought for current and future climate conditions in Hawaiʻi, 8 p.","productDescription":"8 p.","ipdsId":"IP-134041","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":427176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":404656,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c650ae4b0546c0c397b48/580f8424e4b0f497e795ffe1"}],"country":"United 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,{"id":70267789,"text":"70267789 - 2022 - Landscape geomorphology and local-riverine features influence Broad Whitefish (Coregonus nasus) spawning habitat suitability in Arctic Alaska","interactions":[],"lastModifiedDate":"2025-06-02T15:32:24.243098","indexId":"70267789","displayToPublicDate":"2022-03-31T10:26:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Landscape geomorphology and local-riverine features influence Broad Whitefish (<i>Coregonus nasus</i>) spawning habitat suitability in Arctic Alaska","title":"Landscape geomorphology and local-riverine features influence Broad Whitefish (Coregonus nasus) spawning habitat suitability in Arctic Alaska","docAbstract":"<p><span>Landscape-level geomorphic processes influence the spatial and temporal arrangement of fish habitats in freshwater ecosystems and fishes move across riverscapes, selecting a suite of habitats to maximise fitness. Here, we explore the influence of geomorphology on stream channel attributes and assess Broad Whitefish (</span><i>Coregonus nasus</i><span>) spawning habitat potential in the Colville River in Arctic Alaska. Using high-resolution digital surface models (5&nbsp;m</span><sup>2</sup><span>), we quantified the stream network extent and summarised channel habitat attributes continuously across the drainage network. Next, we developed an intrinsic potential (IP) model for Broad Whitefish by using geomorphic channel parameters previously understood to be associated with spawning habitats (channel width, median substrate size and channel braiding) to estimate the potential of streams across the Colville River watershed to provide spawning habitat. Our model results show the majority of habitat with high IP (≥0.6) was located within the braided sections of the main channel, which encompass &gt;1548&nbsp;km, but only 2% of the total channel network. The IP model was tested by tracking radio-tagged Broad Whitefish using aerial surveys. Prespawn fish moved into the watershed starting mid-July and mostly used habitat with moderate to very high IP in the middle and lower watershed. Several individuals were relocated in smaller multichannels with vegetated bars that contained very low IP (≤0.2), suggesting that other factors, such as hyporheic flow, may also influence spawning habitat selection. Our study demonstrates that IP modelling offers a useful method to quantify spawning habitat potential in data-poor riverscapes, providing useful information for managers to assess potential anthropogenic impacts and develop conservation plans to protect essential Broad Whitefish habitat.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12657","usgsCitation":"Leppi, J., Falke, J.A., Rinella, D., Wipfli, M.S., Seitz, A., and Whitman, M.S., 2022, Landscape geomorphology and local-riverine features influence Broad Whitefish (Coregonus nasus) spawning habitat suitability in Arctic Alaska: Ecology of Freshwater Fish, v. 31, no. 4, p. 622-639, https://doi.org/10.1111/eff.12657.","productDescription":"18 p.","startPage":"622","endPage":"639","ipdsId":"IP-126724","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12657","text":"Publisher Index Page"},{"id":489404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -163.185772718535,\n              70.98799175474022\n            ],\n            [\n              -163.185772718535,\n              66.54828717076046\n            ],\n            [\n              -142.02222047339154,\n              66.54828717076046\n            ],\n            [\n              -142.02222047339154,\n              70.98799175474022\n            ],\n            [\n              -163.185772718535,\n              70.98799175474022\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Leppi, Jason C.","contributorId":338571,"corporation":false,"usgs":false,"family":"Leppi","given":"Jason C.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":938899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rinella, Daniel J.","contributorId":355579,"corporation":false,"usgs":false,"family":"Rinella","given":"Daniel J.","affiliations":[{"id":81169,"text":"Fish and Wildlife Field Conservation Office","active":true,"usgs":false}],"preferred":false,"id":938901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seitz, Andrew C.","contributorId":264890,"corporation":false,"usgs":false,"family":"Seitz","given":"Andrew C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":938902,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitman, Matthew S.","contributorId":338574,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":81170,"text":"Arctic Field Office","active":true,"usgs":false}],"preferred":false,"id":938903,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70230106,"text":"70230106 - 2022 - Quantifying the relationship between prey density, livestock and illegal killing of leopards","interactions":[],"lastModifiedDate":"2022-06-16T15:24:17.223503","indexId":"70230106","displayToPublicDate":"2022-03-30T11:23:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the relationship between prey density, livestock and illegal killing of leopards","docAbstract":"<ol class=\"\"><li>Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events. Despite the importance of illegal killing of large carnivores in comparison with other causes of mortality, its relationship with potential drivers such as livestock density and wild prey abundance is rarely described.</li><li>Using ranger-collected data (2007-2019) of leopard killing events and data on covariates (livestock density, wild prey abundance, road length, protected area size, elevation) across Iran, we applied a single-visit N-mixture model to jointly model variation in detection probability and expected annualized number of leopard killing events.</li><li>Over the study period, we estimated 428 leopard mortalities (95% CI 184–1014), which was 45% larger than the observed number. Expected intensity of leopard killing was positively related to protected area size, livestock density and wild prey abundance. Detection of leopard killing was higher in areas with more developed road networks.</li><li>Synthesis and applications: Ranger based monitoring data on poaching of carnivores are cost effective, but traditional analysis does not take into account imperfect detection. We show that innovative statistics (single-visit N-mixture modeling) can reliably quantify poaching events and address their drivers, at large geographical scales. We used the example of the Persian leopard across Iran, but our approach is also applicable to understand killing dynamics of other species. Results suggest that a high frequency of leopard killing is likely to occur in areas with &gt; 100 livestock per km<sup>2</sup>&nbsp;and &gt; 450 individuals of wild prey per km<sup>2</sup>. This highlights the need for improved management of livestock grazing and effective measures around high-risk protected areas to mitigate human-leopard conflict and reduce killing of leopards.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.14163","usgsCitation":"Soofi, M., Qashqaei, A.T., Mousavi, M., Hadipour, E., Filla, M., Kiabi, B.H., Bleyhl, B., Ghoddousi, A., Balkenhol, N., Royle, A., Pavey, C.R., Khorozyan, I., and Waltert, M., 2022, Quantifying the relationship between prey density, livestock and illegal killing of leopards: Journal of Applied Ecology, v. 59, no. 6, p. 1536-1547, https://doi.org/10.1111/1365-2664.14163.","productDescription":"12 p.","startPage":"1536","endPage":"1547","ipdsId":"IP-136705","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Box 14195149, Tehran, Iran.","active":true,"usgs":false}],"preferred":false,"id":839049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bleyhl, Benjamin","contributorId":289359,"corporation":false,"usgs":false,"family":"Bleyhl","given":"Benjamin","email":"","affiliations":[{"id":62112,"text":"Geography Department, Humboldt-Universität zu Berlin, Unter den Linden","active":true,"usgs":false}],"preferred":false,"id":839050,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ghoddousi, Arash","contributorId":289360,"corporation":false,"usgs":false,"family":"Ghoddousi","given":"Arash","email":"","affiliations":[{"id":62114,"text":"Wildlife Sciences, University of Goettingen, Buesgenweg","active":true,"usgs":false}],"preferred":false,"id":839051,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Balkenhol, Niko","contributorId":287519,"corporation":false,"usgs":false,"family":"Balkenhol","given":"Niko","affiliations":[{"id":61604,"text":"Wildlife Sciences, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":839052,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. 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,{"id":70230117,"text":"70230117 - 2022 - A flexible movement model for partially migrating species","interactions":[],"lastModifiedDate":"2022-06-16T15:23:10.366044","indexId":"70230117","displayToPublicDate":"2022-03-30T11:01:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"A flexible movement model for partially migrating species","docAbstract":"<p id=\"d1e390\">We propose a flexible model for a partially migrating species, which we demonstrate using yearly paths for golden eagles (<i>Aquila chrysaetos</i>). Our model relies on a smoothly time-varying potential surface defined by a number of attractors. We compare our proposed approach using varying coefficients to a latent-state model, which we define differently for migrating, dispersing, and local individuals. While latent-state models are more common in the existing animal movement literature, varying coefficient models have various benefits including the ability to fit a wide range of movement strategies without the need for major model adjustments. We compare simulations from the models for three individuals to illustrate the ability of our model to better describe movement behavior for specific movement strategies. We also demonstrate the flexibility of our model by fitting several individuals whose movement behavior is less stereotypical.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.spasta.2022.100637","usgsCitation":"Eisenhauer, E., Hanks, E., Beckman, M., Murphy, R., Miller, T., and Katzner, T., 2022, A flexible movement model for partially migrating species: Spatial Statistics, v. 50, 100637, 25 p., https://doi.org/10.1016/j.spasta.2022.100637.","productDescription":"100637, 25 p.","ipdsId":"IP-135182","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.spasta.2022.100637","text":"Publisher Index Page"},{"id":397868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n  \"type\": 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University","active":true,"usgs":false}],"preferred":false,"id":839286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beckman, Matthew","contributorId":289541,"corporation":false,"usgs":false,"family":"Beckman","given":"Matthew","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":839287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Robert","contributorId":289542,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":839288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Tricia A.","contributorId":64790,"corporation":false,"usgs":true,"family":"Miller","given":"Tricia A.","affiliations":[],"preferred":false,"id":839289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katzner, Todd E. 0000-0003-4503-8435 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,{"id":70230691,"text":"70230691 - 2022 - Vulnerability of avian populations to renewable energy production","interactions":[],"lastModifiedDate":"2022-04-21T13:39:21.769355","indexId":"70230691","displayToPublicDate":"2022-03-30T08:35:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of avian populations to renewable energy production","docAbstract":"<p><span>Renewable energy production can kill individual birds, but little is known about how it affects avian populations. We assessed the vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA. Bayesian hierarchical models suggested that 48% of these species were vulnerable to population-level effects from added fatalities caused by renewables and other sources. Effects of renewables extended far beyond the location of energy production to impact bird populations in distant regions across continental migration networks. Populations of species associated with grasslands where turbines were located were most vulnerable to wind. Populations of nocturnal migrant species were most vulnerable to solar, despite not typically being associated with deserts where the solar facilities we evaluated were located. Our findings indicate that addressing declines of North American bird populations requires consideration of the effects of renewables and other anthropogenic threats on both nearby and distant populations of vulnerable species.</span></p>","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rsos.211558","usgsCitation":"Conkling, T., Vander Zanden, H.B., Allison, T.D., Diffendorfer, J., Dietsch, T.V., Duerr, A., Fesnock, A., Hernandez, R.R., Loss, S.R., Nelson, D.M., Sanzenbacher, P.M., Yee, J.L., and Katzner, T., 2022, Vulnerability of avian populations to renewable energy production: Royal Society Open Science, v. 9, no. 3, 211558, 16 p., https://doi.org/10.1098/rsos.211558.","productDescription":"211558, 16 p.","ipdsId":"IP-125394","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research 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V","contributorId":290516,"corporation":false,"usgs":false,"family":"Dietsch","given":"Thomas","email":"","middleInitial":"V","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":841167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duerr, A. 0000-0002-6145-8897","orcid":"https://orcid.org/0000-0002-6145-8897","contributorId":257045,"corporation":false,"usgs":false,"family":"Duerr","given":"A.","email":"","affiliations":[{"id":38830,"text":"Bloom Research Inc.","active":true,"usgs":false}],"preferred":false,"id":841168,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fesnock, Amy L","contributorId":290517,"corporation":false,"usgs":false,"family":"Fesnock","given":"Amy L","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":841169,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hernandez, Rebecca R.","contributorId":196899,"corporation":false,"usgs":false,"family":"Hernandez","given":"Rebecca","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":841170,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loss, S. R. 0000-0002-8753-2995","orcid":"https://orcid.org/0000-0002-8753-2995","contributorId":257044,"corporation":false,"usgs":false,"family":"Loss","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":51965,"text":"Department of Natural Resource Ecology & Management, Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":841171,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory,  301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":841172,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sanzenbacher, Peter M.","contributorId":90260,"corporation":false,"usgs":false,"family":"Sanzenbacher","given":"Peter","email":"","middleInitial":"M.","affiliations":[{"id":13016,"text":"Department of Fisheries and Wildlife, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":841173,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":841174,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":841175,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70240487,"text":"70240487 - 2022 - Balancing prey availability and predator consumption: A multispecies stock assessment for Lake Ontario","interactions":[],"lastModifiedDate":"2023-02-09T13:02:45.597116","indexId":"70240487","displayToPublicDate":"2022-03-30T06:57:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Balancing prey availability and predator consumption: A multispecies stock assessment for Lake Ontario","docAbstract":"<div>Trophic interactions are drivers of ecosystem change and stability, yet are often excluded from fishery assessment models, despite their potential capacity to improve estimates of species dynamics and future fishery sustainability. In Lake Ontario, recreational salmonine fisheries, including Chinook salmon (<i>Oncorhynchus tshawytscha</i>) and lake trout (<i>Salvelinus namaycush</i>), depend on a single prey species, alewife (<i>Alosa pseudoharengus</i>). To accommodate strong trophic interactions among species, we developed a multispecies statistical catch-at-age assessment (MSCAA) model that links the dynamics of the salmonine fisheries and alewife via prey consumption and predator growth. We found that prey availability had declined since 2015 due to decreased alewife recruitment and increased Chinook salmon biomass, leading to higher alewife mortality rates and lower predator growth rates. Forward projections of predator–prey dynamics suggest that Chinook salmon stocking reductions may improve the probability for alewife population growth, but could be counteracted by increased natural Chinook salmon recruitment. Combined with predator- and prey-monitoring efforts, multispecies assessments show promise as models of intermediate complexity to support a transition to ecosystem-based approaches to fisheries management.</div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0126","usgsCitation":"Fitzpatrick, K.B., Weidel, B., Connerton, M., Lantry, J.R., Holden, J.P., Yuille, M.J., Lantry, B.F., LaPan, S.R., Rudstam, L.G., Sullivan, P., Brenden, T., and Sethi, S., 2022, Balancing prey availability and predator consumption: A multispecies stock assessment for Lake Ontario: Canadian Journal Fisheries and Aquatic Sciences, v. 79, 9, 17 p., https://doi.org/10.1139/cjfas-2021-0126.","productDescription":"9, 17 p.","ipdsId":"IP-127740","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":412907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.60104394959603,\n              42.9937446130092\n            ],\n            [\n              -74.93212778090472,\n              42.9937446130092\n            ],\n            [\n              -74.93212778090472,\n              44.75812539357605\n            ],\n            [\n              -80.60104394959603,\n              44.75812539357605\n            ],\n            [\n              -80.60104394959603,\n              42.9937446130092\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"79","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Kimberly B.","contributorId":270324,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Kimberly","email":"","middleInitial":"B.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":863947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connerton, Michael J.","contributorId":190416,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael J.","affiliations":[],"preferred":false,"id":863949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lantry, Jana R.","contributorId":141107,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":863950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holden, Jeremy P.","contributorId":251689,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":50374,"text":"Ontario Ministry of Natural Resources and Forests (OMNRF)","active":true,"usgs":false}],"preferred":false,"id":863951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuille, Michael J.","contributorId":194647,"corporation":false,"usgs":false,"family":"Yuille","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaPan, Steven R.","contributorId":302290,"corporation":false,"usgs":false,"family":"LaPan","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":56930,"text":"New York DEC","active":true,"usgs":false}],"preferred":false,"id":863954,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":863955,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sullivan, Patrick J.","contributorId":302292,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":863956,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brenden, Travis O.","contributorId":302293,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis O.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":863957,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sethi, Suresh 0000-0002-0053-1827 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,{"id":70240820,"text":"70240820 - 2022 - Evidence for near-source nonlinear propagation of volcano infrasound from Strombolian explosions at Yasur Volcano, Vanuatu","interactions":[],"lastModifiedDate":"2023-02-23T12:45:18.550802","indexId":"70240820","displayToPublicDate":"2022-03-30T06:39:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for near-source nonlinear propagation of volcano infrasound from Strombolian explosions at Yasur Volcano, Vanuatu","docAbstract":"<p><span>Volcanic eruption source parameters may be estimated from acoustic pressure recordings dominant at infrasonic frequencies (&lt; 20&nbsp;Hz), yet uncertainties may be high due in part to poorly understood propagation dynamics. Linear acoustic propagation of volcano infrasound is commonly assumed, but nonlinear processes such as wave steepening may distort waveforms and obscure the sourcing process in recorded waveforms. Here we use a previously developed&nbsp;frequency-domain nonlinearity indicator to quantify spectral changes due to nonlinear propagation primarily in 80 signals from explosions at Yasur Volcano, Vanuatu. We find evidence for&nbsp;</span><span class=\"mathjax-tex\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo>&amp;#x2264;</mo></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mo\">≤</span></span></span></span><span class=\"MJX_Assistive_MathML\">≤</span></span></span><span>&nbsp;10</span><sup>−3</sup><span>&nbsp;dB/m spectral energy transfer in the band 3–9&nbsp;Hz for signals with amplitude on the order of several hundred Pa at 200–400&nbsp;m range. The clarity of the nonlinear spectral signature increases with waveform amplitude, suggesting stronger nonlinear changes for greater source pressures. We observe similar results in application to synthetics generated through finite-difference wavefield simulations of nonlinear propagation, although limitations of the model complicate direct comparison to the observations. Our results provide quantitative evidence for nonlinear propagation that confirms previous interpretations made on the basis of qualitative observations of asymmetric waveforms.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01552-w","usgsCitation":"Maher, S.P., Matoza, R.S., Jolly, A., de Groot-Hedlin, C., Gee, K.L., Fee, D., and Iezzi, A., 2022, Evidence for near-source nonlinear propagation of volcano infrasound from Strombolian explosions at Yasur Volcano, Vanuatu: Bulletin of Volcanology, v. 84, 41, 20 p., https://doi.org/10.1007/s00445-022-01552-w.","productDescription":"41, 20 p.","ipdsId":"IP-135447","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":448326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-022-01552-w","text":"Publisher Index Page"},{"id":413338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Tanna Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              169.33766678462047,\n              -19.539368583023972\n            ],\n            [\n              169.33766678462047,\n              -19.662219083395883\n            ],\n            [\n              169.49415550272943,\n              -19.662219083395883\n            ],\n            [\n              169.49415550272943,\n              -19.539368583023972\n            ],\n            [\n              169.33766678462047,\n              -19.539368583023972\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"84","noUsgsAuthors":false,"publicationDate":"2022-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Maher, Sean P","contributorId":302635,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","email":"","middleInitial":"P","affiliations":[{"id":65524,"text":"U California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":864933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matoza, Robin S","contributorId":215528,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":864934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":864935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Groot-Hedlin, Catherine","contributorId":302636,"corporation":false,"usgs":false,"family":"de Groot-Hedlin","given":"Catherine","email":"","affiliations":[{"id":65525,"text":"U California San Diego","active":true,"usgs":false}],"preferred":false,"id":864936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gee, Kent L. 0000-0002-5768-6483","orcid":"https://orcid.org/0000-0002-5768-6483","contributorId":296468,"corporation":false,"usgs":false,"family":"Gee","given":"Kent","email":"","middleInitial":"L.","affiliations":[{"id":64061,"text":"Department of Physics and Astronomy, Brigham Young University, Provo, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":864937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":864938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":864939,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70242887,"text":"70242887 - 2022 - Toppling of a Trona Pinnacles Spire following the M5.5 RidgecrestaAftershock of June 2020","interactions":[],"lastModifiedDate":"2023-04-21T12:24:54.016303","indexId":"70242887","displayToPublicDate":"2022-03-30T06:35:46","publicationYear":"2022","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}},"displayTitle":"Toppling of a Trona Pinnacles Spire following the M<sub>w</sub>5.5 Ridgecrest Aftershock of June 2020","title":"Toppling of a Trona Pinnacles Spire following the M5.5 RidgecrestaAftershock of June 2020","docAbstract":"<p><span>The 2019&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\">M<sub>w</sub></span></span><span>&nbsp;7.1 Ridgecrest California earthquake rupture passed within 4&nbsp;km of the Trona Pinnacles, a large group of tufa rock pillars. Reconnaissance following the Ridgecrest mainshock documented fresh damage to several of the Pinnacles. Repeated aerial photogrammetric surveys also documented damage during subsequent aftershocks. Here, we describe the photogrammetric data with emphasis on a specific rock spire that toppled during an&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\">M<sub>w</sub></span></span><span>5.5 aftershock. We calculate the volumes of the intact spire and of its subsequent debris. To explore the utility of the pinnacles as fragile geologic features for constraining past earthquake shaking intensity, we calculate the quasi static, horizontal acceleration required to break the spire at its base. We also examine the response of this feature to observed shaking using a dynamic model of the spire. In this case, we find that the quasi‐static estimate provides a conservative maximum constraint on fragility. The dynamic model of the spire suggests that shaking during the&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=\">M<sub>w</sub></span></span><span><sub>&nbsp;</sub>7.1 mainshock likely generated tensile stresses in excess of the spire’s bulk strength, thereby making it vulnerable to collapse in subsequent aftershocks.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210275","usgsCitation":"Donnellan, A., Garcia-Suarez, J., McPhillips, D., Asimaki, D., Goulet, C., Meng, X., Devine, S., and Lyzanga, G., 2022, Toppling of a Trona Pinnacles Spire following the M5.5 RidgecrestaAftershock of June 2020: Seismological Research Letters, v. 93, no. 3, p. 1768-1776, https://doi.org/10.1785/0220210275.","productDescription":"9 p.","startPage":"1768","endPage":"1776","ipdsId":"IP-137323","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":488946,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://infoscience.epfl.ch/record/294243","text":"External Repository"},{"id":416120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Trona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.37290967993692,\n              35.61140365258099\n            ],\n            [\n              -117.37290967993692,\n              35.61036568121271\n            ],\n            [\n              -117.37105357870811,\n              35.61036568121271\n            ],\n            [\n              -117.37105357870811,\n              35.61140365258099\n            ],\n            [\n              -117.37290967993692,\n              35.61140365258099\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"93","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Donnellan, Andrea","contributorId":304295,"corporation":false,"usgs":false,"family":"Donnellan","given":"Andrea","affiliations":[{"id":27923,"text":"NASA JPL","active":true,"usgs":false}],"preferred":false,"id":870100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia-Suarez, Joaquin","contributorId":304296,"corporation":false,"usgs":false,"family":"Garcia-Suarez","given":"Joaquin","email":"","affiliations":[{"id":66021,"text":"Swiss Federal Institute","active":true,"usgs":false}],"preferred":false,"id":870101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McPhillips, Devin 0000-0003-1987-9249","orcid":"https://orcid.org/0000-0003-1987-9249","contributorId":217362,"corporation":false,"usgs":true,"family":"McPhillips","given":"Devin","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":870102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asimaki, Domniki","contributorId":304297,"corporation":false,"usgs":false,"family":"Asimaki","given":"Domniki","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":870103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goulet, Christine","contributorId":304298,"corporation":false,"usgs":false,"family":"Goulet","given":"Christine","affiliations":[{"id":54387,"text":"SCEC","active":true,"usgs":false}],"preferred":false,"id":870104,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meng, Xiaofeng","contributorId":304299,"corporation":false,"usgs":false,"family":"Meng","given":"Xiaofeng","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":870105,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Devine, Savannah","contributorId":304300,"corporation":false,"usgs":false,"family":"Devine","given":"Savannah","email":"","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":870106,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lyzanga, Gregory","contributorId":304301,"corporation":false,"usgs":false,"family":"Lyzanga","given":"Gregory","email":"","affiliations":[{"id":27923,"text":"NASA JPL","active":true,"usgs":false}],"preferred":false,"id":870107,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70230196,"text":"70230196 - 2022 - A biological condition gradient for coral reefs in the US Caribbean Territories: Part I. Coral narrative rules","interactions":[],"lastModifiedDate":"2022-04-04T16:49:10.741224","indexId":"70230196","displayToPublicDate":"2022-03-29T11:42:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"A biological condition gradient for coral reefs in the US Caribbean Territories: Part I. Coral narrative rules","docAbstract":"<p><span>As coral reef condition and sustainability continue to decline worldwide, losses of critical habitat and their ecosystem services have generated an urgency to understand and communicate reef response to management actions, environmental contamination, and natural disasters. Increasingly, coral reef protection and restoration programs emphasize the need for robust assessment tools for protecting high-quality waters and establishing conservation goals. Of equal importance is the need to communicate assessment results to stakeholders, beneficiaries, and the public so that environmental consequences of decisions are understood. The Biological Condition (BCG) model provides a structure to evaluate the condition of a coral reef in increments of change along a gradient of human disturbance. Communication of incremental change, regardless of direction, is important for decision makers and the public to better understand what is gained or lost depending on what actions are taken. We developed a narrative (qualitative) Biological Condition Gradient (BCG) from the consensus of a diverse expert panel to provide a framework for coral reefs in US Caribbean Territories. The model uses narrative descriptions of biological attributes for benthic organisms to evaluate reefs relative to undisturbed or minimally disturbed conditions. Using expert elicitation, narrative decision rules were proposed and deliberated to discriminate among six levels of change along a gradient of increasing anthropogenic stress. Narrative rules for each of the BCG levels are presented to facilitate the evaluation of benthic communities in coral reefs and provide specific narrative features to detect changes in coral reef condition and biological integrity. The BCG model can be used in the absence of numeric, or quantitative metrics, to evaluate actions that may encroach on coral reef ecosystems, manage endangered species habitat, and develop and implement management plans for marine protected areas, watersheds, and coastal zones. The narrative BCG model is a defensible model and communication tool that translates scientific results so the nontechnical person can understand and support both regulatory and non-regulatory water quality and natural resource programs.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108805","usgsCitation":"Santavy, D.L., Jackson, S.K., Jessup, B., Gerritsen, J., Rogers, C., Fisher, W.S., Weil, E., Szmant, A., Cuevas-Miranda, D., Walker, B.K., Jeffrey, C., Bradley, P., Ballantine, D., Roberson, L., Ruiz-Torres, H., Todd, B., Smith, T.B., Clark, R., Diaz, E.L., Bauza-Ortega, J., Horstmann, C., and Raimondo, S., 2022, A biological condition gradient for coral reefs in the US Caribbean Territories: Part I. Coral narrative rules: Ecological Indicators, v. 138, 108805, 13 p., https://doi.org/10.1016/j.ecolind.2022.108805.","productDescription":"108805, 13 p.","ipdsId":"IP-132623","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448332,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108805","text":"Publisher Index Page"},{"id":398022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, U.S. Virgin Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -68.236083984375,\n              17.38209494787749\n            ],\n            [\n           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EPA","active":true,"usgs":false}],"preferred":false,"id":839485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jessup, Benjamin","contributorId":272092,"corporation":false,"usgs":false,"family":"Jessup","given":"Benjamin","email":"","affiliations":[{"id":56349,"text":"Tetra Tech, Inc","active":true,"usgs":false}],"preferred":false,"id":839486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerritsen, Jeroen 0000-0002-4455-1088","orcid":"https://orcid.org/0000-0002-4455-1088","contributorId":216564,"corporation":false,"usgs":false,"family":"Gerritsen","given":"Jeroen","email":"","affiliations":[],"preferred":false,"id":839487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogers, Caroline 0000-0001-9056-6961","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":218416,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, William S.","contributorId":229394,"corporation":false,"usgs":false,"family":"Fisher","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":839489,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weil, Ernesto","contributorId":191048,"corporation":false,"usgs":false,"family":"Weil","given":"Ernesto","email":"","affiliations":[],"preferred":false,"id":839490,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Szmant, Alina","contributorId":272094,"corporation":false,"usgs":false,"family":"Szmant","given":"Alina","email":"","affiliations":[{"id":24668,"text":"University of North Carolina, Wilmington","active":true,"usgs":false}],"preferred":false,"id":839491,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cuevas-Miranda, David","contributorId":289619,"corporation":false,"usgs":false,"family":"Cuevas-Miranda","given":"David","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":839492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walker, Brian K.","contributorId":289620,"corporation":false,"usgs":false,"family":"Walker","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":839493,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jeffrey, Christopher F G","contributorId":275150,"corporation":false,"usgs":false,"family":"Jeffrey","given":"Christopher F G","affiliations":[{"id":56719,"text":"CSS, Inc., Fairfax, VA, USA","active":true,"usgs":false}],"preferred":false,"id":839494,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bradley, 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Hector","contributorId":289623,"corporation":false,"usgs":false,"family":"Ruiz-Torres","given":"Hector","email":"","affiliations":[{"id":62201,"text":"University of Puerto Rico, Rio Piedras","active":true,"usgs":false}],"preferred":false,"id":839498,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Todd, Brandi","contributorId":272099,"corporation":false,"usgs":false,"family":"Todd","given":"Brandi","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":839499,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Smith, Tyler B.","contributorId":150546,"corporation":false,"usgs":false,"family":"Smith","given":"Tyler","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":839500,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":839501,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Diaz, Ernesto L.","contributorId":212197,"corporation":false,"usgs":false,"family":"Diaz","given":"Ernesto","email":"","middleInitial":"L.","affiliations":[{"id":38453,"text":"Department of Natural and Environmental Resources, Coastal Zone Management Program","active":true,"usgs":false}],"preferred":false,"id":839502,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Bauza-Ortega, Jorge","contributorId":289624,"corporation":false,"usgs":false,"family":"Bauza-Ortega","given":"Jorge","email":"","affiliations":[{"id":62202,"text":"San Juan Bay National Estuary Program","active":true,"usgs":false}],"preferred":false,"id":839503,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Horstmann, Christina","contributorId":272093,"corporation":false,"usgs":false,"family":"Horstmann","given":"Christina","email":"","affiliations":[{"id":56350,"text":"Oak Ridge Institute for Science Education Participant at US EPA","active":true,"usgs":false}],"preferred":false,"id":839504,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Raimondo, Sandy","contributorId":150748,"corporation":false,"usgs":false,"family":"Raimondo","given":"Sandy","email":"","affiliations":[{"id":18090,"text":"U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL","active":true,"usgs":false}],"preferred":false,"id":839505,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70230121,"text":"70230121 - 2022 - Interlaboratory comparison of three sediment bioaccumulation tests","interactions":[],"lastModifiedDate":"2022-04-26T12:15:02.338916","indexId":"70230121","displayToPublicDate":"2022-03-29T11:12:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Interlaboratory comparison of three sediment bioaccumulation tests","docAbstract":"<p><span>Standard bioaccumulation tests are commonly conducted using&nbsp;</span><i>Macoma nasuta</i><span>&nbsp;(clam), and&nbsp;</span><i>Alitta virens</i><span>&nbsp;(polychaete) for marine tests, and&nbsp;</span><i>Lumbriculus variegatus</i><span>&nbsp;(an oligochaete) for freshwater tests. Because the interlaboratory variability associated with these tests is unknown, four experienced laboratories conducted standard 28-day bioaccumulation tests with the above species using sediments contaminated with polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs). Chemical analysis of tissue samples was performed by a single laboratory. The intralaboratory variance among replicates was relatively low for PCB tissue concentrations, with coefficients of variation (CVs) ranging from 9% to 28% for all laboratories and species, with the exception of one laboratory reporting higher variability for&nbsp;</span><i>L</i><span>.&nbsp;</span><i>variegatus</i><span>&nbsp;(CV = 51%). Intralaboratory variance for PCB tissue concentrations was higher than interlaboratory variance for&nbsp;</span><i>A. virens</i><span>&nbsp;and&nbsp;</span><i>L</i><span>.&nbsp;</span><i>variegatus</i><span>, and the magnitude of difference (MOD) for laboratory means ranged from 1.4 to 2.0 across species. Intralaboratory variability was also low for lipid content, and lipid normalization of PCB and PAH body residues generally had little impact on variability. In addition to variability across bioassay laboratories, analytical variability was evaluated by different laboratories measuring the concentration of PCBs and total lipids in a subsample of tissue homogenate of sediment-exposed test organisms. Variability associated with tissue analysis was higher than bioassay laboratory variability only in tests with&nbsp;</span><i>L</i><span>.&nbsp;</span><i>variegatus</i><span>. Statistical differences between samples may be observed due to the low intralaboratory variability; however, the biological significance of these differences may be limited because the MOD is low. Considering the MOD when comparing bioaccumulation across treatments accounts for uncertainty related to inherent variability of the test in the interpretation of statistically significant results.</span></p>","language":"English","publisher":"Society of Environmental Chemistry and Toxicology (SETAC)","doi":"10.1002/etc.5300","usgsCitation":"Lotufo, G., Biedenbach, J.M., Farrar, J., Chanov, M.K., Hester, B.W., Warbritton, C.R., Steevens, J.A., Netchaev, J.M., Bednar, A., and Moore, D.W., 2022, Interlaboratory comparison of three sediment bioaccumulation tests: Environmental Toxicology and Chemistry, v. 41, no. 5, p. 1260-1275, https://doi.org/10.1002/etc.5300.","productDescription":"16 p.","startPage":"1260","endPage":"1275","ipdsId":"IP-130532","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":448334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5300","text":"Publisher Index Page"},{"id":397867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"New Bedford Harbor","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.92206954956055,\n              41.62237216807198\n            ],\n            [\n              -70.90198516845703,\n              41.62237216807198\n            ],\n            [\n              -70.90198516845703,\n              41.646107652521614\n            ],\n            [\n              -70.92206954956055,\n              41.646107652521614\n            ],\n            [\n              -70.92206954956055,\n              41.62237216807198\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lotufo, Guilherme R.","contributorId":289468,"corporation":false,"usgs":false,"family":"Lotufo","given":"Guilherme R.","affiliations":[{"id":40033,"text":"US Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":839169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biedenbach, James M.","contributorId":289469,"corporation":false,"usgs":false,"family":"Biedenbach","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":40033,"text":"US Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":839170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrar, J. Daniel","contributorId":289470,"corporation":false,"usgs":false,"family":"Farrar","given":"J. Daniel","affiliations":[{"id":40033,"text":"US Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":839171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chanov, Michael K.","contributorId":289472,"corporation":false,"usgs":false,"family":"Chanov","given":"Michael","email":"","middleInitial":"K.","affiliations":[{"id":62154,"text":"EA Engineering, Science, and Technology","active":true,"usgs":false}],"preferred":false,"id":839172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hester, Brian W.","contributorId":289475,"corporation":false,"usgs":false,"family":"Hester","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":62152,"text":"EcoAnalysts","active":true,"usgs":false}],"preferred":false,"id":839173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warbritton, Charles R.","contributorId":289477,"corporation":false,"usgs":true,"family":"Warbritton","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":839174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":839175,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Netchaev, Jenifer M.","contributorId":289479,"corporation":false,"usgs":false,"family":"Netchaev","given":"Jenifer","email":"","middleInitial":"M.","affiliations":[{"id":40033,"text":"US Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":839176,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bednar, Anthony J.","contributorId":289481,"corporation":false,"usgs":false,"family":"Bednar","given":"Anthony J.","affiliations":[{"id":40033,"text":"US Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":839177,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moore, David W.","contributorId":210111,"corporation":false,"usgs":false,"family":"Moore","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":839178,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70230714,"text":"70230714 - 2022 - Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?","interactions":[],"lastModifiedDate":"2022-05-13T15:19:01.582298","indexId":"70230714","displayToPublicDate":"2022-03-29T06:42:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?","docAbstract":"<p>The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub-daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state-of-the art applications of ML for water quality models and discuss opportunities to improve the use of ML for emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model-data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge-guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision-relevant predictions of riverine water quality.</p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14565","usgsCitation":"Varadharajan, C., Appling, A.P., Arora, B., Christianson, D., Hendrix, V., Kumar, V., Lima, A.R., Mueller, J., Oliver, S.K., Ombadi, M., Perciano, T., Sadler, J.M., Weierbach, H., Willard, J., Xu, Z., and Zwart, J.A., 2022, Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?: Hydrological Processes, v. 36, e14565, 22 p., https://doi.org/10.1002/hyp.14565.","productDescription":"e14565, 22 p.","ipdsId":"IP-133065","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14565","text":"Publisher Index Page"},{"id":399487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","noUsgsAuthors":false,"publicationDate":"2022-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Varadharajan, Charuleka","contributorId":242712,"corporation":false,"usgs":false,"family":"Varadharajan","given":"Charuleka","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":841218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arora, Bhavna 0000-0001-7841-886X","orcid":"https://orcid.org/0000-0001-7841-886X","contributorId":290532,"corporation":false,"usgs":false,"family":"Arora","given":"Bhavna","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christianson, Danielle","contributorId":265829,"corporation":false,"usgs":false,"family":"Christianson","given":"Danielle","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":841220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hendrix, Valerie 0000-0001-9061-8952","orcid":"https://orcid.org/0000-0001-9061-8952","contributorId":290533,"corporation":false,"usgs":false,"family":"Hendrix","given":"Valerie","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":841222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lima, Aranildo R.","contributorId":290536,"corporation":false,"usgs":false,"family":"Lima","given":"Aranildo","email":"","middleInitial":"R.","affiliations":[{"id":25337,"text":"Aquatic Informatics","active":true,"usgs":false}],"preferred":false,"id":841223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Juliane 0000-0001-8627-1992","orcid":"https://orcid.org/0000-0001-8627-1992","contributorId":290539,"corporation":false,"usgs":false,"family":"Mueller","given":"Juliane","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841225,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ombadi, Mohammed","contributorId":290542,"corporation":false,"usgs":false,"family":"Ombadi","given":"Mohammed","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841226,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Perciano, Talita 0000-0002-2388-1803","orcid":"https://orcid.org/0000-0002-2388-1803","contributorId":290546,"corporation":false,"usgs":false,"family":"Perciano","given":"Talita","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841227,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":841228,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Weierbach, Helen","contributorId":290549,"corporation":false,"usgs":false,"family":"Weierbach","given":"Helen","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841229,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":841230,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Xu, Zexuan","contributorId":290552,"corporation":false,"usgs":false,"family":"Xu","given":"Zexuan","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":841231,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":841232,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70237210,"text":"70237210 - 2022 - Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: Implications for people and plovers","interactions":[],"lastModifiedDate":"2022-10-04T11:43:54.452949","indexId":"70237210","displayToPublicDate":"2022-03-29T06:38:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: Implications for people and plovers","docAbstract":"<div class=\"article-section__content en main\"><p>Forecasting biogeomorphological conditions for barrier islands is critical for informing sea-level rise (SLR) planning, including management of coastal development and ecosystems. We combined five probabilistic models to predict SLR-driven changes and their implications on Fire Island, New York, by 2050. We predicted barrier island biogeomorphological conditions, dynamic landcover response, piping plover (<i>Charadrius melodus</i>) habitat availability, and probability of storm overwash under three scenarios of shoreline change (SLC) and compared results to observed 2014/2015 conditions. Scenarios assumed increasing rates of mean SLC from 0 to 4.71&nbsp;m erosion per year. We observed uncertainty in several morphological predictions (e.g., beach width, dune height), suggesting decreasing confidence that Fire Island will evolve in response to SLR as it has in the past. Where most likely conditions could be determined, models predicted that Fire Island would become flatter, narrower, and more overwash-prone with increasing rates of SLC. Beach ecosystems were predicted to respond dynamically to SLR and migrate with the shoreline, while marshes lost the most area of any landcover type compared to 2014/2015 conditions. Such morphological changes may lead to increased flooding or breaching with coastal storms. However—although modest declines in piping plover habitat were observed with SLC—the dynamic response of beaches, flatter topography, and increased likelihood of overwash suggest storms could promote suitable conditions for nesting piping plovers above what our geomorphology models predict. Therefore, Fire Island may offer a conservation opportunity for coastal species that rely on early successional beach environments if natural overwash processes are encouraged.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002436","usgsCitation":"Zeigler, S.L., Gutierrez, B.T., Lentz, E.E., Plant, N., Sturdivant, E., and Doran, K., 2022, Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: Implications for people and plovers: Earth's Future, v. 10, no. 4, e2021EF002436, 25 p., https://doi.org/10.1029/2021EF002436.","productDescription":"e2021EF002436, 25 p.","ipdsId":"IP-133005","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448343,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021ef002436","text":"External Repository"},{"id":407851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.32893371582031,\n              40.612909950230936\n            ],\n            [\n              -73.21495056152344,\n              40.612388698663665\n            ],\n            [\n              -72.98492431640625,\n              40.659285052824394\n            ],\n            [\n              -72.8668212890625,\n              40.71499673906409\n            ],\n            [\n              -72.8668212890625,\n              40.734770989672406\n            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0000-0002-5472-769X szeigler@usgs.gov","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":297194,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","email":"szeigler@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel 0000-0002-5703-5672","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":81234,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sturdivant, Emily J.","contributorId":297196,"corporation":false,"usgs":false,"family":"Sturdivant","given":"Emily J.","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":853645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":292448,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853646,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70252848,"text":"70252848 - 2022 - Assessment of a habitat equivalency analysis for freshwater mussels in the upper Mississippi River","interactions":[],"lastModifiedDate":"2024-04-09T11:38:59.443979","indexId":"70252848","displayToPublicDate":"2022-03-29T06:37:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5254,"text":"Freshwater Mollusk Biology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of a habitat equivalency analysis for freshwater mussels in the upper Mississippi River","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">The upper Mississippi River (UMR) contains diverse, dense, and reproducing assemblages of native freshwater mussels. In the case of an injury to mussels and their habitats, such as a hazardous material spill, train derailment, or barge grounding, resource managers have few restoration strategies. Resource managers need a means to document, quantify, and mitigate adverse effects on mussels resulting from injury. Habitat equivalency analysis (HEA), developed for use with a wide variety of habitat types, is a restoration scaling technique that compares ecological services lost from injury to ecological services gained through restoration actions. The U.S. Fish and Wildlife Service and Iowa Department of Natural Resources modified the HEA for use with native mussels. The mussel HEA has been applied within the UMR to estimate the quantity of restoration needed to compensate the public for injuries to mussels due to contaminant spills and construction projects. Our objective was to describe the UMR HEA for a general audience and assess if the four biological input variables used in the mussel HEA were reasonable based on literature values. We also evaluated the performance of HEA under a range of input scenarios. Although the input estimates used in HEA were within ranges reported in the peer-reviewed literature or were supported by professional judgment in the absence of peer-reviewed literature, outcomes of the mussel HEA were highly variable and would benefit from additional research to reduce uncertainty in the biological inputs. The application of HEA to mussels provides resource managers with a tool to quantify mussel-related ecological services lost from injury and to guide restoration efforts in the UMR.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.31931/fmbc-d-21-00004","usgsCitation":"Newton, T., Schrank, P.R., Zigler, S., Gritters, S., Kenney, A., and Kristin, S., 2022, Assessment of a habitat equivalency analysis for freshwater mussels in the upper Mississippi River: Freshwater Mollusk Biology and Conservation, v. 25, no. 1, p. 15-26, https://doi.org/10.31931/fmbc-d-21-00004.","productDescription":"12p.","startPage":"15","endPage":"26","ipdsId":"IP-120072","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448348,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-21-00004","text":"Publisher Index Page"},{"id":427610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newton, Teresa J. 0000-0001-9351-5852","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":78696,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schrank, Patricia R.","contributorId":335485,"corporation":false,"usgs":false,"family":"Schrank","given":"Patricia","email":"","middleInitial":"R.","affiliations":[{"id":80416,"text":"University of Minnesota, Minneapolis","active":true,"usgs":false}],"preferred":false,"id":898432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zigler, Steven J. 0000-0002-4153-0652","orcid":"https://orcid.org/0000-0002-4153-0652","contributorId":244025,"corporation":false,"usgs":false,"family":"Zigler","given":"Steven J.","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":898433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gritters, Scott","contributorId":335486,"corporation":false,"usgs":false,"family":"Gritters","given":"Scott","email":"","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenney, Aleshia","contributorId":237780,"corporation":false,"usgs":false,"family":"Kenney","given":"Aleshia","email":"","affiliations":[{"id":47611,"text":"USFWS, Illinois Ecological Services Field Office","active":true,"usgs":false}],"preferred":false,"id":898435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kristin, Skrabis.","contributorId":335487,"corporation":false,"usgs":false,"family":"Kristin","given":"Skrabis.","email":"","affiliations":[{"id":80419,"text":"U.S. Department of the Interior, Office of Policy Analysis","active":true,"usgs":false}],"preferred":false,"id":898436,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70267786,"text":"70267786 - 2022 - Using structured decision making to guide habitat restoration for butterflies: A case study of Oregon silverspots","interactions":[],"lastModifiedDate":"2025-06-02T15:18:57.178697","indexId":"70267786","displayToPublicDate":"2022-03-29T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2356,"text":"Journal of Insect Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Using structured decision making to guide habitat restoration for butterflies: A case study of Oregon silverspots","docAbstract":"<p><span>When making decisions about how to restore habitat for at-risk species, land managers must balance multiple competing objectives in the face of uncertainty about the impacts of management actions on at-risk populations. The Oregon silverspot (</span><i>Speyeria</i><span> = </span><i>Argynnis zerene hippolyta</i><span>) is a federally threatened butterfly, and uncertainty exists about the effects of proposed management. We used structured decision making (SDM) to guide restoration for Oregon silverspots. Managers identified persistence as their primary objective and further identified effects of herbicides as a key uncertainty. We developed a model of population dynamics incorporating management actions and parameterized the model based on experiments with a surrogate subspecies, the Zerene silverspot (</span><i>S. z. zerene</i><span>). Herbicide application may directly harm Oregon silverspots by increasing larval mortality, while indirectly benefiting silverspots by reducing the competition faced by their host plant. In this system, potential herbicide treatments include grass-specific fluazifop-P-butyl or forb-specific clopyralid applied with Agri-Dex</span><sup>®</sup><span>&nbsp;or Nu-Film</span><sup>®</sup><span>-IR adjuvants. We found that Oregon silverspot population growth rate is greatest with clopyralid and fluazifop-P-butyl when combined with Nu-Film</span><sup>®</sup><span>-IR than other alternatives (including no treatment) considering only direct effects or in combination with indirect effects. An adaptive management program would benefit Oregon silverspots by promoting exploration of management alternatives while allowing managers to act quickly to arrest steep declines. Uncertainty remains regarding how well our results will generalize in field conditions.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10841-022-00379-2","usgsCitation":"Doll, C., Converse, S.J., Edwards, C., and Schultz, C., 2022, Using structured decision making to guide habitat restoration for butterflies: A case study of Oregon silverspots: Journal of Insect Conservation, v. 26, p. 219-230, https://doi.org/10.1007/s10841-022-00379-2.","productDescription":"12 p.","startPage":"219","endPage":"230","ipdsId":"IP-133483","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Doll, Cassandra F.","contributorId":356208,"corporation":false,"usgs":false,"family":"Doll","given":"Cassandra F.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":938878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Collin B.","contributorId":356209,"corporation":false,"usgs":false,"family":"Edwards","given":"Collin B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":938879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Cheryl B.","contributorId":356210,"corporation":false,"usgs":false,"family":"Schultz","given":"Cheryl B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":938880,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70230016,"text":"sir20215123 - 2022 - Synthesizing ground magnetic disturbance using dipole-aligned loop elementary currents and Biot-Savart relationship","interactions":[],"lastModifiedDate":"2022-03-29T10:43:37.616302","indexId":"sir20215123","displayToPublicDate":"2022-03-28T15:50:00","publicationYear":"2022","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":"2021-5123","displayTitle":"Synthesizing Ground Magnetic Disturbance Using Dipole-Aligned Loop Elementary Currents and Biot-Savart Relationship","title":"Synthesizing ground magnetic disturbance using dipole-aligned loop elementary currents and Biot-Savart relationship","docAbstract":"<p>This report presents a method for constructing a simplified numerical description of the electric current distributions in the ionosphere and gap region based on dipole-aligned loop elementary currents (DALECs). A theoretical basis for DALECs is presented, along with a prototypical algorithm for constructing an elementary numerical DALEC. The algorithm is verified and validated by combining DALECs with an efficient Biot-Savart solver in order to estimate magnetic disturbance on the Earth’s surface. We examine (1) simple scenarios with known solutions and (2) hemispherical magnetic disturbance fields obtained from a state-of-the-art global geospace circulation model.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20215123","collaboration":"Prepared in cooperation with National Center for Atmospheric Research High Altitude Observatory","usgsCitation":"Rigler, E.J., and Wiltberger, M., 2022, Synthesizing ground magnetic disturbance using dipole-aligned loop elementary currents and Biot-Savart relationship: U.S. Geological Survey Scientific Investigations Report 2021–5123, 17 p., https://doi.org/10.3133/sir20215123.","productDescription":"Report: vi, 17 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-126434","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":397506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5123/sir50215123.pdf","text":"Report","size":"4.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5123"},{"id":397505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5123/coverthb.jpg"},{"id":397507,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5123/sir50215123_appendix.pdf","text":"Appendix 1. Algorithms","size":"296 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5123 Appendix 1. Algorithms"},{"id":397508,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5123/images"},{"id":397509,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5123/sir50215123.xml"}],"contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/geohazards/\" data-mce-href=\"http://www.usgs.gov/centers/geohazards/\">Geologic Hazards Science Center </a><br>U.S. Geological Survey<br>Box 25046, MS-966<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Physics and Mathematical Theory</li><li>Algorithms and Practical Considerations</li><li>Verification and Validation</li><li>Broader Context and Future Work </li><li>References Cited</li><li>Appendix</li></ul>","publishedDate":"2022-03-28","noUsgsAuthors":false,"publicationDate":"2022-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":838677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltberger, Michael 0000-0002-4844-3148","orcid":"https://orcid.org/0000-0002-4844-3148","contributorId":289192,"corporation":false,"usgs":false,"family":"Wiltberger","given":"Michael","email":"","affiliations":[{"id":62063,"text":"NCAR High Altitude Observatory","active":true,"usgs":false}],"preferred":false,"id":838678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230040,"text":"70230040 - 2022 - A methodology to assess the historical environmental footprint of in-situ recovery (ISR) of uranium: A demonstration in the Goliad Sand in the Texas Coastal Plain, USA","interactions":[],"lastModifiedDate":"2022-03-28T14:30:38.45732","indexId":"70230040","displayToPublicDate":"2022-03-28T09:20:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"A methodology to assess the historical environmental footprint of in-situ recovery (ISR) of uranium: A demonstration in the Goliad Sand in the Texas Coastal Plain, USA","docAbstract":"<p>In-situ recovery (ISR) has been the only technique used to extract uranium from sandstone-hosted uranium deposits in the Pliocene Goliad Sand in the Texas Coastal Plain. Water plays a crucial role throughout the ISR lifecycle of production and groundwater restoration yet neither the water use nor other environmental footprints have been well documented. The goal of this study is to examine historical records for all six ISR operations completed in the Goliad Sand to identify and quantify parameters that indicate the surface and aquifer disturbances, water use, and radon emissions. Overall, the average mine area was 0.00023 ± 0.00006 acres per pound (ac/lb) U<sub>3</sub>O<sub>8</sub>. The average mine pore volume was 48.9 ± 50 gal/lb U<sub>3</sub>O<sub>8</sub><span>&nbsp;</span>with a minimum affected aquifer volume of 0.51 ± 0.08 cubic feet per pound (cu ft/lb) U<sub>3</sub>O<sub>8.</sub><span>&nbsp;</span>An average of 258 ± 40 gallons (gal) of fluid were disposed per pound (lb) U<sub>3</sub>O<sub>8</sub>, with an average of 169 ± 26 gal/lb U<sub>3</sub>O<sub>8</sub><span>&nbsp;</span>attributed to restoration and 89 ± 36 gal/lb U<sub>3</sub>O<sub>8</sub><span>&nbsp;</span>attributed to the uranium production phase. The average radon emitted was 1.06 × 10<sup>−3</sup><span>&nbsp;</span>± 7.4 × 10<sup>−4</sup><span>&nbsp;</span>curies per pound (Ci/lb) U<sub>3</sub>O<sub>8</sub>. Goodness-of-fit (<span class=\"html-italic\">R</span><sup>2</sup>) values are ≥0.79 for linear regressions of the amount of uranium produced versus mine area, mine pore volumes, mine aquifer volumes, water pumped, and total water disposed. The<span>&nbsp;</span><span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;</span>value for radon emitted was 0.68. However, the water disposed only during the uranium production phase is more strongly correlated to the number of production days (<span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;</span>= 0.96) than to uranium production (<span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;</span>= 0.84), whereas the volume of water disposed during restoration is more strongly correlated to the “pore volume” (<span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;</span>= 0.97) than to uranium production (<span class=\"html-italic\">R</span><sup>2</sup><span>&nbsp;</span>= 0.90). Pore volume is an industry term used to describe the amount of fluid circulated through the aquifer during the uranium production period and stipulated in bond agreements in order to satisfy groundwater restoration requirements. Models constructed in this study can be used to estimate probable water use and the extent of surface and aquifer disturbances associated with ISR-amenable undiscovered uranium resources in the Goliad Sand. The historical perspective offered by the data compiled and correlations may prove useful to both industry and regulators.</p>","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/min12030369","usgsCitation":"Gallegos, T., Scott, A., Stengel, V.G., and Teeple, A., 2022, A methodology to assess the historical environmental footprint of in-situ recovery (ISR) of uranium: A demonstration in the Goliad Sand in the Texas Coastal Plain, USA: Minerals, v. 12, no. 3, 369, 29 p., https://doi.org/10.3390/min12030369.","productDescription":"369, 29 p.","ipdsId":"IP-132933","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":448350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min12030369","text":"Publisher Index Page"},{"id":397704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Texas Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.69140625,\n              31.44741029142872\n            ],\n            [\n              -96.328125,\n              31.22219703210317\n            ],\n            [\n              -99.65698242187499,\n              27.61540601339959\n            ],\n            [\n              -99.525146484375,\n              27.45953933271788\n            ],\n            [\n              -99.60205078124999,\n              27.332735136859146\n            ],\n            [\n              -99.503173828125,\n              27.225325836903373\n 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vstengel@usgs.gov","orcid":"https://orcid.org/0000-0003-0481-3159","contributorId":5932,"corporation":false,"usgs":true,"family":"Stengel","given":"Victoria","email":"vstengel@usgs.gov","middleInitial":"G.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":193061,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838976,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70230055,"text":"70230055 - 2022 - Landscape-scale forest restoration decreases vulnerability to drought mortality under climate change in southwest USA ponderosa forest","interactions":[],"lastModifiedDate":"2022-03-29T10:54:55.451953","indexId":"70230055","displayToPublicDate":"2022-03-28T08:09:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale forest restoration decreases vulnerability to drought mortality under climate change in southwest USA ponderosa forest","docAbstract":"<p>Drought-induced tree mortality is predicted to increase in dry forests across the western USA as future projections show hotter, drier climates potentially resulting in large-scale tree die-offs, changes in species composition, and loss of forest ecosystem services, including carbon storage. While some studies have found that forest stands with greater basal areas (BA) have higher drought mortality, many have not evaluated the extent to which forest structure, either overly dense forests due to fire suppression or forests restored to lower densities, interacts with drought mortality. The southwestern USA is particularly susceptible to tree mortality due to the predicted increases in temperature, drier soils, and forests with high density. Our objective was to evaluate how ponderosa pine mortality is expected to be influenced by the Four Forests Restoration Initiative, a large-scale forest restoration effort ongoing in northern Arizona, USA, that will reduce stand BA by approximately 40%. Specifically, we modeled drought mortality in three time periods, one contemporary (1970-2010), and two future (2020-2059 and 2060-2099) under three restoration scenarios: no thinning, 4FRI thinning, and a BA reduction beyond the 4FRI plan (4FRI-intensive). We estimated mortality using 11 climate models under two emissions scenarios. Without thinning, our model predicted that by mid-century (2020-2059), changes in climate could increase annual ponderosa pine mortality rates by 45-57% over contemporary rates. However, with thinning, mid-century mortality was predicted to remain near or below contemporary rates and these rates are 31-35% (4FRI) and 46-51% (4FRI-intensive) less than the mid-century scenarios without thinning. Our study shows that while climate change is likely to increase tree mortality rates, large-scale forest restoration projects, such as 4FRI, have the potential to ameliorate the effects of climate change and keep mortality rates near contemporary levels for decades.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120088","usgsCitation":"McCauley, L., Bradford, J., Robles, M.D., Shriver, R.K., Woolley, T.J., and Andrews, C.M., 2022, Landscape-scale forest restoration decreases vulnerability to drought mortality under climate change in southwest USA ponderosa forest: Forest Ecology and Management, v. 509, 120088, 11 p., https://doi.org/10.1016/j.foreco.2022.120088.","productDescription":"120088, 11 p.","ipdsId":"IP-135260","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120088","text":"Publisher Index Page"},{"id":397690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Coconino National Forest, Kaibab National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.66754150390625,\n              34.24586516842103\n            ],\n            [\n              -110.5389404296875,\n              34.24586516842103\n            ],\n            [\n              -110.5389404296875,\n              35.61488368245436\n            ],\n            [\n              -112.66754150390625,\n              35.61488368245436\n            ],\n            [\n              -112.66754150390625,\n              34.24586516842103\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"509","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCauley, Lisa A","contributorId":268774,"corporation":false,"usgs":false,"family":"McCauley","given":"Lisa A","affiliations":[{"id":55658,"text":"The Nature Conservancy, Center for Science and Public Policy, 1510 E Ft Lowell Road, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":838909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robles, Marcos D.","contributorId":244893,"corporation":false,"usgs":false,"family":"Robles","given":"Marcos","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":838911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":838912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolley, Travis J.","contributorId":229070,"corporation":false,"usgs":false,"family":"Woolley","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":41578,"text":"The Nature Conservancy, 114 N., San Francisco Street #205, Flagstaff, Arizona, 86001, USA","active":true,"usgs":false}],"preferred":false,"id":838913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":838914,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70230440,"text":"70230440 - 2022 - Sedimentary record of annual-decadal timescale reservoir dynamics: Anthropogenic stratigraphy of Lake Powell, Utah, U.S.A.","interactions":[],"lastModifiedDate":"2022-04-13T11:57:33.660983","indexId":"70230440","displayToPublicDate":"2022-03-28T06:54:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9134,"text":"The Sedimentary Record","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary record of annual-decadal timescale reservoir dynamics: Anthropogenic stratigraphy of Lake Powell, Utah, U.S.A.","docAbstract":"The tributaries of Lake Powell were impounded following construction of Glen Canyon Dam, resulting in deposition of reservoir sediment over a ∼650 km2 area since 1963. These units have been exposed through erosion as water storage in Lake Powell has decreased since 2000. This anthropogenic sedimentary record reflects the complex interplay among wet and dry periods of Colorado River runoff and the reservoir operating rules of Lake Powell. The relevant sedimentary exposures are mapped at reconnaissance level over 300 river-km above Glen Canyon Dam in canyons of the Colorado, San Juan, Escalante, and Dirty Devil Rivers. A detailed reference section measured in Calf Canyon, a tributary to the Colorado River, preserves more than 12 m of lacustrine, mainstem Colorado River, and local tributary sediment in an up-river location and elevation that is determined to have been inundated only during the highest reservoir level periods. At Calf Canyon, exposed reservoir sediment is comprised of cyclic sand-mud interbeds that record periods of deposition when reservoir level was at or above full pool. Six depositional cycles are identified in Calf Canyon, and each of these is interpreted to represent rapid sand deposition during Colorado River flood events (likely related to spring snowmelt runoff) followed by deposition of lacustrine mud while reservoir levels were high. The lacustrine mud units display significant pedogenic modification, indicating exposure and colonization dominated by tamarisk plants, prior to deposition of the next sand unit. High-precision elevation surveys of the 6 main lacustrine marker beds in Calf Canyon are correlated to multiple lake level highstands between 1975 and 2000. Preliminary observations suggest that age-equivalent strata are widespread within the reservoir-affected zones of all major tributaries including the Colorado and San Juan River arms as well as the Escalante and Dirty Devil Rivers. We predict that future map- ping in other Lake Powell side canyons will demonstrate strong local control on sediment provenance, dictated by side canyon lithology, as well as time-transgressive deposition (and erosion) moving up and down the main canyons.","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/sedred.2022.1.3","usgsCitation":"Johnson, C., Root, J.C., Hynek, S., and Schmidt, J., 2022, Sedimentary record of annual-decadal timescale reservoir dynamics: Anthropogenic stratigraphy of Lake Powell, Utah, U.S.A.: The Sedimentary Record, v. 20, no. 1, p. 15-29, https://doi.org/10.2110/sedred.2022.1.3.","productDescription":"15 p.","startPage":"15","endPage":"29","ipdsId":"IP-133199","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":448362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2110/sedred.2022.1.3","text":"Publisher Index Page"},{"id":398629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Lake Powell","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.73095703125,\n              37.01132594307015\n            ],\n            [\n              -109.720458984375,\n              37.01132594307015\n            ],\n            [\n              -109.720458984375,\n              38.16911413556086\n            ],\n            [\n              -111.73095703125,\n              38.16911413556086\n            ],\n            [\n              -111.73095703125,\n              37.01132594307015\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Cari","contributorId":290196,"corporation":false,"usgs":false,"family":"Johnson","given":"Cari","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":840434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Root, Jonathan Casey 0000-0003-0537-4418","orcid":"https://orcid.org/0000-0003-0537-4418","contributorId":223107,"corporation":false,"usgs":true,"family":"Root","given":"Jonathan","email":"","middleInitial":"Casey","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":840435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hynek, Scott 0000-0002-6885-0445","orcid":"https://orcid.org/0000-0002-6885-0445","contributorId":216634,"corporation":false,"usgs":true,"family":"Hynek","given":"Scott","email":"","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":840436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, John (Jack) C.","contributorId":290197,"corporation":false,"usgs":false,"family":"Schmidt","given":"John (Jack) C.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":840437,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70248721,"text":"70248721 - 2022 - Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density","interactions":[],"lastModifiedDate":"2023-09-18T14:05:04.028786","indexId":"70248721","displayToPublicDate":"2022-03-27T08:53:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density","docAbstract":"<p><span>Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium,&nbsp;</span><i>Gloeotrichia echinulata</i><span>. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of&nbsp;</span><i>G. echinulata</i><span>&nbsp;densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2590","usgsCitation":"Lofton, M., Brentrup, J.A., Beck, W.S., Zwart, J.A., Bhattacharya, R., Brighenti, L.S., Burnett, S.H., McCullough, I.M., Steele, B., Carey, C.C., Cottingham, K., Dietze, M., Ewing, H.A., Weathers, K.C., and LaDeau, S.L., 2022, Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density: Ecological Applications, v. 32, e2590, 24 p., https://doi.org/10.1002/eap.2590.","productDescription":"e2590, 24 p.","ipdsId":"IP-119852","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2590","text":"Publisher Index Page"},{"id":420889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire","otherGeospatial":"Lake Sunapee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.10639790180213,\n              43.45916503807919\n            ],\n            [\n              -72.10639790180213,\n              43.3077735355308\n            ],\n            [\n              -72.01805843117764,\n              43.3077735355308\n            ],\n            [\n              -72.01805843117764,\n              43.45916503807919\n            ],\n            [\n              -72.10639790180213,\n              43.45916503807919\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","noUsgsAuthors":false,"publicationDate":"2022-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lofton, Mary","contributorId":329783,"corporation":false,"usgs":false,"family":"Lofton","given":"Mary","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":883298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brentrup, Jennifer A.","contributorId":194457,"corporation":false,"usgs":false,"family":"Brentrup","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, Whitney S.","contributorId":268335,"corporation":false,"usgs":false,"family":"Beck","given":"Whitney","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":883300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bhattacharya, Ruchi","contributorId":297412,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Ruchi","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":883302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brighenti, Ludmila S","contributorId":317713,"corporation":false,"usgs":false,"family":"Brighenti","given":"Ludmila","email":"","middleInitial":"S","affiliations":[{"id":69135,"text":"Universidade do Estado de Minas Gerais","active":true,"usgs":false}],"preferred":false,"id":883303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burnett, Sarah H.","contributorId":288140,"corporation":false,"usgs":false,"family":"Burnett","given":"Sarah","email":"","middleInitial":"H.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":883304,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":883305,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steele, Bethel 0000-0003-4365-4103","orcid":"https://orcid.org/0000-0003-4365-4103","contributorId":329785,"corporation":false,"usgs":false,"family":"Steele","given":"Bethel","email":"","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":883306,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":883307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cottingham, Kathryn L","contributorId":329786,"corporation":false,"usgs":false,"family":"Cottingham","given":"Kathryn L","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":883308,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dietze, Michael","contributorId":248349,"corporation":false,"usgs":false,"family":"Dietze","given":"Michael","affiliations":[],"preferred":false,"id":883309,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ewing, Holly A.","contributorId":191962,"corporation":false,"usgs":false,"family":"Ewing","given":"Holly","email":"","middleInitial":"A.","affiliations":[{"id":33413,"text":"Bates College","active":true,"usgs":false}],"preferred":false,"id":883310,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weathers, Kathleen C.","contributorId":202417,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","email":"","middleInitial":"C.","affiliations":[{"id":36424,"text":"Cary Institute of Ecosystems Studies","active":true,"usgs":false}],"preferred":false,"id":883311,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":883312,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70230098,"text":"70230098 - 2022 - Arsenic in private well water and birth outcomes in the United States","interactions":[],"lastModifiedDate":"2022-03-29T11:50:35.732821","indexId":"70230098","displayToPublicDate":"2022-03-26T06:46:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic in private well water and birth outcomes in the United States","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab005\" class=\"abstract author\" lang=\"en\"><div id=\"as005\"><h3 id=\"st010\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Background</h3><p id=\"sp0005\"><a class=\"topic-link\" title=\"Learn more about Prenatal exposure from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/prenatal-exposure\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/prenatal-exposure\">Prenatal exposure</a><span>&nbsp;</span>to drinking water with arsenic concentrations &gt;50&nbsp;μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50&nbsp;μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells—federally unregulated for drinking water contaminants—and evaluated associations with birth outcomes throughout the conterminous U.S.</p></div><div id=\"as010\"><h3 id=\"st015\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Methods</h3><p id=\"sp0010\">Using several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n&nbsp;=&nbsp;3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering.</p></div><div id=\"as015\"><h3 id=\"st020\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Results</h3><p id=\"sp0015\">We generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5&nbsp;μg/L was associated with a −1.83&nbsp;g (95% CI: −3.30, −0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10&nbsp;μg/L was associated with a −2.79&nbsp;g (95% CI: −4.99, −0.58) lower term birth weight. Associations with gestational age were null.</p></div><div id=\"as020\"><h3 id=\"st025\" class=\"u-h4 u-margin-m-top u-margin-xs-bottom\">Conclusion</h3><p id=\"sp0020\">In this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2022.107176","usgsCitation":"Bulka, C., Scannell Bryan, M., Lombard, M.A., Bartell, S., Jones, D.K., Bradley, P., Vieira, V., Silverman, D., Focazio, M.J., Toccalino, P., Daniel, J., Backer, L.C., Ayotte, J.D., Gribble, M.O., and Argos, M., 2022, Arsenic in private well water and birth outcomes in the United States: Environment International, v. 163, 107176, 12 p., https://doi.org/10.1016/j.envint.2022.107176.","productDescription":"107176, 12 p.","ipdsId":"IP-124470","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":448373,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.envint.2022.107176","text":"External Repository"},{"id":397765,"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     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\"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"163","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bulka, Catherine","contributorId":255546,"corporation":false,"usgs":false,"family":"Bulka","given":"Catherine","email":"","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":839002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scannell Bryan, Molly","contributorId":255545,"corporation":false,"usgs":false,"family":"Scannell Bryan","given":"Molly","email":"","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":839003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":839004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartell, Scott 0000-0001-7797-2906","orcid":"https://orcid.org/0000-0001-7797-2906","contributorId":289350,"corporation":false,"usgs":false,"family":"Bartell","given":"Scott","email":"","affiliations":[{"id":13696,"text":"University of California Irvine","active":true,"usgs":false}],"preferred":false,"id":839005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vieira, Veronica","contributorId":289351,"corporation":false,"usgs":false,"family":"Vieira","given":"Veronica","email":"","affiliations":[{"id":13696,"text":"University of California Irvine","active":true,"usgs":false}],"preferred":false,"id":839007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Silverman, Debra","contributorId":184133,"corporation":false,"usgs":false,"family":"Silverman","given":"Debra","affiliations":[],"preferred":false,"id":839008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":839009,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213727,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","email":"","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":839010,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Daniel, Johnni","contributorId":247808,"corporation":false,"usgs":false,"family":"Daniel","given":"Johnni","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":839011,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Backer, Lorraine C.","contributorId":198459,"corporation":false,"usgs":false,"family":"Backer","given":"Lorraine","email":"","middleInitial":"C.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":true,"id":839012,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839013,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gribble, Matthew O.","contributorId":255548,"corporation":false,"usgs":false,"family":"Gribble","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":839014,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Argos, Maria 0000-0003-4234-252X","orcid":"https://orcid.org/0000-0003-4234-252X","contributorId":204352,"corporation":false,"usgs":false,"family":"Argos","given":"Maria","email":"","affiliations":[{"id":18125,"text":"University of Illinois, Chicago","active":true,"usgs":false}],"preferred":false,"id":839015,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70255098,"text":"70255098 - 2022 - Population dynamics of Yellowstone Cutthroat Trout in Henrys Lake, Idaho","interactions":[],"lastModifiedDate":"2024-06-12T22:22:45.429017","indexId":"70255098","displayToPublicDate":"2022-03-25T17:19:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics of Yellowstone Cutthroat Trout in Henrys Lake, Idaho","docAbstract":"<p><span>Yellowstone Cutthroat Trout (YCT)&nbsp;</span><i>Oncorhynchus clarkii bouvieri</i><span>&nbsp;is a species with significant ecological and recreational value. In many YCT fisheries, managers are tasked with balancing angler expectations and fish conservation. Henrys Lake supports a popular trophy trout fishery, but the increase of nonnative Utah Chub&nbsp;</span><i>Gila atraria</i><span>&nbsp;has caused concern for YCT. We summarized long-term trends in abundance, length structure, body condition, and growth of YCT to evaluate the effect of Utah Chub. Additionally, we investigated abiotic and biotic factors influencing YCT. We examined archived hard structures to provide a comprehensive evaluation of changes in age and growth of YCT in the system. We used stocking records and catch rates of Utah Chub and trout in Henrys Lake as covariates to explain changes in YCT catch rates and growth. Catch rates varied from 1.5 to 15.4 YCT per net night during the 2002 to 2020 sampling period, but we did not identify consistent patterns. Length structure was consistently dominated by stock- to quality-length fish, and we captured few fish &gt;600 mm in total length. Relative weight of YCT was decreased from a mean ± standard deviation (SD) of 115.9 ± 16.5 in 2004 to 93.2 ± 8.2 in 2020. The age of YCT varied between 1 and 11 years; fish that we captured during 2010 to 2020 were the oldest. The majority of fish that we sampled were age 4 and younger. Total annual mortality of age-2 and older YCT was higher than other Cutthroat Trout populations (i.e., 0.70 during 2002 to 2010 and 0.60 during 2011 to 2020). Based on regression models, we identified positive relationships between catch rates of YCT, Brook Trout&nbsp;</span><i>Salvelinus fontinalis,</i><span>&nbsp;and Rainbow Trout&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;× YCT hybrid trout. We observed negative relationships between growth of YCT and abundance of Utah Chub and Brook Trout. Although we identified negative relationships, YCT growth in recent decades is as fast as or faster than earlier time periods. Results from this research suggest that major changes in YCT population dynamics are not evident over the last 20 years. This study provides insight into the factors influencing an adfluvial trout population. In particular, results from this research may be useful for managers of systems where Utah Chub have been introduced.</span></p>","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-074","usgsCitation":"McCarrick, D.K., Dillon, J., High, B., and Quist, M.C., 2022, Population dynamics of Yellowstone Cutthroat Trout in Henrys Lake, Idaho: Journal of Fish and Wildlife Management, v. 13, no. 1, p. 169-181, https://doi.org/10.3996/JFWM-21-074.","productDescription":"13 p.","startPage":"169","endPage":"181","ipdsId":"IP-131713","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-074","text":"Publisher Index Page"},{"id":430042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Henrys Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.45365706101977,\n              44.679676467620226\n            ],\n            [\n              -111.45365706101977,\n              44.60608365836251\n            ],\n            [\n              -111.3617721462157,\n              44.60608365836251\n            ],\n            [\n              -111.3617721462157,\n              44.679676467620226\n            ],\n            [\n              -111.45365706101977,\n              44.679676467620226\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"McCarrick, Darcy K.","contributorId":269700,"corporation":false,"usgs":false,"family":"McCarrick","given":"Darcy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":903389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dillon, Jeffrey","contributorId":338604,"corporation":false,"usgs":false,"family":"Dillon","given":"Jeffrey","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":903390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"High, Brett","contributorId":274499,"corporation":false,"usgs":false,"family":"High","given":"Brett","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":903391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903392,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70230171,"text":"70230171 - 2022 - Fingerprinting historical tributary contributions to floodplain sediment using bulk geochemistry","interactions":[],"lastModifiedDate":"2022-04-01T21:47:47.81119","indexId":"70230171","displayToPublicDate":"2022-03-25T09:44:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Fingerprinting historical tributary contributions to floodplain sediment using bulk geochemistry","docAbstract":"<p><span>Sediment deposition on floodplains is essential for the development and maintenance of riparian ecosystems. Upstream erosion is known to influence downstream floodplain construction, but linking these disparate processes is challenging, especially over large spatial and temporal scales. Sediment fingerprinting is thus a robust tool to establish process linkages between downstream floodplain development and sediment production in distal headwater basins. Here we use sediment geochemistry to connect historical erosion in several tributaries of the Yampa River in Colorado and Wyoming, USA, to the construction of downstream floodplains on which extensive cottonwood forests established. Using a combination of conventional techniques and the relatively novel machine-learning random forest algorithm, we build multiple fingerprints of diagnostic geochemical tracers that are then input into a Bayesian mixing model to apportion provenance of floodplain sediment. Sediment samples for provenance analysis were collected from an excavated floodplain in Deerlodge Park on the Yampa River at the rooting surface of the surrounding cottonwood forest and dominantly comprised of very fine (4Φ) sand. Fingerprinting analysis of the 4Φ fraction of collected floodplain sink (n&nbsp;=&nbsp;38) and tributary source (n&nbsp;=&nbsp;218) samples revealed floodplain sediment to be dominantly sourced from the tributaries of Muddy Creek (45&nbsp;±&nbsp;4%) and Sand Wash (42&nbsp;±&nbsp;6%). Dendrochronology results moreover indicate the Deerlodge floodplain sediment was deposited in ∼1912, which falls squarely within the time (1880–1940) these tributaries were actively eroding. Taken together, study results indicate a demonstrable link between historical tributary erosion and downstream floodplain construction and concomitant forest establishment. Our findings suggest processes operating in tributary watersheds play an important role in the dynamics of large rivers and emphasize both the need for holistic, collaborative management of sediment as an essential resource and the potential to utilize sediment fingerprinting to inform and direct river ecosystem management.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2022.106231","usgsCitation":"Kemper, J.T., Rathburn, S.L., Friedman, J.M., Nelson, J.M., Mueller, E., and Vincent, K.R., 2022, Fingerprinting historical tributary contributions to floodplain sediment using bulk geochemistry: Catena, v. 214, 106231, 16 p., https://doi.org/10.1016/j.catena.2022.106231.","productDescription":"106231, 16 p.","ipdsId":"IP-136718","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":397975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Little Snake River, Yampa River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.49822998046875,\n              40.42813291388417\n            ],\n            [\n              -108.36639404296875,\n              40.42813291388417\n            ],\n            [\n              -108.36639404296875,\n              40.48873742102282\n            ],\n            [\n              -108.49822998046875,\n              40.48873742102282\n            ],\n            [\n              -108.49822998046875,\n              40.42813291388417\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"214","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kemper, John T.","contributorId":270040,"corporation":false,"usgs":false,"family":"Kemper","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":839361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rathburn, Sara L.","contributorId":140606,"corporation":false,"usgs":false,"family":"Rathburn","given":"Sara","email":"","middleInitial":"L.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":839362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":44495,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":839363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, John M.","contributorId":83578,"corporation":false,"usgs":true,"family":"Nelson","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":839364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller, Erich R. 0000-0001-8202-154X","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":207750,"corporation":false,"usgs":false,"family":"Mueller","given":"Erich R.","affiliations":[{"id":37626,"text":"Department of Geography, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":839365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vincent, Kirk R","contributorId":289578,"corporation":false,"usgs":false,"family":"Vincent","given":"Kirk","email":"","middleInitial":"R","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":839366,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70230160,"text":"70230160 - 2022 - Spatial social value distributions for multiple user groups in a coastal national park","interactions":[],"lastModifiedDate":"2022-03-31T13:52:27.689105","indexId":"70230160","displayToPublicDate":"2022-03-25T08:45:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial social value distributions for multiple user groups in a coastal national park","docAbstract":"<p><span>Managing public lands to maximize societal benefits requires spatially explicit understanding of societal valuation, and public participation&nbsp;geographic information systems&nbsp;(PPGIS) are increasingly used in coastal settings to accomplish this task. Social Values for Ecosystem Services (SolVES), a PPGIS tool that systematizes the mapping and modeling of social values and cultural ecosystem services, is promising for use in coastal settings but has seen relatively limited applications relative to other PPGIS approaches; it has also, to our knowledge, not yet been applied in a barrier island setting. In this study, we surveyed two visitor groups and residents living near Cape Lookout National&nbsp;Seashore&nbsp;(North Carolina, USA) to understand their social values in the context of the park's management needs. We developed social-value models to evaluate differences between three user groups (fall visitors, summer visitors, and residents) and to evaluate how respondents' experiences, attitudes, and recreational activities influence the locations they value and their most strongly held value types, which included aesthetic, recreation, biodiversity, future, therapeutic, and historic values. We found that accessibility, user types and the&nbsp;</span>seasonality<span>&nbsp;of major recreational activities, and the linear configuration of the barrier island system at Cape Lookout are important influences on the social values held by visitors and residents. The modeling results provide information relevant to management at Cape Lookout and can inform the design of future PPGIS studies in coastal and marine settings.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2022.106126","usgsCitation":"Ancona, Z.H., Bagstad, K.J., Le, L., Semmens, D., Sherrouse, B.C., Murray, G., Cook, P.S., and DiDonato, E., 2022, Spatial social value distributions for multiple user groups in a coastal national park: Ocean and Coastal Management, v. 222, 106126, 17 p., https://doi.org/10.1016/j.ocecoaman.2022.106126.","productDescription":"106126, 17 p.","ipdsId":"IP-128127","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":435911,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TVMHYT","text":"USGS data release","linkHelpText":"Spatial social value distributions for multiple user groups in a coastal national park"},{"id":397932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Lookout National Seashore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.70379638671874,\n              34.56538299699511\n            ],\n            [\n              -76.2506103515625,\n              34.56538299699511\n            ],\n            [\n              -76.2506103515625,\n              34.84536693184101\n            ],\n            [\n              -76.70379638671874,\n              34.84536693184101\n            ],\n            [\n              -76.70379638671874,\n              34.56538299699511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"222","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Le, Lena","contributorId":192544,"corporation":false,"usgs":false,"family":"Le","given":"Lena","email":"","affiliations":[],"preferred":false,"id":839339,"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":839340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murray, Grant","contributorId":289567,"corporation":false,"usgs":false,"family":"Murray","given":"Grant","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":839342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cook, Philip S.","contributorId":149906,"corporation":false,"usgs":false,"family":"Cook","given":"Philip","email":"","middleInitial":"S.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":839343,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DiDonato, Eva","contributorId":149907,"corporation":false,"usgs":false,"family":"DiDonato","given":"Eva","email":"","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":839344,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70230017,"text":"70230017 - 2022 - FluOil: A novel tool for modeling the transport of oil-particle aggregates in inland waterways","interactions":[],"lastModifiedDate":"2022-03-25T13:25:57.234236","indexId":"70230017","displayToPublicDate":"2022-03-24T09:14:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"FluOil: A novel tool for modeling the transport of oil-particle aggregates in inland waterways","docAbstract":"Spilled oil in inland waterways can aggregate with mineral and organic particles to form oil-particle aggregates (OPAs). OPAs can be transported in suspension or deposited to the bed. Modeling the fate and transport of OPAs can provide useful information for making mitigation decisions. A novel open-source tool, FluOil, is developed to predict where OPAs may deposit and when they arrive in affected river/lake reaches by implementing the random walk particle tracking algorithm to represent the advection, diffusion, deposition, and resuspension of OPAs. The usability of FluOil is demonstrated with the 2010 Kalamazoo River oil spill case study. An unsteady hydrodynamic model simulates the river hydraulics and provides hydraulic data for use in FluOil. Settling velocity and critical shear stress for resuspension are the most important OPA properties concerning the transport and deposition of OPAs. Settling velocity determines the vertical distribution of OPAs and, thus, the travel speed, whereas critical shear stress determines where and when OPAs are deposited and resuspended.","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2021.771764","usgsCitation":"Li, Y., Zhu, Z., Soong, D., Khorasani, H., Wang, S., Fitzpatrick, F.A., and Garcia, M., 2022, FluOil: A novel tool for modeling the transport of oil-particle aggregates in inland waterways: Frontiers in Water, v. 3, 771764, 14 p., https://doi.org/10.3389/frwa.2021.771764.","productDescription":"771764, 14 p.","ipdsId":"IP-119066","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448381,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2021.771764","text":"Publisher Index Page"},{"id":397523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Kalamazoo River, Talmadge Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.55465698242188,\n              42.239702056572334\n            ],\n            [\n              -84.96757507324219,\n              42.239702056572334\n            ],\n            [\n              -84.96757507324219,\n              42.3468728197949\n            ],\n            [\n              -85.55465698242188,\n              42.3468728197949\n            ],\n            [\n              -85.55465698242188,\n              42.239702056572334\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Yilan","contributorId":289194,"corporation":false,"usgs":false,"family":"Li","given":"Yilan","email":"","affiliations":[{"id":62064,"text":"Department of Civil, Structural, and Environmental Engineering, University at Buffalo, NY","active":true,"usgs":false}],"preferred":false,"id":838679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Zhenduo","contributorId":206524,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhenduo","email":"","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":838680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soong, David 0000-0003-0404-2163","orcid":"https://orcid.org/0000-0003-0404-2163","contributorId":206523,"corporation":false,"usgs":true,"family":"Soong","given":"David","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khorasani, Hamed","contributorId":289241,"corporation":false,"usgs":false,"family":"Khorasani","given":"Hamed","email":"","affiliations":[],"preferred":false,"id":838782,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Shu","contributorId":289195,"corporation":false,"usgs":false,"family":"Wang","given":"Shu","email":"","affiliations":[{"id":62065,"text":"School of Civil and Resource Engineering, University of Science and Technology Beiijing, Beijing, 100083 PR China","active":true,"usgs":false}],"preferred":false,"id":838682,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":196543,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":838785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":838684,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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