{"pageNumber":"422","pageRowStart":"10525","pageSize":"25","recordCount":184582,"records":[{"id":70227170,"text":"70227170 - 2022 - Quantifying the influence of different biocrust community states and their responses to warming temperatures on soil biogeochemistry in field and mesocosm studies","interactions":[],"lastModifiedDate":"2022-01-03T16:58:16.370099","indexId":"70227170","displayToPublicDate":"2021-12-07T10:47:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the influence of different biocrust community states and their responses to warming temperatures on soil biogeochemistry in field and mesocosm studies","docAbstract":"<p><span>Biocrusts influence soil biogeochemistry by fixing carbon (C) and nitrogen (N) and through leachate inputs to soils. Functional rates can vary among biocrust community states and in response to edaphic properties, heterotrophic microbial activity, and global change. Using soils and biocrusts from the Colorado Plateau, Utah, USA, we aimed to quantify the influence of early-successional (ES) and late-successional (LS) biocrust community states on soil biogeochemistry. In a field setting, we found soil was less “fertile” under ES than LS biocrust, but ES biocrust had a relative influence 1.3 times greater than LS biocrust on soil fertility. Leachate collected from LS biocrust had, on average, 6 times more organic C and 1.7 times more dissolved N than ES biocrust, but concentrations of phosphorus (P) and inorganic N did not differ among the two biocrust types. To disentangle influences of biocrusts and soil properties on biogeochemical pools, we constructed mesocosms from homogenized soil and left the surface bare or covered with ES or LS biocrust, before assignment to ambient or warmed (+5&nbsp;°C) temperature treatments for 3&nbsp;months. Multivariate biogeochemical properties differed among cover types, yet all exhibited losses of P, N, and organic C and nearly half of the biogeochemical variables considered did not differ among cover types. Mesocosms with LS biocrust retained more dissolved N, supported 8 additional, significant correlations among biogeochemical pools of the biocrust and mineral soil layer on average, and lost fewer of these correlations under warming. Overall, while soils under LS biocrusts were more fertile (i.e., had higher nutrient concentrations) than under ES, we did not find evidence implicating leachate as the primary driver of this difference. Biocrust influences on soil fertility were greater when mineral soil nutrients were in lower concentrations, highlighting the value of even incipient biocrusts for dryland functioning.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2021.115633","usgsCitation":"Ferrrenberg, S., Tucker, C.L., Reibold, R.H., Howell, A.J., and Reed, S., 2022, Quantifying the influence of different biocrust community states and their responses to warming temperatures on soil biogeochemistry in field and mesocosm studies: Geoderma, v. 409, 115633, 13 p., https://doi.org/10.1016/j.geoderma.2021.115633.","productDescription":"115633, 13 p.","ipdsId":"IP-133236","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1977162","text":"Publisher Index Page"},{"id":393751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.764404296875,\n              36.4433803110554\n            ],\n            [\n              -109.127197265625,\n              36.4433803110554\n            ],\n            [\n              -109.127197265625,\n              37.34395908944491\n            ],\n            [\n              -109.764404296875,\n              37.34395908944491\n            ],\n            [\n              -109.764404296875,\n              36.4433803110554\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"409","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferrrenberg, Scott","contributorId":270736,"corporation":false,"usgs":false,"family":"Ferrrenberg","given":"Scott","email":"","affiliations":[{"id":56204,"text":"Department of Biology, New Mexico State University, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":829887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Colin L","contributorId":270737,"corporation":false,"usgs":false,"family":"Tucker","given":"Colin","email":"","middleInitial":"L","affiliations":[{"id":56205,"text":"U.S. National Forest Service, Northern Research Station, Houghton, MI 49931","active":true,"usgs":false}],"preferred":false,"id":829888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reibold, Robin H. 0000-0002-3323-487X","orcid":"https://orcid.org/0000-0002-3323-487X","contributorId":207499,"corporation":false,"usgs":true,"family":"Reibold","given":"Robin","email":"","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":829891,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228218,"text":"70228218 - 2022 - Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada","interactions":[],"lastModifiedDate":"2022-03-17T16:51:31.185083","indexId":"70228218","displayToPublicDate":"2021-12-07T09:33:20","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":"Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada","docAbstract":"<p><span>Severe droughts are predicted to become more frequent in the future, and the consequences of such droughts on forests can be dramatic, resulting in massive tree mortality, rapid change in forest structure and composition, and substantially increased risk of catastrophic fire. Forest managers have tools at their disposal to try to mitigate these effects but are often faced with limited resources, forcing them to make choices about which parts of the landscape to target for treatment. Such planning can greatly benefit from landscape vulnerability assessments, but many existing vulnerability analyses are unvalidated and not grounded in robust empirical datasets. We combined robust sets of ground-based plot and remote sensing data, collected during the 2012–2016 California drought, to develop rigorously validated tools for assessing forest vulnerability to drought-related canopy tree mortality for the mixed conifer forests of the Sequoia and Kings Canyon national parks and potentially for mixed conifer forests in the Sierra Nevada as a whole. Validation was carried out using a large external dataset. The best models included normalized difference vegetation index (NDVI), elevation, and species identity. Models indicated that tree survival probability decreased with greenness (as measured by NDVI) and elevation, particularly if trees were growing slowly. Overall, models showed good calibration and validation, especially for&nbsp;</span><i>Abies concolor</i><span>, which comprise a large majority of the trees in many mixed conifer forests in the Sierra Nevada. Our models tended to overestimate mortality risk for&nbsp;</span><i>Calocedrus decurrens</i><span>&nbsp;and underestimate risk for pine species, in the latter case probably due to pine bark beetle outbreak dynamics. Validation results indicated dangers of overfitting, as well as showing that the inclusion of trees already under attack by bark beetles at the time of sampling can give false confidence in model strength, while also biasing predictions. These vulnerability tools should be useful to forest managers trying to assess which parts of their landscape were vulnerable during the 2012–2016 drought, and, with additional validation, may prove useful for ongoing assessments and predictions of future forest vulnerability.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2514","usgsCitation":"Das, A., Slaton, M.R., Mallory, J., Asner, G.P., Martin, R.E., and Hardwick, P., 2022, Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada: Ecological Applications, v. 32, no. 2, e2514, 19 p., https://doi.org/10.1002/eap.2514.","productDescription":"e2514, 19 p.","ipdsId":"IP-131799","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436030,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6JKJW","text":"USGS data release","linkHelpText":"Calibration and Validation Data and Model Coefficients for Mixed Conifer Vulnerability Project from Sequoia and Kings Canyon National Park 2015 to 2019"},{"id":395619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sequoia and Kings Canyon National Parks, Sierra Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.33349609375,\n              35.55010533588552\n            ],\n            [\n              -117.828369140625,\n              35.55010533588552\n            ],\n            [\n              -117.828369140625,\n              37.339591851359174\n            ],\n            [\n              -119.33349609375,\n              37.339591851359174\n            ],\n            [\n              -119.33349609375,\n              35.55010533588552\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slaton, Michele R","contributorId":274868,"corporation":false,"usgs":false,"family":"Slaton","given":"Michele","email":"","middleInitial":"R","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":833459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mallory, Jeffrey","contributorId":274869,"corporation":false,"usgs":false,"family":"Mallory","given":"Jeffrey","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":833460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":833461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Roberta E.","contributorId":201234,"corporation":false,"usgs":false,"family":"Martin","given":"Roberta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":833462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hardwick, Paul","contributorId":261559,"corporation":false,"usgs":false,"family":"Hardwick","given":"Paul","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":833463,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226860,"text":"70226860 - 2022 - Complex demographic responses to contrasting climate drivers lead to divergent population trends across the range of a threatened alpine plant","interactions":[],"lastModifiedDate":"2021-12-16T12:53:03.866205","indexId":"70226860","displayToPublicDate":"2021-12-07T06:51:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Complex demographic responses to contrasting climate drivers lead to divergent population trends across the range of a threatened alpine plant","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0050\"><span>Alpine plants&nbsp;are likely to be particularly vulnerable to climate change because of their restricted distributions and sensitivity to rapid environmental shifts occurring in high-elevation ecosystems. The well-studied Haleakalā silversword (‘āhinahina,&nbsp;</span><i>Argyroxiphium sandwicense</i><span>&nbsp;</span>subsp.<span>&nbsp;</span><i>macrocephalum</i>) already exhibits substantial climate-associated population decline, and offers the opportunity to understand the ecological and demographic mechanisms that underlie ongoing and predicted range shifts. We use nearly four decades of demographic monitoring for this threatened Hawaiian species, in combination with other biological, ecological and climate data to explore demographic responses across its entire range. We construct and independently validate population models for two elevation zones representing the species’ lower trailing and higher stable regions. Differences in population growth rate (lambda) between trailing and stable regions were influenced most strongly by lower survival of juvenile and small adult size classes, as well as by lower recruitment and lower survival of seedlings and large adults in the trailing region. Furthermore, seed production appears to have decreased from the 1980’s to present in the trailing region, and is now significantly less than in the stable region. Lambda and several underlying vital rates were significantly associated with wetter dry season conditions in the lower trailing region, indicating water limitation. In the higher elevation stable region, in contrast, lambda and vital rates were associated with warmer air temperatures, indicating cold limitation. These contrasting demographic patterns and climate dependencies lead to a high probability of extinction over the next century in the lower region, where most plants occur, but zero probability of the same in the higher region, according to stochastic population projections. Drier future scenarios further increase the probability of extinction at low elevations. The combined results illustrate the complexity in the demographic response and future viability that can occur across the range of a single species.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elesevier","doi":"10.1016/j.gecco.2021.e01954","usgsCitation":"Fortini, L., Krushelnycky, P., Drake, D., Starr, F., Starr, K., and Chimera, C.G., 2022, Complex demographic responses to contrasting climate drivers lead to divergent population trends across the range of a threatened alpine plant: Global Ecology and Conservation, v. 33, e01954, 17 p., https://doi.org/10.1016/j.gecco.2021.e01954.","productDescription":"e01954, 17 p.","ipdsId":"IP-080030","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":449451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2021.e01954","text":"Publisher Index Page"},{"id":393004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":828522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krushelnycky, Paul","contributorId":265727,"corporation":false,"usgs":false,"family":"Krushelnycky","given":"Paul","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":828523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drake, Donald","contributorId":270149,"corporation":false,"usgs":false,"family":"Drake","given":"Donald","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":828524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starr, Forest","contributorId":270150,"corporation":false,"usgs":false,"family":"Starr","given":"Forest","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":828525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Starr, Kim","contributorId":270151,"corporation":false,"usgs":false,"family":"Starr","given":"Kim","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":828526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chimera, Charles G.","contributorId":177629,"corporation":false,"usgs":false,"family":"Chimera","given":"Charles","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":828527,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227805,"text":"70227805 - 2022 - Capacity of two Sierra Nevada rivers for reintroduction of anadromous salmonids: Insights from a high-resolution view","interactions":[],"lastModifiedDate":"2022-02-01T19:04:08.428192","indexId":"70227805","displayToPublicDate":"2021-12-06T14:03:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Capacity of two Sierra Nevada rivers for reintroduction of anadromous salmonids: Insights from a high-resolution view","docAbstract":"<p>Historically, anadromous steelhead <i>Oncorhynchus mykiss</i> and spring-run Chinook Salmon <i>O. tshawytscha</i> used high-elevation rivers in the Sierra Nevada of California but were extirpated in the 20th century by construction of impassable dams. Plans to reintroduce the fish by opening migratory passage across the dams and reservoirs can only succeed if upstream habitats have the capacity to support viable populations of each species. To estimate capacity in the Tuolumne and Merced rivers of the central Sierra Nevada, we used a high-resolution approach based on remote sensing and dynamic habitat modeling. Our results suggested that for both species in both systems, sediment grain sizes would support widespread spawning and the water temperatures, depths, and velocities would generate ample capacity for fry and juveniles. However, the unregulated Merced River was consistently too warm for adult Chinook Salmon to hold in the dry season prior to spawning, while the regulated Tuolumne River maintained a cooler, more stable thermal regime with a capacity for thousands of holding adults. In our high-resolution approach, we also discovered several specific physical controls on life history expression, including thermal constraints on the timing of spawning, hydraulic prompts for downstream migration of fry, divergence of the hydraulic niches of steelhead and Chinook Salmon, and a key but uncertain role for thermal tolerance in adult Chinook Salmon. Our results suggested that steelhead reintroduction could succeed in either system and Chinook Salmon could succeed in the Tuolumne River if passage strategies account for large numbers of migrant fry and juveniles driven downstream by winter storms and snowmelt. The Merced River appeared too warm for adult Chinook Salmon, which raises questions about the current limited understanding of thermal tolerance in holding adults. Our study shows how a high-resolution approach can provide valuable insights on specific limiting factors that must be addressed for reintroduction to succeed.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10334","usgsCitation":"Boughton, D.A., Harrison, L.R., John, S.N., Bond, R.M., Nicol, C.L., Legleiter, C.J., and Richardson, R.T., 2022, Capacity of two Sierra Nevada rivers for reintroduction of anadromous salmonids: Insights from a high-resolution view: Transactions of the American Fisheries Society, v. 151, no. 1, p. 13-41, https://doi.org/10.1002/tafs.10334.","productDescription":"29 p.","startPage":"13","endPage":"41","ipdsId":"IP-123624","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467211,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/tafs.10334","text":"External Repository"},{"id":436031,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MUPT5X","text":"USGS data release","linkHelpText":"Topographic, temperature, and sediment grain size data used to evaluate potential habitat for anadromous salmonids on the upper Merced and Tuolumne Rivers in California"},{"id":395229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.67907714843751,\n              37.08585785263673\n            ],\n            [\n              -119.16320800781249,\n              37.08585785263673\n            ],\n            [\n              -119.16320800781249,\n              38.07404145941957\n            ],\n            [\n              -121.67907714843751,\n              38.07404145941957\n            ],\n            [\n              -121.67907714843751,\n              37.08585785263673\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"151","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Boughton, David A.","contributorId":172477,"corporation":false,"usgs":false,"family":"Boughton","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":832337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":832338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"John, Sara N.","contributorId":273050,"corporation":false,"usgs":false,"family":"John","given":"Sara","email":"","middleInitial":"N.","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":832339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bond, Rosealea M. 0000-0003-0939-2007","orcid":"https://orcid.org/0000-0003-0939-2007","contributorId":272853,"corporation":false,"usgs":false,"family":"Bond","given":"Rosealea","email":"","middleInitial":"M.","affiliations":[{"id":56398,"text":"Institute of Marine Sciences, University of California Santa Cruz and National Marine Fisheries Service, Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":832340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicol, Colin L.","contributorId":201719,"corporation":false,"usgs":false,"family":"Nicol","given":"Colin","email":"","middleInitial":"L.","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":832341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":832342,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richardson, Ryan T. 0000-0002-7864-8670","orcid":"https://orcid.org/0000-0002-7864-8670","contributorId":272854,"corporation":false,"usgs":false,"family":"Richardson","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":56400,"text":"River Design Group","active":true,"usgs":false}],"preferred":false,"id":832343,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70229760,"text":"70229760 - 2022 - Visualizing social-ecological intensities for management of recreation visitors in a multiuse system","interactions":[],"lastModifiedDate":"2022-03-17T16:29:05.715051","indexId":"70229760","displayToPublicDate":"2021-12-06T11:23:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Visualizing social-ecological intensities for management of recreation visitors in a multiuse system","docAbstract":"<p><span>Accounting for the variation of visitor conflicts and ecological disturbance of&nbsp;outdoor recreation&nbsp;activities across space and time can cause difficulty for managers seeking to make decisions in social-ecological systems (SESs). We develop a method to quantify and visualize social and ecological intensities resulting from outdoor recreation. We demonstrate the utility of our method at Valentine National Wildlife Refuge, where we conducted onsite surveys for an entire year of recreationists participating in consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing) and nonconsumptive (e.g., hiking) activities. We use survey results and combine them with expert consensus by engaging refuge managers and scientists (i.e., Delphi method) to chart patterns in social (e.g., visitor conflicts) and ecological (e.g., damages to natural resources) intensities across multiple spatial and temporal scales. We highlight unexpected patterns that are revealed by collectively considering multi-activity groups through space and time and combining different survey methods (onsite, Delphi method). Based on the consensus reached using the&nbsp;</span>Delphi method<span>, the consumptive group had the greatest potential for social conflicts and ecological disturbances. Social and ecological intensities (i.e., hotspots) of recreation varied across lake types and seasons, highlighting high-intensity areas and periods on the refuge. Accounting for diverse outdoor recreation activities and coinciding social and ecological intensities will allow managers of SESs the ability to concomitantly preserve ecological resources, prioritize conservation efforts, and minimize visitor conflicts. We demonstrate the utility and ease of use of this technique, which can be implemented by managers and scientists within their respective SES of interest.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.114224","usgsCitation":"DaRugna, O., Chizinski, C., Pope, K.L., Powell, L.A., and Kaemik, M.A., 2022, Visualizing social-ecological intensities for management of recreation visitors in a multiuse system: Journal of Environmental Management, v. 304, 114224, 10 p., https://doi.org/10.1016/j.jenvman.2021.114224.","productDescription":"114224, 10 p.","ipdsId":"IP-127699","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":397258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Valentine National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.74874877929688,\n              42.40115038362433\n            ],\n            [\n              -100.32852172851562,\n              42.40115038362433\n            ],\n            [\n              -100.32852172851562,\n              42.61880201144831\n            ],\n            [\n              -100.74874877929688,\n              42.61880201144831\n            ],\n            [\n              -100.74874877929688,\n              42.40115038362433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"304","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DaRugna, O. A.","contributorId":288682,"corporation":false,"usgs":false,"family":"DaRugna","given":"O. A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":838218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chizinski, C. J.","contributorId":288683,"corporation":false,"usgs":false,"family":"Chizinski","given":"C. J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":838219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, L. A.","contributorId":273152,"corporation":false,"usgs":false,"family":"Powell","given":"L.","email":"","middleInitial":"A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":838221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaemik, M. A.","contributorId":288686,"corporation":false,"usgs":false,"family":"Kaemik","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":838222,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228221,"text":"70228221 - 2022 - Crowding, climate, and the case for social distancing among trees","interactions":[],"lastModifiedDate":"2022-03-17T16:54:09.157512","indexId":"70228221","displayToPublicDate":"2021-12-06T09:44:32","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":"Crowding, climate, and the case for social distancing among trees","docAbstract":"<p><span>In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate–vegetation–disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets—each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence—in a post-hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk (</span><i>P</i><sub><i>m</i></sub><span>) was higher in crowded local neighborhoods that burned in wet years (</span><i>P</i><sub><i>m</i></sub><span>&nbsp;=&nbsp;42%) compared with sparse neighborhoods that burned during drought (</span><i>P</i><sub><i>m</i></sub><span>&nbsp;=&nbsp;30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought-related mortality over short timespans (&lt;7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2507","usgsCitation":"Furniss, T.J., Das, A., van Mantgem, P., Stephenson, N.L., and Lutz, J.A., 2022, Crowding, climate, and the case for social distancing among trees: Ecological Applications, v. 32, no. 2, e2507, 14 p., https://doi.org/10.1002/eap.2507.","productDescription":"e2507, 14 p.","ipdsId":"IP-126098","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436032,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92SJXAD","text":"USGS data release","linkHelpText":"Sequoia and Yosemite National Parks Mortality and Fire Data (1990-2019) for Competition-Fire-Drought Interaction Analysis"},{"id":395622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.8173828125,\n              35.77325759103725\n            ],\n            [\n              -118.57543945312501,\n              37.4530574713902\n            ],\n            [\n              -119.44335937499999,\n              38.31149091244452\n            ],\n            [\n              -119.761962890625,\n              38.302869955150044\n            ],\n            [\n              -119.94873046875,\n              38.14751758025121\n            ],\n            [\n              -119.93225097656251,\n              37.51844023887861\n            ],\n            [\n              -119.20166015625,\n              36.71687068791304\n            ],\n            [\n              -118.59191894531251,\n              35.67068501330236\n            ],\n            [\n              -118.1634521484375,\n              35.505400093441324\n            ],\n            [\n              -117.740478515625,\n              35.61711648382185\n            ],\n            [\n              -117.8173828125,\n              35.77325759103725\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Furniss, Tucker J.","contributorId":181754,"corporation":false,"usgs":false,"family":"Furniss","given":"Tucker","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":833464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, James A.","contributorId":139178,"corporation":false,"usgs":false,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":833468,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226883,"text":"70226883 - 2022 - Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat","interactions":[],"lastModifiedDate":"2022-06-01T15:07:22.372804","indexId":"70226883","displayToPublicDate":"2021-12-06T07:09:24","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":"Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 &lt; AUC &lt; 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2510","usgsCitation":"Conlisk, E., Golet, G., Reynolds, M., Barbaree, B., Sesser, K., Byrd, K.B., Veloz, S., and Reiter, M., 2022, Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat: Ecological Applications, v. 32, no. 4, e2510, 20 p., https://doi.org/10.1002/eap.2510.","productDescription":"e2510, 20 p.","ipdsId":"IP-121785","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":449459,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9286402","text":"External Repository"},{"id":393097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Conlisk, Erin","contributorId":270185,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":828625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golet, Gregory","contributorId":270186,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":828626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Mark","contributorId":270187,"corporation":false,"usgs":false,"family":"Reynolds","given":"Mark","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":828627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbaree, Blake","contributorId":270188,"corporation":false,"usgs":false,"family":"Barbaree","given":"Blake","email":"","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":828628,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sesser, Kristin","contributorId":270189,"corporation":false,"usgs":false,"family":"Sesser","given":"Kristin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":828629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":828630,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Veloz, Sam","contributorId":270190,"corporation":false,"usgs":false,"family":"Veloz","given":"Sam","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":828631,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reiter, Matthew E.","contributorId":270191,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","middleInitial":"E.","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":828632,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70227200,"text":"70227200 - 2022 - Velocity-porosity relations in carbonate and siliciclastic subduction zone input materials","interactions":[],"lastModifiedDate":"2022-02-08T22:31:49.373536","indexId":"70227200","displayToPublicDate":"2021-12-05T07:39:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Velocity-porosity relations in carbonate and siliciclastic subduction zone input materials","docAbstract":"<p>The mechanical, physical, and frictional properties of incoming materials play an important role in subduction zone structure and slip behavior because these properties influence the strength of the accretionary wedge and megathrust plate boundary faults. Incoming sediment sections often show an increase in compressional wave speed (Vp) and a decrease in porosity with depth due to consolidation. These relations allow seismic-velocity models to be used to elucidate properties and conditions at depth. However, variations in these properties are controlled by lithology and composition as well as cementation and diagenesis. We present an analysis of shipboard measurements of Vp&nbsp;and porosity on incoming sediment cores from International Ocean Discovery Program (IODP) expeditions at the Hikurangi Margin, Nankai Trough, Aleutian Trench, Middle America Trench, and Sunda Trench. Porosity for these samples ranges from 5% to 85% and Vp&nbsp;ranges from 1.5 to 6&nbsp;km/s. Vp-porosity relations developed by Erikson &amp; Jarrad&nbsp;(1998),&nbsp;https://doi.org/10.1029/98JB02128&nbsp;and Hoffman &amp; Tobin&nbsp;(2004)&nbsp;https://10.2973/odp.proc.sr.190196.355.2004, with a critical porosity of ∼30%, can represent carbonate-poor (&lt;50 wt% CaCO3), mainly hemipelagic, incoming sediment regardless of the margin. But these relations tend to underestimate porosity in incoming sediments with carbonate content greater than 50 wt%, which appear to have a critical porosity of between 45% and 50%. This discrepancy will lead to inaccuracy in estimates of fluid budget and overpressure in subduction zones. The velocity-porosity relation in carbonate sediments is non-unique due to the complexity that results from the greater susceptibility of carbonate rocks to diagenetic processes.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC010074","usgsCitation":"Jeppson, T.N., and Kitajima, H., 2022, Velocity-porosity relations in carbonate and siliciclastic subduction zone input materials: Geochemistry, Geophysics, Geosystems, v. 23, no. 1, e2021GC010074, 15 p., https://doi.org/10.1029/2021GC010074.","productDescription":"e2021GC010074, 15 p.","ipdsId":"IP-130458","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489114,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gc010074","text":"Publisher Index Page"},{"id":393842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Jeppson, Tamara Nicole 0000-0001-5526-5530","orcid":"https://orcid.org/0000-0001-5526-5530","contributorId":248768,"corporation":false,"usgs":true,"family":"Jeppson","given":"Tamara","email":"","middleInitial":"Nicole","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":830061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kitajima, Hiroko","contributorId":270795,"corporation":false,"usgs":false,"family":"Kitajima","given":"Hiroko","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":830062,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226859,"text":"70226859 - 2022 - Climate extremes as drivers of surface-water-quality trends in the United States","interactions":[],"lastModifiedDate":"2021-12-16T12:55:51.685069","indexId":"70226859","displayToPublicDate":"2021-12-05T06:53:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Climate extremes as drivers of surface-water-quality trends in the United States","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0035\">Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic matter on the landscape. Many studies predict future changes in water-quality related to climate changes; however, fewer studies specifically document changes in water quality related to changes in climate, and they are usually limited in geographic scope. Recently, the<span>&nbsp;</span><a class=\"topic-link\" title=\"Learn more about U.S. from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/united-states-of-america\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/united-states-of-america\">U.S.</a><span>&nbsp;</span>Geological Survey's National Water-Quality Program reported nearly 12,000 trends in concentration and load for numerous water-quality constituents, including nutrients, sediment, major ions, and carbon. The results provide an unprecedented opportunity to examine sites across the conterminous United States for changes in water quality related to climate changes. We used published water-quality trends, modeled using the method of Weighted Regressions on Time, Season and Discharge, and calculated trends in climate extremes indices, using a modified Mann-Kendall trend method. The water-quality and the climate extremes trends were combined to identify areas in the conterminous United States where changes in climate extremes may have changed water quality. We investigated the water-quality trends in these areas to determine whether the trends related to changes in climate. We found that it was important to go beyond spatial correlation and examine trends on a watershed scale to investigate key drivers of trends. We found successful management practices in Iowa to reduce chloride concentrations, despite increases in icing days. For sediment, it appeared that management practices were having a larger effect than climate changes. For nutrients, complex forces affecting water quality make it difficult to unequivocally attribute water-quality change to climate change.</p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.152165","usgsCitation":"Ryberg, K.R., and Chanat, J.G., 2022, Climate extremes as drivers of surface-water-quality trends in the United States: Science of the Total Environment, v. 809, 152165, 12 p., https://doi.org/10.1016/j.scitotenv.2021.152165.","productDescription":"152165, 12 p.","ipdsId":"IP-130945","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488976,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.152165","text":"Publisher Index Page"},{"id":393005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n      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        43.62509\n              ],\n              [\n                -77.73789,\n                43.62906\n              ],\n              [\n                -76.82003,\n                43.62878\n              ],\n              [\n                -76.5,\n                44.01846\n              ],\n              [\n                -76.375,\n                44.09631\n              ],\n              [\n                -75.31821,\n                44.81645\n              ],\n              [\n                -74.867,\n                45.00048\n              ],\n              [\n                -73.34783,\n                45.00738\n              ],\n              [\n                -71.50506,\n                45.0082\n              ],\n              [\n                -71.405,\n                45.255\n              ],\n              [\n                -71.08482,\n                45.30524\n              ],\n              [\n                -70.66,\n                45.46\n              ],\n              [\n                -70.305,\n                45.915\n              ],\n              [\n                -69.99997,\n                46.69307\n              ],\n              [\n                -69.23722,\n                47.44778\n              ],\n              [\n                -68.905,\n                47.185\n              ],\n              [\n                -68.23444,\n                47.35486\n              ],\n              [\n                -67.79046,\n                47.06636\n              ],\n              [\n                -67.79134,\n                45.70281\n              ],\n              [\n                -67.13741,\n                45.13753\n              ],\n              [\n                -66.96466,\n                44.8097\n              ],\n              [\n                -68.03252,\n                44.3252\n              ],\n              [\n                -69.06,\n                43.98\n              ],\n              [\n                -70.11617,\n                43.68405\n              ],\n              [\n                -70.64548,\n                43.09024\n              ],\n              [\n                -70.81489,\n                42.8653\n              ],\n              [\n                -70.825,\n                42.335\n              ],\n              [\n                -70.495,\n                41.805\n              ],\n              [\n                -70.08,\n                41.78\n              ],\n              [\n                -70.185,\n                42.145\n              ],\n              [\n                -69.88497,\n                41.92283\n              ],\n              [\n                -69.96503,\n                41.63717\n              ],\n              [\n                -70.64,\n                41.475\n              ],\n              [\n                -71.12039,\n                41.49445\n              ],\n              [\n                -71.86,\n                41.32\n              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38.31921\n              ],\n              [\n                -76.35,\n                39.15\n              ],\n              [\n                -76.54272,\n                38.71762\n              ],\n              [\n                -76.32933,\n                38.08326\n              ],\n              [\n                -76.99,\n                38.23999\n              ],\n              [\n                -76.30162,\n                37.91794\n              ],\n              [\n                -76.25874,\n                36.9664\n              ],\n              [\n                -75.9718,\n                36.89726\n              ],\n              [\n                -75.86804,\n                36.55125\n              ],\n              [\n                -75.72749,\n                35.55074\n              ],\n              [\n                -76.36318,\n                34.80854\n              ],\n              [\n                -77.39763,\n                34.51201\n              ],\n              [\n                -78.05496,\n                33.92547\n              ],\n              [\n                -78.55435,\n                33.86133\n              ],\n              [\n                -79.06067,\n                33.49395\n              ],\n              [\n                -79.20357,\n                33.15839\n              ],\n              [\n                -80.30132,\n                32.50935\n              ],\n              [\n                -80.86498,\n                32.0333\n              ],\n              [\n                -81.33629,\n                31.44049\n              ],\n              [\n                -81.49042,\n                30.72999\n              ],\n              [\n                -81.31371,\n                30.03552\n              ],\n              [\n                -80.98,\n                29.18\n              ],\n              [\n                -80.53558,\n                28.47213\n              ],\n              [\n                -80.53,\n                28.04\n              ],\n              [\n                -80.05654,\n                26.88\n              ],\n              [\n                -80.08801,\n                26.20576\n              ],\n              [\n                -80.13156,\n                25.81677\n              ],\n              [\n                -80.38103,\n                25.20616\n              ],\n              [\n                -80.68,\n                25.08\n              ],\n              [\n                -81.17213,\n                25.20126\n              ],\n              [\n                -81.33,\n                25.64\n              ],\n              [\n                -81.71,\n                25.87\n              ],\n              [\n                -82.24,\n                26.73\n              ],\n              [\n                -82.70515,\n                27.49504\n              ],\n              [\n                -82.85526,\n                27.88624\n              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             30.15999\n              ],\n              [\n                -89.41373,\n                29.89419\n              ],\n              [\n                -89.43,\n                29.48864\n              ],\n              [\n                -89.21767,\n                29.29108\n              ],\n              [\n                -89.40823,\n                29.15961\n              ],\n              [\n                -89.77928,\n                29.30714\n              ],\n              [\n                -90.15463,\n                29.11743\n              ],\n              [\n                -90.88022,\n                29.14854\n              ],\n              [\n                -91.62678,\n                29.677\n              ],\n              [\n                -92.49906,\n                29.5523\n              ],\n              [\n                -93.22637,\n                29.78375\n              ],\n              [\n                -93.84842,\n                29.71363\n              ],\n              [\n                -94.69,\n                29.48\n              ],\n              [\n                -95.60026,\n                28.73863\n              ],\n              [\n                -96.59404,\n                28.30748\n              ],\n              [\n                -97.14,\n                27.83\n              ],\n              [\n                -97.37,\n                27.38\n              ],\n              [\n                -97.38,\n                26.69\n              ],\n              [\n                -97.33,\n                26.21\n              ],\n              [\n                -97.14,\n                25.87\n              ],\n              [\n                -97.53,\n                25.84\n              ],\n              [\n                -98.24,\n                26.06\n              ],\n              [\n                -99.02,\n                26.37\n              ],\n              [\n                -99.3,\n                26.84\n              ],\n              [\n                -99.52,\n                27.54\n              ],\n              [\n                -100.11,\n                28.11\n              ],\n              [\n                -100.45584,\n                28.69612\n              ],\n              [\n                -100.9576,\n                29.38071\n              ],\n              [\n                -101.6624,\n                29.7793\n              ],\n              [\n                -102.48,\n                29.76\n              ],\n              [\n                -103.11,\n                28.97\n              ],\n              [\n                -103.94,\n                29.27\n              ],\n              [\n                -104.45697,\n                29.57196\n              ],\n              [\n                -104.70575,\n                30.12173\n              ],\n              [\n                -105.03737,\n                30.64402\n              ],\n              [\n                -105.63159,\n                31.08383\n              ],\n              [\n                -106.1429,\n                31.39995\n              ],\n              [\n                -106.50759,\n                31.75452\n              ],\n              [\n                -108.24,\n                31.75485\n              ],\n              [\n                -108.24194,\n                31.34222\n              ],\n              [\n                -109.035,\n                31.34194\n              ],\n              [\n                -111.02361,\n                31.33472\n              ],\n              [\n                -113.30498,\n                32.03914\n              ],\n              [\n                -114.815,\n                32.52528\n              ],\n              [\n                -114.72139,\n                32.72083\n              ],\n              [\n                -115.99135,\n                32.61239\n              ],\n              [\n                -117.12776,\n                32.53534\n              ],\n              [\n                -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"809","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227045,"text":"70227045 - 2022 - Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence","interactions":[],"lastModifiedDate":"2022-01-25T17:37:41.709676","indexId":"70227045","displayToPublicDate":"2021-12-04T09:04:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Understanding the controls on the amount and persistence of soil organic carbon (C) is essential for predicting its sensitivity to global change. The response may depend on whether C is unprotected, isolated within aggregates, or protected from decomposition by mineral associations. Here, we present a global synthesis of the relative influence of environmental factors on soil organic C partitioning among pools, abundance in each pool (mg C g<sup>−1</sup>&nbsp;soil), and persistence (as approximated by radiocarbon abundance) in relatively unprotected particulate and protected mineral-bound pools. We show that C within particulate and mineral-associated pools consistently differed from one another in degree of persistence and relationship to environmental factors. Soil depth was the best predictor of C abundance and persistence, though it accounted for more variance in persistence. Persistence of all C pools decreased with increasing mean annual temperature (MAT) throughout the soil profile, whereas persistence increased with increasing wetness index (MAP/PET) in subsurface soils (30–176&nbsp;cm). The relationship of C abundance (mg C g<sup>−1</sup>&nbsp;soil) to climate varied among pools and with depth. Mineral-associated C in surface soils (&lt;30&nbsp;cm) increased more strongly with increasing wetness index than the free particulate C, but both pools showed attenuated responses to the wetness index at depth. Overall, these relationships suggest a strong influence of climate on soil C properties, and a potential loss of soil C from protected pools in areas with decreasing wetness. Relative persistence and abundance of C pools varied significantly among land cover types and soil parent material lithologies. This variability in each pool's relationship to environmental factors suggests that not all soil organic C is equally vulnerable to global change. Therefore, projections of future soil organic C based on patterns and responses of bulk soil organic C may be misleading.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16023","usgsCitation":"Heckman, K., Hicks Pries, C.E., Lawrence, C., Rasmussen, C., Crow, S.E., Hoyt, A., von Fromm, S., Shi, Z., Stoner, S., McGrath, C., Beem-Miller, J., Asefaw Berhe, A., Blankinship, J., Keiluweit, M., Marín-Spiotta, E., Monroe, J.G., Plante, A., Schimel, J., Sierra, C., Thompson, A., and Wagai, R., 2022, Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence: Global Change Biology, v. 28, no. 3, p. 1178-1196, https://doi.org/10.1111/gcb.16023.","productDescription":"19 p.","startPage":"1178","endPage":"1196","ipdsId":"IP-127650","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":393502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Heckman, Katherine","contributorId":270436,"corporation":false,"usgs":false,"family":"Heckman","given":"Katherine","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":829342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hicks Pries, Caitlin E.","contributorId":270437,"corporation":false,"usgs":false,"family":"Hicks Pries","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":36404,"text":"Dartmouth University","active":true,"usgs":false}],"preferred":false,"id":829343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":829344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasmussen, Craig","contributorId":270438,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Craig","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":829345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crow, Susan E.","contributorId":270439,"corporation":false,"usgs":false,"family":"Crow","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":829346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoyt, Alison M.","contributorId":270440,"corporation":false,"usgs":false,"family":"Hoyt","given":"Alison M.","affiliations":[{"id":39621,"text":"Max Planck Institute for Biogeochemistry","active":true,"usgs":false}],"preferred":false,"id":829347,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"von Fromm, Sophie F.","contributorId":270441,"corporation":false,"usgs":false,"family":"von Fromm","given":"Sophie F.","affiliations":[{"id":39621,"text":"Max Planck Institute for Biogeochemistry","active":true,"usgs":false}],"preferred":false,"id":829348,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shi, Zheng","contributorId":270442,"corporation":false,"usgs":false,"family":"Shi","given":"Zheng","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":829349,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stoner, Shane","contributorId":270443,"corporation":false,"usgs":false,"family":"Stoner","given":"Shane","affiliations":[{"id":39621,"text":"Max Planck Institute for Biogeochemistry","active":true,"usgs":false}],"preferred":false,"id":829350,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McGrath, Casey","contributorId":270444,"corporation":false,"usgs":false,"family":"McGrath","given":"Casey","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":829351,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Beem-Miller, Jeffery","contributorId":270445,"corporation":false,"usgs":false,"family":"Beem-Miller","given":"Jeffery","email":"","affiliations":[{"id":39621,"text":"Max Planck Institute for Biogeochemistry","active":true,"usgs":false}],"preferred":false,"id":829352,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Asefaw Berhe, Asmeret","contributorId":270446,"corporation":false,"usgs":false,"family":"Asefaw Berhe","given":"Asmeret","email":"","affiliations":[{"id":16805,"text":"University of California, Merced","active":true,"usgs":false}],"preferred":false,"id":829353,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Blankinship, Joseph C.","contributorId":270447,"corporation":false,"usgs":false,"family":"Blankinship","given":"Joseph C.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":829354,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Keiluweit, Marco","contributorId":270448,"corporation":false,"usgs":false,"family":"Keiluweit","given":"Marco","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":829355,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Marín-Spiotta, Erika","contributorId":270452,"corporation":false,"usgs":false,"family":"Marín-Spiotta","given":"Erika","affiliations":[{"id":56168,"text":"Department of Geography, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":829357,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Monroe, J. Grey","contributorId":270449,"corporation":false,"usgs":false,"family":"Monroe","given":"J.","email":"","middleInitial":"Grey","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":829356,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Plante, Alain F.","contributorId":270453,"corporation":false,"usgs":false,"family":"Plante","given":"Alain F.","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":829358,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schimel, Joshua","contributorId":270455,"corporation":false,"usgs":false,"family":"Schimel","given":"Joshua","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":829359,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Sierra, Carlos A.","contributorId":270462,"corporation":false,"usgs":false,"family":"Sierra","given":"Carlos A.","affiliations":[{"id":56169,"text":"Max-Planck-Institute for Biogeochemistry","active":true,"usgs":false}],"preferred":false,"id":829362,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Thompson, Aaron","contributorId":270457,"corporation":false,"usgs":false,"family":"Thompson","given":"Aaron","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":829360,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wagai, Rota","contributorId":270459,"corporation":false,"usgs":false,"family":"Wagai","given":"Rota","affiliations":[{"id":36407,"text":"Institute for Agro-Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":829361,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70227194,"text":"70227194 - 2022 - Mismatch-induced growth reductions in a clade of Arctic-breeding shorebirds are rarely mitigated by increasing temperatures","interactions":[],"lastModifiedDate":"2022-01-25T17:38:33.909532","indexId":"70227194","displayToPublicDate":"2021-12-04T08:55:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Mismatch-induced growth reductions in a clade of Arctic-breeding shorebirds are rarely mitigated by increasing temperatures","docAbstract":"<p><span>In seasonal environments subject to climate change, organisms typically show phenological changes. As these changes are usually stronger in organisms at lower trophic levels than those at higher trophic levels, mismatches between consumers and their prey may occur during the consumers’ reproduction period. While in some species a trophic mismatch induces reductions in offspring growth, this is not always the case. This variation may be caused by the relative strength of the mismatch, or by mitigating factors like increased temperature-reducing energetic costs. We investigated the response of chick growth rate to arthropod abundance and temperature for six populations of ecologically similar shorebirds breeding in the Arctic and sub-Arctic (four subspecies of Red Knot&nbsp;</span><i>Calidris canutus</i><span>, Great Knot&nbsp;</span><i>C</i><span>.&nbsp;</span><i>tenuirostris</i><span>&nbsp;and Surfbird&nbsp;</span><i>C</i><span>.&nbsp;</span><i>virgata</i><span>). In general, chicks experienced growth benefits (measured as a condition index) when hatching before the seasonal peak in arthropod abundance, and growth reductions when hatching after the peak. The moment in the season at which growth reductions occurred varied between populations, likely depending on whether food was limiting growth before or after the peak. Higher temperatures led to faster growth on average, but could only compensate for increasing trophic mismatch for the population experiencing the coldest conditions. We did not find changes in the timing of peaks in arthropod availability across the study years, possibly because our series of observations was relatively short; timing of hatching displayed no change over the years either. Our results suggest that a trend in trophic mismatches may not yet be evident; however, we show Arctic-breeding shorebirds to be vulnerable to this phenomenon and vulnerability to depend on seasonal prey dynamics.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16025","usgsCitation":"Lameris, T., Tomkovich, P.S., Johnson, J., Morrison, R.G., Decicco, L., Dementyev, M.N., Tulp, I., Lisovski, S., Gill, R., ten Horn, J., Piersma, T., Pohlen, Z., Schekkerman, H., Soloviev, M., Syroechkovsky, E., van Gils, J.A., and Zhemchuzhnikov, M., 2022, Mismatch-induced growth reductions in a clade of Arctic-breeding shorebirds are rarely mitigated by increasing temperatures: Global Change Biology, v. 28, no. 3, p. 829-847, https://doi.org/10.1111/gcb.16025.","productDescription":"19 p.","startPage":"829","endPage":"847","ipdsId":"IP-135408","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":449466,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16025","text":"External Repository"},{"id":436033,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VDI8RZ","text":"USGS data release","linkHelpText":"Measurements of Surfbirds (Calidris virgata), Southcentral Alaska 1997-1999"},{"id":393853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","volume":"28","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lameris, Thomas","contributorId":270786,"corporation":false,"usgs":false,"family":"Lameris","given":"Thomas","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":830037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tomkovich, Pavel S.","contributorId":55333,"corporation":false,"usgs":false,"family":"Tomkovich","given":"Pavel","email":"","middleInitial":"S.","affiliations":[{"id":6930,"text":"Zoological Museum of Moscow, MV Lomonosov University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":830094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, James A.","contributorId":84649,"corporation":false,"usgs":true,"family":"Johnson","given":"James A.","affiliations":[],"preferred":false,"id":830095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, R.I. Guy","contributorId":173839,"corporation":false,"usgs":false,"family":"Morrison","given":"R.I.","email":"","middleInitial":"Guy","affiliations":[],"preferred":false,"id":830096,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Decicco, Lucas","contributorId":270833,"corporation":false,"usgs":false,"family":"Decicco","given":"Lucas","affiliations":[],"preferred":false,"id":830097,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dementyev, Maksim N.","contributorId":138560,"corporation":false,"usgs":false,"family":"Dementyev","given":"Maksim","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":830098,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tulp, Ingrid","contributorId":243504,"corporation":false,"usgs":false,"family":"Tulp","given":"Ingrid","email":"","affiliations":[],"preferred":false,"id":830099,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":830038,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lisovski, Simeon","contributorId":213809,"corporation":false,"usgs":false,"family":"Lisovski","given":"Simeon","email":"","affiliations":[{"id":38883,"text":"Schweizerische Vogelwarte","active":true,"usgs":false}],"preferred":false,"id":830100,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"ten Horn, Job","contributorId":209707,"corporation":false,"usgs":false,"family":"ten Horn","given":"Job","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":830101,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Piersma, Theunis","contributorId":45863,"corporation":false,"usgs":true,"family":"Piersma","given":"Theunis","affiliations":[],"preferred":false,"id":830102,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pohlen, Z.","contributorId":243268,"corporation":false,"usgs":false,"family":"Pohlen","given":"Z.","email":"","affiliations":[],"preferred":false,"id":830103,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schekkerman, Hans","contributorId":243495,"corporation":false,"usgs":false,"family":"Schekkerman","given":"Hans","email":"","affiliations":[],"preferred":false,"id":830104,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Soloviev, Mikhail","contributorId":209711,"corporation":false,"usgs":false,"family":"Soloviev","given":"Mikhail","email":"","affiliations":[{"id":37973,"text":"Department of Vertebrate Zoology, Biological Faculty, Lomonosov Moscow State University","active":true,"usgs":false}],"preferred":false,"id":830105,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Syroechkovsky, E.","contributorId":58976,"corporation":false,"usgs":true,"family":"Syroechkovsky","given":"E.","email":"","affiliations":[],"preferred":false,"id":830106,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"van Gils, Jan A.","contributorId":141170,"corporation":false,"usgs":false,"family":"van Gils","given":"Jan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":830039,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhemchuzhnikov, Mikhail","contributorId":270834,"corporation":false,"usgs":false,"family":"Zhemchuzhnikov","given":"Mikhail","email":"","affiliations":[],"preferred":false,"id":830107,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70241623,"text":"70241623 - 2022 - Seasonal impoundment management reduces nitrogen cycling but not resilience to surface fire in a tidal wetland","interactions":[],"lastModifiedDate":"2023-03-24T13:27:12.928099","indexId":"70241623","displayToPublicDate":"2021-12-04T08:18:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal impoundment management reduces nitrogen cycling but not resilience to surface fire in a tidal wetland","docAbstract":"<p><span>Hydrology and salinity regimes of many impounded wetlands are manipulated to provide seasonal habitats for migratory&nbsp;<a class=\"topic-link\" title=\"Learn more about waterfowl from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/waterfowl\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/waterfowl\">waterfowl</a>, with little-known consequences for ecosystem structure and function. Managed hydrology can alter ecosystems by directly changing soil properties and processes and by influencing plant community dynamics. Additionally, management history may influence ecosystem response to disturbance, including fires. To better understand how wetland management regime influences ecosystem response to disturbance, we quantified elevation,&nbsp;<a class=\"topic-link\" title=\"Learn more about soil nitrogen from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/soil-nitrogen\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/soil-nitrogen\">soil nitrogen</a>&nbsp;concentrations and process rates, and plant community structure and diversity in a natural experiment following the 2018 Branscombe Fire. We measured paired burned-unburned patches in both tidally-influenced and managed, seasonally-impounded wetlands in Suisun Marsh, California, USA. Unburned ecosystem structure and nutrient cycling differed by wetland management history; unburned impounded wetlands were ∼1&nbsp;m lower in elevation and plant community composition was dominated by succulents whereas the unburned tidal wetland was dominated by graminoids. Unburned impounded&nbsp;<a class=\"topic-link\" title=\"Learn more about wetland soil from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/wetland-soil\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/wetland-soil\">wetland soil</a>&nbsp;nitrogen cycling (potential nitrification and denitrification) rates were &lt;28% of those measured in unburned tidal wetland soils and soil extractable nitrate, ammonium, and&nbsp;</span><a class=\"topic-link\" title=\"Learn more about dissolved inorganic phosphorus from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/dissolved-inorganic-phosphorus\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/dissolved-inorganic-phosphorus\">dissolved inorganic phosphorus</a><span>&nbsp;concentrations were also substantially lower in unburned impounded than unburned tidal wetlands. Despite these differences in pre-disturbance (i.e., unburned) conditions, all soil processes recovered to baseline levels within 6 months after surface fire, and we found no evidence of plant community change 1 year after fire in either wetland management type. Overall, water management history exerted stronger control on ecosystem processes and structure than surface fire disturbance. Low extractable soil nitrate and potential denitrification rates may indicate limitation of soil nitrogen removal in impounded wetlands, with implications for downstream environmental quality and eutrophication across managed landscapes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.114153","usgsCitation":"Jones, S., Schutte, C.A., Roberts, B., and Thorne, K., 2022, Seasonal impoundment management reduces nitrogen cycling but not resilience to surface fire in a tidal wetland: Journal of Environmental Management, v. 303, 114153, 11 p., https://doi.org/10.1016/j.jenvman.2021.114153.","productDescription":"114153, 11 p.","ipdsId":"IP-134289","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":449468,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2021.114153","text":"Publisher Index Page"},{"id":436034,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DWBSQT","text":"USGS data release","linkHelpText":"Soil, Plant, and Elevation Characteristics of Tidal and Managed Impounded Wetlands in Suisun Marsh, California, USA (2018-2019)"},{"id":414698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Suisun Marsh","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.01718926989348,\n              38.18457183754458\n            ],\n            [\n              -122.01718926989348,\n              38.080375985659515\n            ],\n            [\n              -121.8946168874855,\n              38.080375985659515\n            ],\n            [\n              -121.8946168874855,\n              38.18457183754458\n            ],\n            [\n              -122.01718926989348,\n              38.18457183754458\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"303","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schutte, Charles A","contributorId":303410,"corporation":false,"usgs":false,"family":"Schutte","given":"Charles","email":"","middleInitial":"A","affiliations":[{"id":65797,"text":"Louisiana Universities Marine Consortium, Chauvin, LA; Rowan University (present)","active":true,"usgs":false}],"preferred":false,"id":867526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Brian J","contributorId":146207,"corporation":false,"usgs":false,"family":"Roberts","given":"Brian J","affiliations":[{"id":16627,"text":"Louisiana Universities Marine Consortium (LUMCON)","active":true,"usgs":false}],"preferred":false,"id":867527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867528,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70247510,"text":"70247510 - 2022 - Estimating pelagic primary production in lakes: Comparison of 14C incubation and free-water O2 approaches","interactions":[],"lastModifiedDate":"2023-08-11T13:22:06.505287","indexId":"70247510","displayToPublicDate":"2021-12-04T06:48:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimating pelagic primary production in lakes: Comparison of <sup>14</sup>C incubation and free-water O<sub>2</sub> approaches","title":"Estimating pelagic primary production in lakes: Comparison of 14C incubation and free-water O2 approaches","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Historically, estimates of pelagic primary production in lake ecosystems were made by measuring the uptake of carbon-14 (<sup>14</sup>C)-labeled inorganic carbon in samples incubated under laboratory or in situ conditions. However, incubation approaches are increasingly being replaced by methods that analyze diel changes in high-frequency in situ data such as free-water dissolved oxygen (O<sub>2</sub>). While there is a rich literature on the comparison of approaches for estimating primary production using incubations (e.g.,<span>&nbsp;</span><sup>14</sup>C and O<sub>2</sub><span>&nbsp;</span>bottle experiments), as well for approaches using high-frequency data (e.g., diel O<sub>2</sub><span>&nbsp;</span>and CO<sub>2</sub><span>&nbsp;</span>metabolism models), there are few direct comparisons of<span>&nbsp;</span><sup>14</sup>C incubations and free-water O<sub>2</sub><span>&nbsp;</span>approaches for estimating primary production. We used 20 lake-years of concurrent measurements of primary production quantified from high-frequency free-water O<sub>2</sub><span>&nbsp;</span>data and<span>&nbsp;</span><sup>14</sup>C incubations in four different lakes (4–7 years per lake) to compare these different approaches. Across all lakes, 61% of the<span>&nbsp;</span><sup>14</sup>C production estimates were within the 95% credible intervals of the free-water O<sub>2</sub><span>&nbsp;</span>production estimates. Error-in-variable regressions support the assumption that<span>&nbsp;</span><sup>14</sup>C methods estimate a production value between gross primary production and net primary production and the bottle effect is constant across the entire range of production values considered here. There was little evidence that daily pelagic, epilimnetic estimates of primary production differed substantially based on the selection of free-water O<sub>2</sub><span>&nbsp;</span>or<span>&nbsp;</span><sup>14</sup>C approaches in these lakes during summer stratified conditions.</p></div></div>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lom3.10471","usgsCitation":"Lottig, N.R., Phillips, J., Batt, R.D., Scordo, F., Williamson, T.J., Carpenter, S.R., Chandra, S., Hanson, P.C., Solomon, C.T., Vanni, M.J., and Zwart, J.A., 2022, Estimating pelagic primary production in lakes: Comparison of 14C incubation and free-water O2 approaches: Limnology and Oceanography: Methods, v. 20, no. 1, p. 34-45, https://doi.org/10.1002/lom3.10471.","productDescription":"12 p.","startPage":"34","endPage":"45","ipdsId":"IP-126978","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":419693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lottig, Noah R.","contributorId":172031,"corporation":false,"usgs":false,"family":"Lottig","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Joseph 0000-0003-2016-1306","orcid":"https://orcid.org/0000-0003-2016-1306","contributorId":318157,"corporation":false,"usgs":false,"family":"Phillips","given":"Joseph","email":"","affiliations":[{"id":69342,"text":"Holar University","active":true,"usgs":false}],"preferred":false,"id":879918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":196242,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":879919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scordo, Facundo","contributorId":298282,"corporation":false,"usgs":false,"family":"Scordo","given":"Facundo","email":"","affiliations":[{"id":64520,"text":"Instituto Argentino de Oceanografía","active":true,"usgs":false}],"preferred":false,"id":879920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williamson, Tanner J.","contributorId":223165,"corporation":false,"usgs":false,"family":"Williamson","given":"Tanner","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":879921,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carpenter, Stephen R. 0000-0001-8097-8700","orcid":"https://orcid.org/0000-0001-8097-8700","contributorId":196945,"corporation":false,"usgs":false,"family":"Carpenter","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879922,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":879923,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":879924,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":879925,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vanni, Michael J.","contributorId":204106,"corporation":false,"usgs":false,"family":"Vanni","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":36846,"text":"Department of Zoology, Miami University (Ohio)","active":true,"usgs":false}],"preferred":false,"id":879926,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":879927,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70226885,"text":"70226885 - 2022 - Geostatistical mapping of salinity conditioned on borehole logs, Montebello Oil Field, California","interactions":[],"lastModifiedDate":"2022-03-15T16:38:07.413106","indexId":"70226885","displayToPublicDate":"2021-12-03T07:01:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical mapping of salinity conditioned on borehole logs, Montebello Oil Field, California","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (<i>n</i>&nbsp;=&nbsp;4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (<i>n</i>&nbsp;=&nbsp;8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.</p></div></div>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13155","usgsCitation":"Terry, N., Day-Lewis, F., Landon, M.K., Land, M., Stanton, J.S., and Lane, J.W., 2022, Geostatistical mapping of salinity conditioned on borehole logs, Montebello Oil Field, California: Groundwater, v. 60, no. 2, p. 242-261, https://doi.org/10.1111/gwat.13155.","productDescription":"20 p.","startPage":"242","endPage":"261","ipdsId":"IP-118997","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":449470,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gwat.13155","text":"External Repository"},{"id":436035,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L0XGEG","text":"USGS data release","linkHelpText":"Data used to estimate groundwater salinity above the Montebello oil field (California, USA)"},{"id":393095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Montebello Oil Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.0703125,\n              33.742612777346885\n            ],\n            [\n              -116.3836669921875,\n              33.742612777346885\n            ],\n            [\n              -116.3836669921875,\n              34.048108084909835\n            ],\n            [\n              -117.0703125,\n              34.048108084909835\n            ],\n            [\n              -117.0703125,\n              33.742612777346885\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"60","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":828636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":828637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanton, Jennifer S. 0000-0002-2520-753X jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828640,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - 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,{"id":70226862,"text":"70226862 - 2022 - The presence of denitrifiers in bacterial communities of urban stormwater best management practices (BMPs)","interactions":[],"lastModifiedDate":"2022-01-25T17:36:32.166054","indexId":"70226862","displayToPublicDate":"2021-12-03T06:48:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"The presence of denitrifiers in bacterial communities of urban stormwater best management practices (BMPs)","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Stormwater best management practices (BMPs) are engineered structures that attempt to mitigate the impacts of stormwater, which can include nitrogen inputs from the surrounding drainage area. The goal of this study was to assess bacterial community composition in different types of stormwater BMP soils to establish whether a particular BMP type harbors more denitrification potential. Soil sampling took place over the summer of 2015 following precipitation events. Soils were sampled from four bioretention facilities, four dry ponds, four surface sand filters, and one dry swale. 16S rRNA gene analysis of extracted DNA and RNA amplicons indicated high bacterial diversity in the soils of all BMP types sampled. An abundance of denitrifiers was also indicated in the extracted DNA using presence/absence of<span>&nbsp;</span><i>nirS, nirK</i>, and<span>&nbsp;</span><i>nosZ</i><span>&nbsp;</span>denitrification genes. BMP soil bacterial communities were impacted by the surrounding soil physiochemistry. Based on the identification of a metabolically-active community of denitrifiers, this study has indicated that denitrification could potentially occur under appropriate conditions in all types of BMP sampled, including surface sand filters that are often viewed as providing low potential for denitrification. The carbon content of incoming stormwater could be providing bacterial communities with denitrification conditions. The findings of this study are especially relevant for land managers in watersheds with legacy nitrogen from former agricultural land use.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00267-021-01529-z","usgsCitation":"Hall, N., Sikaroodi, M., Hogan, D.M., Jones, R.C., and Gillevet, P., 2022, The presence of denitrifiers in bacterial communities of urban stormwater best management practices (BMPs): Environmental Management, v. 69, p. 89-110, https://doi.org/10.1007/s00267-021-01529-z.","productDescription":"22 p.","startPage":"89","endPage":"110","ipdsId":"IP-112221","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":449472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-021-01529-z","text":"Publisher Index Page"},{"id":393003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Montgomery County","city":"Clarksburg","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.29482650756836,\n              39.22001911674211\n            ],\n            [\n              -77.25242614746094,\n              39.22001911674211\n            ],\n            [\n              -77.25242614746094,\n              39.25285999099622\n            ],\n            [\n              -77.29482650756836,\n              39.25285999099622\n            ],\n            [\n              -77.29482650756836,\n              39.22001911674211\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"69","noUsgsAuthors":false,"publicationDate":"2021-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Natalie C. 0000-0002-6448-162X nhall@usgs.gov","orcid":"https://orcid.org/0000-0002-6448-162X","contributorId":223255,"corporation":false,"usgs":true,"family":"Hall","given":"Natalie","email":"nhall@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":828528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sikaroodi, Masoumeh","contributorId":270156,"corporation":false,"usgs":false,"family":"Sikaroodi","given":"Masoumeh","email":"","affiliations":[{"id":56098,"text":"George Mason University, Dept. of Biology","active":true,"usgs":false}],"preferred":false,"id":828530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, R. Christian","contributorId":270157,"corporation":false,"usgs":false,"family":"Jones","given":"R.","email":"","middleInitial":"Christian","affiliations":[{"id":56099,"text":"George Mason University, Dept. of Environmental Science and Policy; PEREC Director","active":true,"usgs":false}],"preferred":false,"id":828532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillevet, Patrick","contributorId":270155,"corporation":false,"usgs":false,"family":"Gillevet","given":"Patrick","email":"","affiliations":[{"id":56098,"text":"George Mason University, Dept. of Biology","active":true,"usgs":false}],"preferred":false,"id":828529,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70229711,"text":"70229711 - 2022 - Population genomics of free-ranging Great Plains white-tailed and mule deer reflects a long history of interspecific hybridization","interactions":[],"lastModifiedDate":"2022-03-16T16:59:22.351383","indexId":"70229711","displayToPublicDate":"2021-12-02T11:54:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Population genomics of free-ranging Great Plains white-tailed and mule deer reflects a long history of interspecific hybridization","docAbstract":"<p><span>Hybridization is a natural process at species-range boundaries that may variably promote the speciation process or break down species barriers but minimally will influence management outcomes of distinct populations. White-tailed deer (</span><i>Odocoileus virginianus</i><span>) and mule deer (</span><i>Odocoileus hemionus</i><span>) have broad and overlapping distributions in North America and a recognized capacity for interspecific hybridization. In response to contemporary environmental change to any of one or multiple still-unknown factors, mule deer range is contracting westward accompanied by a westward expansion of white-tailed deer, leading to increasing interactions, opportunities for gene flow, and associated conservation implications. To quantify genetic diversity, phylogenomic structure, and dynamics of hybridization in sympatric populations of white-tailed and mule deer, we used mitochondrial cytochrome b data coupled with SNP loci discovered with double-digest restriction site-associated DNA sequencing. We recovered 25,018 SNPs across 92 deer samples from both species, collected from two regions of western Kansas. Eight individuals with unambiguous external morphology representing both species were of hybrid origin (8.7%), and represented the product of multi-generational backcrossing. Mitochondrial data showed both ancient and recent directional discordance with morphological species assignments, reflecting a legacy of mule deer males mating with white-tailed deer females. Mule deer had lower genetic diversity than white-tailed deer, and both mitochondrial and nuclear data suggest contemporary mule deer effective population decline. Landscape genetic analyses show relative isolation between the two study regions for white-tailed deer, but greater connectivity among mule deer, with predominant movement from north to south. Collectively, our results suggest a long history of gene flow between these species in the Great Plains and hint at evolutionary processes that purge incompatible functional genomic elements as a result of hybridization. Surviving hybrids evidently may be reproductive, but with unknown consequences for the future integrity of these species, population trajectories, or relative susceptibility to emerging pathogens.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/eva.13330","usgsCitation":"Combe, F.J., Jaster, L., Ricketts, A., Haukos, D.A., and Hope, A., 2022, Population genomics of free-ranging Great Plains white-tailed and mule deer reflects a long history of interspecific hybridization: Evolutionary Applications, v. 15, no. 1, p. 111-131, https://doi.org/10.1111/eva.13330.","productDescription":"21 p.","startPage":"111","endPage":"131","ipdsId":"IP-132503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449474,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eva.13330","text":"External 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,{"id":70229712,"text":"70229712 - 2022 - Warming conditions boost reproductive output for a northern gopher tortoise population","interactions":[],"lastModifiedDate":"2022-03-16T15:47:19.149065","indexId":"70229712","displayToPublicDate":"2021-12-02T11:45:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Warming conditions boost reproductive output for a northern gopher tortoise population","docAbstract":"<p>The effects of climate change on at-risk species will depend on how life history processes respond to climate and whether the seasonal timing of local climate changes overlaps with species-specific windows of climate sensitivity. For long-lived, iteroparous species like gopher tortoises <i>Gopherus polyphemus</i>, climate likely has a greater influence on reproduction than on adult survival. Our objective was to estimate the timing, magnitude, and direction of climate-driven effects on gopher tortoise reproductive output using a 25 yr dataset collected in southeastern Georgia, USA, near the northern edge of the species’ range. We assessed the timing of climate effects on reproductive output (both probability of reproduction and clutch size) by fitting models with climate covariates (maximum temperature, precipitation, and temperature range) summarized at all possible time intervals (in 1 mo increments) within the 24 mo period prior to the summer census date. We then fit a final model of reproductive output as a function of the identified climate variables and time windows using a Bayesian mixture model. Probability of reproduction was positively correlated with the prior year’s April-May maximum temperature, and clutch size was positively correlated with the prior year’s June maximum temperature. April-May and June maximum temperatures have increased over the past 3 decades at the study site, which likely led to an increase in clutch size of approximately 1 egg (15% increase over a mean of 6.5 eggs). However, the net effect of climate change on gopher tortoise population dynamics will depend on whether there are opposing or reinforcing climate responses for other demographic rates.</p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01155","usgsCitation":"Hunter, E.A., Loope, K., Drake, K.K., Hanley, K., Jones, D.N., Shoemaker, K., and Rostal, D., 2022, Warming conditions boost reproductive output for a northern gopher tortoise population: Endangered Species Research, v. 46, p. 215-226, https://doi.org/10.3354/esr01155.","productDescription":"12 p.","startPage":"215","endPage":"226","ipdsId":"IP-132399","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":449478,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01155","text":"Publisher Index Page"},{"id":397162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Fort Stewart Army Reserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.683349609375,\n              32.11747489684617\n            ],\n            [\n              -81.727294921875,\n              32.10816944421472\n            ],\n            [\n              -81.78909301757812,\n              32.12910537866883\n            ],\n            [\n              -81.81243896484375,\n              32.10816944421472\n            ],\n            [\n              -81.82891845703125,\n              32.10467965495091\n            ],\n            [\n              -81.85638427734375,\n              32.051152857201714\n            ],\n            [\n              -81.85089111328125,\n              32.0232133942454\n            ],\n            [\n              -81.86187744140625,\n              31.991771310172094\n            ],\n            [\n              -81.89071655273438,\n              31.949831760406877\n            ],\n            [\n              -81.88522338867188,\n              31.91953017247695\n            ],\n            [\n              -81.63116455078124,\n              31.84373252620705\n            ],\n            [\n              -81.62017822265625,\n              31.85773063158148\n            ],\n            [\n              -81.60781860351561,\n              31.85889704445453\n            ],\n            [\n              -81.57073974609375,\n              31.87522527511162\n            ],\n            [\n              -81.55838012695312,\n              31.865895211796346\n            ],\n            [\n              -81.36474609375,\n              31.950997006605856\n            ],\n            [\n              -81.3372802734375,\n              31.948666499428395\n            ],\n            [\n              -81.30020141601562,\n              32.001088607540446\n            ],\n            [\n              -81.41006469726562,\n              32.09769967633269\n            ],\n            [\n              -81.46774291992186,\n              32.10002639514208\n            ],\n            [\n              -81.683349609375,\n              32.11747489684617\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loope, Kevin J.","contributorId":288536,"corporation":false,"usgs":false,"family":"Loope","given":"Kevin J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":838062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drake, K. 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Jr.","contributorId":288539,"corporation":false,"usgs":false,"family":"Jones","given":"Douglas","suffix":"Jr.","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":838065,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shoemaker, Kevin T.","contributorId":288541,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin T.","affiliations":[{"id":61793,"text":"University of Nevada – Reno","active":true,"usgs":false}],"preferred":false,"id":838066,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rostal, David C.","contributorId":288543,"corporation":false,"usgs":false,"family":"Rostal","given":"David C.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":838067,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70255072,"text":"70255072 - 2022 - An introduction to decision science for conservation","interactions":[],"lastModifiedDate":"2024-06-12T16:17:16.570459","indexId":"70255072","displayToPublicDate":"2021-12-02T10:51:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"An introduction to decision science for conservation","docAbstract":"<p><span>Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms:&nbsp;</span><i>decision science</i><span>,&nbsp;</span><i>decision theory</i><span>,&nbsp;</span><i>decision analysis</i><span>,&nbsp;</span><i>structured decision-making</i><span>, and&nbsp;</span><i>decision-support tools</i><span>. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.</span></p>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13868","usgsCitation":"Hemming, V., Camaclang, A.E., Adams, M., Burgman, M., Carbeck, K., Carwardine, J., Chades, I., Chalifour, L., Converse, S.J., Davidson, L., Garrard, G.E., Finn, R., Fleri, J.R., Huard, J., Mayfield, H., McDonald Madden, E., Naujokaitis-Lewis, I., Possingham, H.P., Rumpff, L., Runge, M.C., Stewart, D., Tulloch, V.J., Walshe, T., and Martin, T.G., 2022, An introduction to decision science for conservation: Conservation Biology, v. 36, no. 1, e13868, 16 p., https://doi.org/10.1111/cobi.13868.","productDescription":"e13868, 16 p.","ipdsId":"IP-126293","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449481,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9302662","text":"External Repository"},{"id":430020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hemming, Victoria","contributorId":338511,"corporation":false,"usgs":false,"family":"Hemming","given":"Victoria","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":903323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camaclang, Abbey E.","contributorId":338512,"corporation":false,"usgs":false,"family":"Camaclang","given":"Abbey","email":"","middleInitial":"E.","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":903324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Megan","contributorId":338513,"corporation":false,"usgs":false,"family":"Adams","given":"Megan","email":"","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":903325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burgman, Mark","contributorId":150633,"corporation":false,"usgs":false,"family":"Burgman","given":"Mark","email":"","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":903559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carbeck, Katherine","contributorId":338751,"corporation":false,"usgs":false,"family":"Carbeck","given":"Katherine","email":"","affiliations":[],"preferred":false,"id":903560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carwardine, Josie","contributorId":338752,"corporation":false,"usgs":false,"family":"Carwardine","given":"Josie","email":"","affiliations":[],"preferred":false,"id":903561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chades, Iadine","contributorId":338753,"corporation":false,"usgs":false,"family":"Chades","given":"Iadine","affiliations":[],"preferred":false,"id":903562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chalifour, Lia","contributorId":338754,"corporation":false,"usgs":false,"family":"Chalifour","given":"Lia","email":"","affiliations":[],"preferred":false,"id":903563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":903322,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Davidson, Lindsay","contributorId":338755,"corporation":false,"usgs":false,"family":"Davidson","given":"Lindsay","email":"","affiliations":[],"preferred":false,"id":903564,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Garrard, Georgia E.","contributorId":197116,"corporation":false,"usgs":false,"family":"Garrard","given":"Georgia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":903565,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Finn, Riley","contributorId":338756,"corporation":false,"usgs":false,"family":"Finn","given":"Riley","email":"","affiliations":[],"preferred":false,"id":903566,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fleri, Jesse R.","contributorId":237004,"corporation":false,"usgs":false,"family":"Fleri","given":"Jesse","email":"","middleInitial":"R.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":903567,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Huard, Jacqueline","contributorId":338757,"corporation":false,"usgs":false,"family":"Huard","given":"Jacqueline","email":"","affiliations":[],"preferred":false,"id":903568,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mayfield, Helen","contributorId":338758,"corporation":false,"usgs":false,"family":"Mayfield","given":"Helen","email":"","affiliations":[],"preferred":false,"id":903569,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"McDonald Madden, Eve","contributorId":338759,"corporation":false,"usgs":false,"family":"McDonald Madden","given":"Eve","affiliations":[],"preferred":false,"id":903570,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Naujokaitis-Lewis, Ilona","contributorId":338760,"corporation":false,"usgs":false,"family":"Naujokaitis-Lewis","given":"Ilona","email":"","affiliations":[],"preferred":false,"id":903571,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Possingham, Hugh P.","contributorId":20882,"corporation":false,"usgs":false,"family":"Possingham","given":"Hugh","email":"","middleInitial":"P.","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":903572,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Rumpff, Libby","contributorId":197117,"corporation":false,"usgs":false,"family":"Rumpff","given":"Libby","email":"","affiliations":[],"preferred":false,"id":903573,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":903574,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Stewart, Daniel","contributorId":338761,"corporation":false,"usgs":false,"family":"Stewart","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":903575,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Tulloch, Vivitskaia J. D.","contributorId":338762,"corporation":false,"usgs":false,"family":"Tulloch","given":"Vivitskaia","email":"","middleInitial":"J. D.","affiliations":[],"preferred":false,"id":903576,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Walshe, Terry","contributorId":28151,"corporation":false,"usgs":true,"family":"Walshe","given":"Terry","affiliations":[],"preferred":false,"id":903577,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Martin, Tara G.","contributorId":71687,"corporation":false,"usgs":true,"family":"Martin","given":"Tara","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":903578,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70226656,"text":"70226656 - 2022 - Spatial and temporal controls on proglacial erosion rates: A comparison of four basins on Mount Rainier, 1960 to 2017","interactions":[],"lastModifiedDate":"2022-02-15T16:10:26.168967","indexId":"70226656","displayToPublicDate":"2021-12-02T10:33:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal controls on proglacial erosion rates: A comparison of four basins on Mount Rainier, 1960 to 2017","docAbstract":"<p>The retreat of alpine glaciers since the mid-19th century has triggered rapid landscape adjustments in many headwater basins. However, the degree to which decadal-scale glacier retreat is associated with systematic or substantial changes in overall coarse sediment export, with the potential to impact downstream river dynamics, remains poorly understood. Here, we use repeat topographic surveys to assess geomorphic change in four partly-glaciated basins on a stratovolcano (Mount Rainier) in Washington State at roughly decadal intervals from 1960 to 2017. The proglacial extents of the four basins show distinct geomorphic trajectories, ranging from substantial and sustained net erosion to relatively inactive with net deposition. These different trajectories correspond to differences in initial (1960) valley floor gradients, and can be effectively understood as valley floor grade adjustments. Significant erosion was most often accomplished by debris flows triggered by extreme rainfall or glacial outburst floods, though a single rockfall mobilized more material than all other events combined. Year-to-year runoff events had little measurable geomorphic impact. Exported material tended to accumulate in broad deposits within several kilometers of source areas and largely remained there through the end of the study period. Over 10- to 100-year timescales, we nd that the impact of glacier retreat on coarse sediment yield may then vary substantially according to the geometry and storage trends of the newly-exposed valley floor; the timing of that response may also be dictated, and potentially obscured, by stochastic and/or extreme events.</p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5274","usgsCitation":"Anderson, S.W., and Shean, D., 2022, Spatial and temporal controls on proglacial erosion rates: A comparison of four basins on Mount Rainier, 1960 to 2017: Earth Surface Processes and Landforms, v. 47, no. 2, p. 596-617, https://doi.org/10.1002/esp.5274.","productDescription":"22 p.","startPage":"596","endPage":"617","ipdsId":"IP-119858","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":436036,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9056ZNG","text":"USGS data release","linkHelpText":"Supporting Datasets for Proglacial Topographic Change Analyses on Mount Rainier, 1960 to 2017"},{"id":392384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.85073852539064,\n              46.78971755817767\n            ],\n            [\n              -121.6351318359375,\n              46.78971755817767\n            ],\n            [\n              -121.6351318359375,\n              46.930572093016316\n            ],\n            [\n              -121.85073852539064,\n              46.930572093016316\n            ],\n            [\n              -121.85073852539064,\n              46.78971755817767\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shean, David 0000-0003-3840-3860","orcid":"https://orcid.org/0000-0003-3840-3860","contributorId":269624,"corporation":false,"usgs":false,"family":"Shean","given":"David","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":827602,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226653,"text":"70226653 - 2022 - Social Values for Ecosystem Services (SolVES): Open-source spatial modeling of cultural services","interactions":[],"lastModifiedDate":"2021-12-02T16:19:39.846812","indexId":"70226653","displayToPublicDate":"2021-12-02T10:16:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Social Values for Ecosystem Services (SolVES): Open-source spatial modeling of cultural services","docAbstract":"Social Values for Ecosystem Services (SolVES) version 4.0 is a fully open-source, GIS-based tool designed to aid in the creation of quantitative, spatially explicit models of the nonmonetary values attributed to cultural ecosystem services, such as aesthetics and recreation, specifically to facilitate their incorporation into larger ecosystem service assessments. Newly redeveloped for QGIS, SolVES can be applied in a wide variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban settings worldwide. Redeveloping SolVES for an open-source platform was intended to expand its user base by eliminating the cost of proprietary GIS software licenses and to remove the impact of proprietary software changes on SolVES development. Providing additional options would enable users to delineate relevant stakeholder groups to better assess how differing preferences impact the intensity and spatial distribution of perceived social values.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105259","usgsCitation":"Sherrouse, B.C., Semmens, D., and Ancona, Z.H., 2022, Social Values for Ecosystem Services (SolVES): Open-source spatial modeling of cultural services: Environmental Modelling & Software, v. 148, p. 1-16, https://doi.org/10.1016/j.envsoft.2021.105259.","productDescription":"105259, 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-127459","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":449484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105259","text":"Publisher Index Page"},{"id":392382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"148","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":827598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":827599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":827600,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230805,"text":"70230805 - 2022 - Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system","interactions":[],"lastModifiedDate":"2022-04-26T14:48:25.006386","indexId":"70230805","displayToPublicDate":"2021-12-02T09:25:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system","docAbstract":"<p><span>Water resource managers are faced with difficult decisions on how to satisfy human water needs while maintaining or restoring riverine ecosystems. Decision sciences have developed approaches and tools that can be used to break down difficult water management decisions into their component parts. An essential aspect of these approaches is the use of quantitative models to evaluate alternative management strategies. Here, we describe four integrated decision support models for evaluating the effect of flows on two life history stages of Chinook salmon (</span><i>Oncorhynchus tshawytscha</i><span>) and Steelhead (</span><i>O. mykiss</i><span>). We then use constrained nonlinear optimization to identify optimal flow regimes for the water year type with the least available water. These flow regimes were then used by managers to develop candidate minimum flow strategies that were evaluated using forward simulation and sensitivity analyses. We found that optimal flow regimes differed markedly from existing regulations and varied among species and life history stages. However, evaluation of tradeoffs among the four competing objectives indicated relatively minimal losses for most objectives when the optimal flows were based on equally weighting the objectives. Sensitivity analysis indicated that water temperature was the primary driver of estimated outcomes and suggested that managers consider alternative means of managing temperatures. Decision sciences have created multiple analytical tools and approaches that simplify complex problems, such as water resource management, and we believe that water resource management would benefit from their increased use.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3903","usgsCitation":"Peterson, J., Pease, J., Whitman, L., White, J., Stratton Garvin, L.E., Rounds, S.A., and Wallick, J., 2022, Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system: River Research and Applications, v. 38, no. 2, p. 293-308, https://doi.org/10.1002/rra.3903.","productDescription":"16 p.","startPage":"293","endPage":"308","ipdsId":"IP-131462","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":449487,"rank":0,"type":{"id":40,"text":"Open Access Publisher 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,{"id":70231829,"text":"70231829 - 2022 - Assessment and significance of the frequency domain for trends in annual peak streamflow","interactions":[],"lastModifiedDate":"2022-05-30T22:54:07.928183","indexId":"70231829","displayToPublicDate":"2021-12-01T15:52:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2289,"text":"Journal of Flood Risk Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessment and significance of the frequency domain for trends in annual peak streamflow","docAbstract":"<p>Risk management of nonstationary floods depends on an understanding of trends over a range of flood frequencies representing small (frequent) to large (infrequent) floods. Quantile regression is applied to the annual peak streamflow distributions at 2683 sites in the contiguous United States to test for trends in the 10th quantile (floods with a 0.9 annual exceedance probability), the 50th quantile (median annual flood), and 90th quantile (floods with a 0.1 annual exceedance probability). Trends are most common (36% of sites) for the median annual flood (50th quantile) and often coherent with trends in both frequent small floods (10th quantile) and infrequent large floods (90th quantile). Changes in the at-site variance of annual peak streamflow, indicated by convergence (decreasing variance) or divergence (increasing variance) of the 10th and 90th quantiles over time, are primarily in response to reservoir operation or urban development rather than climate. An analysis of synthetic series generated from nonstationary distributions demonstrates that quantile regression and standard trend tests used in flood frequency analysis have limited power and high rates of false negatives (&gt;70%) when a test has a significance of<span>&nbsp;</span><i>p</i>&nbsp;=&nbsp;0.05. Quantile regression and tests with lower significance complement standard trend testing to inform flood risk management.</p>","language":"English","publisher":"Wiley","doi":"10.1111/jfr3.12761","usgsCitation":"Konrad, C.P., and Restivo, D.E., 2022, Assessment and significance of the frequency domain for trends in annual peak streamflow: Journal of Flood Risk Management, v. 14, no. 4, e12761, 17 p., https://doi.org/10.1111/jfr3.12761.","productDescription":"e12761, 17 p.","ipdsId":"IP-110944","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":449488,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfr3.12761","text":"Publisher Index Page"},{"id":436037,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95DRY7D","text":"USGS data release","linkHelpText":"Trends in annual peak streamflow quantiles for 2,683 U.S. Geological Survey streamgages in the conterminous United States"},{"id":401365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":292140,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Restivo, Daniel E. 0000-0002-4822-317X","orcid":"https://orcid.org/0000-0002-4822-317X","contributorId":292141,"corporation":false,"usgs":true,"family":"Restivo","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237339,"text":"70237339 - 2022 - Final report: Understanding historical and predicting future lake temperatures in North and South Dakota","interactions":[],"lastModifiedDate":"2022-10-11T18:02:08.115406","indexId":"70237339","displayToPublicDate":"2021-12-01T13:01:08","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Final report: Understanding historical and predicting future lake temperatures in North and South Dakota","docAbstract":"Lakes, reservoirs, and ponds are central and integral features of the landscape of the North Central US. These water bodies provide aesthetic, cultural, and ecosystem services to surrounding wildlife and human communities. Lakes are warming, resulting in the loss of many native fish. In order to manage economically valuable fisheries and other ecosystem services provided by lakes, it is important for managers to have access to accurate estimates of water temperature to better understand past change and to plan for potential future further warming. These data are invaluable for making decisions such as whether to continue stocking plans as usual in certain lakes or how to set specific harvest limits. 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,{"id":70237342,"text":"70237342 - 2022 - Physics-guided machine learning from simulation data: An application in modeling lake and river systems","interactions":[],"lastModifiedDate":"2022-10-11T16:20:24.97395","indexId":"70237342","displayToPublicDate":"2021-12-01T11:12:09","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Physics-guided machine learning from simulation data: An application in modeling lake and river systems","docAbstract":"This paper proposes a new physics-guided machine learning approach that incorporates the scientific knowledge in physics-based models into machine learning models. Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. Although they are built based on general physical laws that govern the relations from input to output variables, these models often produce biased simulations due to inaccurate parameterizations or approximations used to represent the true physics. In this paper, we aim to build a new data-driven framework to monitor dynamical systems by extracting general scientific knowledge embodied in simulation data generated by the physics-based model. To handle the bias in simulation data caused by imperfect parameterization, we propose to extract general physical relations jointly from multiple sets of simulations generated by a physics-based model under different physical parameters. In particular, we develop a spatio-temporal network architecture that uses its gating variables to capture the variation of physical parameters. We initialize this model using a pre-training strategy that helps discover common physical patterns shared by different sets of simulation data. Then we fine-tune it using limited observation data via a contrastive learning process. By leveraging the complementary strength of machine learning and domain knowledge, our method has been shown to produce accurate predictions, use less training samples and generalize to out-of-sample scenarios. 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