{"pageNumber":"21","pageRowStart":"500","pageSize":"25","recordCount":4111,"records":[{"id":70232385,"text":"70232385 - 2022 - Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA","interactions":[],"lastModifiedDate":"2022-07-01T12:09:43.70979","indexId":"70232385","displayToPublicDate":"2022-05-28T18:02:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA","docAbstract":"<p>Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due to their limited availability and high demand in a wide range of applications and especially in high-technology products. The increased demand and geopolitical pressures motivate the search for alternative sources of REYs, and coal, coal waste, and coal ash are considered as new sources for these critical elements. This research evaluates the REY potential of coals from Indiana (USA). However, although coal data revealed REY potential, it suffered from sparse samples with complete REY measurements. Therefore, we explore the applicability of machine learning (ML) models and data augmentation techniques to demonstrate their applicability to evaluate REY potential in Indiana, and other areas in coal basins, using selected coal parameters (Al2O3, Fe2O3, C, Ash, S, P, Mo, Zn, and As contents) as covariates (indicators). Due to the relatively small sample size with complete REY data in the Indiana Coal Database, two data augmentation techniques (Random Over-Sampling Examples and Synthetic Minority Over-Sampling Technique) were used. Four machine learning algorithms (linear discriminate analysis, support vector machine, random forest, and artificial neural networks) were applied for modeling REY potential as a classification problem. The results show that application of Synthetic Minority Over-Sampling Technique prior to development of the support vector machine (SVM) models generated the best REY classification with an accuracy of 95%. The encouraging results based on Indiana coal data may suggest that a similar approach can be used for other coal basins for screening the locations with REY potential. Those locations then can be targeted for more detailed geochemical surveys to identify most promising areas and evaluate overall REY resources.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104054","usgsCitation":"Chatterjee, S., Mastalerz, M., Drobniak, A., and Karacan, C.O., 2022, Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA: International Journal of Coal Geology, v. 259, 104054, 14 p., https://doi.org/10.1016/j.coal.2022.104054.","productDescription":"104054, 14 p.","ipdsId":"IP-138032","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":402804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.56103515625,\n              40.49709237269567\n            ],\n            [\n              -87.5390625,\n              39.35129035526705\n            ],\n            [\n              -87.56103515625,\n              38.839707613545144\n            ],\n            [\n              -87.86865234374999,\n              38.06539235133249\n            ],\n            [\n              -88.11035156249999,\n              37.90953361677018\n            ],\n            [\n              -88.154296875,\n              37.77071473849609\n            ],\n            [\n              -87.451171875,\n              37.92686760148135\n            ],\n            [\n              -87.099609375,\n              37.87485339352928\n            ],\n            [\n              -86.81396484375,\n              38.048091067457236\n            ],\n            [\n              -86.572265625,\n              37.89219554724437\n            ],\n            [\n              -86.396484375,\n              38.11727165830543\n            ],\n            [\n              -86.63818359375,\n              38.95940879245423\n            ],\n            [\n              -86.8359375,\n              40.111688665595956\n            ],\n            [\n              -87.03369140625,\n              40.463666324587685\n            ],\n            [\n              -87.56103515625,\n              40.49709237269567\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"259","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chatterjee, Snahamoy","contributorId":292652,"corporation":false,"usgs":false,"family":"Chatterjee","given":"Snahamoy","email":"","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":845399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastalerz, Maria","contributorId":292654,"corporation":false,"usgs":false,"family":"Mastalerz","given":"Maria","affiliations":[{"id":62959,"text":"IU and Indiana Geological Survey","active":true,"usgs":false}],"preferred":false,"id":845400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drobniak, Agnieszka","contributorId":292655,"corporation":false,"usgs":false,"family":"Drobniak","given":"Agnieszka","email":"","affiliations":[{"id":62959,"text":"IU and Indiana Geological Survey","active":true,"usgs":false}],"preferred":false,"id":845401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":845402,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238935,"text":"70238935 - 2022 - Global environmental changes more frequently offset than intensify detrimental effects of biological invasions","interactions":[],"lastModifiedDate":"2022-12-19T14:10:19.706047","indexId":"70238935","displayToPublicDate":"2022-05-27T07:50:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Global environmental changes more frequently offset than intensify detrimental effects of biological invasions","docAbstract":"<p><span>Human-induced abiotic global environmental changes (GECs) and the spread of nonnative invasive species are rapidly altering ecosystems. Understanding the relative and interactive effects of invasion and GECs is critical for informing ecosystem adaptation and management, but this information has not been synthesized. We conducted a meta-analysis to investigate effects of invasions, GECs, and their combined influences on native ecosystems. We found 458 cases from 95 published studies that reported individual and combined effects of invasions and a GEC stressor, which was most commonly warming, drought, or nitrogen addition. We calculated standardized effect sizes (Hedges’&nbsp;</span><i>d</i><span>) for individual and combined treatments and classified interactions as additive (sum of individual treatment effects), antagonistic (smaller than expected), or synergistic (outside the expected range). The ecological effects of GECs varied, with detrimental effects more likely with drought than the other GECs. Invasions were more strongly detrimental, on average, than GECs. Invasion and GEC interactions were mostly antagonistic, but synergistic interactions occurred in &gt;25% of cases and mostly led to more detrimental outcomes for ecosystems. While interactive effects were most often smaller than expected from individual invasion and GEC effects, synergisms were not rare and occurred across ecological responses from the individual to the ecosystem scale. Overall, interactions between invasions and GECs were typically no worse than the effects of invasions alone, highlighting the importance of managing invasions locally as a crucial step toward reducing harm from multiple global changes.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2117389119","usgsCitation":"Lopez, B., Allen, J., Dukes, J., Lenoir, J., Vila, M., Blumenthal, D., Beaury, E.M., Fusco, E.J., Laginhas, B.B., Morelli, T.L., O’Neill, M.W., Sorte, C.J., Maceda-Veiga, A., Whitlock, R., and Bradley, B., 2022, Global environmental changes more frequently offset than intensify detrimental effects of biological invasions: Proceedings of the National Academy of Sciences, v. 119, no. 22, e2117389119, 7 p., https://doi.org/10.1073/pnas.2117389119.","productDescription":"e2117389119, 7 p.","ipdsId":"IP-138217","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://idus.us.es/handle//11441/162137","text":"Publisher Index Page"},{"id":410699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"22","noUsgsAuthors":false,"publicationDate":"2022-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Lopez, Bianca","contributorId":299985,"corporation":false,"usgs":false,"family":"Lopez","given":"Bianca","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":859239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Jenica","contributorId":299986,"corporation":false,"usgs":false,"family":"Allen","given":"Jenica","affiliations":[{"id":25495,"text":"Mount Holyoke College","active":true,"usgs":false}],"preferred":false,"id":859240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dukes, Jeffrey","contributorId":299987,"corporation":false,"usgs":false,"family":"Dukes","given":"Jeffrey","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":859241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lenoir, Jonathan","contributorId":167876,"corporation":false,"usgs":false,"family":"Lenoir","given":"Jonathan","email":"","affiliations":[{"id":24849,"text":"Université de Picardie Jules Verne","active":true,"usgs":false}],"preferred":false,"id":859242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vila, Montserrat","contributorId":236834,"corporation":false,"usgs":false,"family":"Vila","given":"Montserrat","email":"","affiliations":[],"preferred":false,"id":859243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blumenthal, Dana","contributorId":70686,"corporation":false,"usgs":true,"family":"Blumenthal","given":"Dana","affiliations":[],"preferred":false,"id":859244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beaury, Evelyn M.","contributorId":236820,"corporation":false,"usgs":false,"family":"Beaury","given":"Evelyn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":859245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fusco, Emily J.","contributorId":236821,"corporation":false,"usgs":false,"family":"Fusco","given":"Emily","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":859246,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laginhas, Brittany B.","contributorId":236823,"corporation":false,"usgs":false,"family":"Laginhas","given":"Brittany","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":859247,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":859248,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"O’Neill, Mitchell W.","contributorId":299994,"corporation":false,"usgs":false,"family":"O’Neill","given":"Mitchell","email":"","middleInitial":"W.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":859249,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sorte, Cascade J.B.","contributorId":236835,"corporation":false,"usgs":false,"family":"Sorte","given":"Cascade","middleInitial":"J.B.","affiliations":[],"preferred":false,"id":859250,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Maceda-Veiga, Alberto","contributorId":299996,"corporation":false,"usgs":false,"family":"Maceda-Veiga","given":"Alberto","email":"","affiliations":[{"id":56742,"text":"Universitat de Barcelona","active":true,"usgs":false}],"preferred":false,"id":859251,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Whitlock, Raj","contributorId":299997,"corporation":false,"usgs":false,"family":"Whitlock","given":"Raj","email":"","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":859252,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bradley, Bethany A. 0000-0003-4912-4971","orcid":"https://orcid.org/0000-0003-4912-4971","contributorId":299998,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany A.","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":859253,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70232104,"text":"70232104 - 2022 - #TheSmoreYouKnow and #emergencycute: A conceptual model on the use of humor by science agencies during crisis to create connection, empathy, and compassion","interactions":[],"lastModifiedDate":"2022-06-06T11:51:38.884858","indexId":"70232104","displayToPublicDate":"2022-05-27T06:48:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"#TheSmoreYouKnow and #emergencycute: A conceptual model on the use of humor by science agencies during crisis to create connection, empathy, and compassion","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Studies from a variety of disciplines reveal that humor can be a useful method to reduce stress and increase compassion, connection, and empathy between agencies and people they serve during times of crisis. Despite this growing evidence base, humor's use during a geohazard (earthquake,<span>&nbsp;</span>volcanoes<span>,&nbsp;landslides, and tsunami) to aid scientific agencies' crisis communication response has been rarely studied. A broad literature review of humor in crisis and an exploratory examination of several case studies reveal that scientific organizations, specifically those that respond to geohazards, can harness the power of humor to help create connection and empathy with the publics they seek to serve. We find evidence that supports our argument that the use of humor acknowledges a shared human experience, reducing the barriers between public officials, scientists, and the people most impacted by crisis. Public statements made by scientists and public officials during the&nbsp;U.S.&nbsp;Geological Survey (USGS) response to the Kīlauea eruption in 2018 in Hawai'i, United States, and GNS Science/GeoNet (GeoNet) response to the M7.8 Kaikōura/North Hurunui earthquake in 2016 in Aotearoa New Zealand, are used to inform the development of this conceptual model. We then posit a conceptual model which unifies concepts from the literature with our case studies to provide potential guidelines for those crisis communicators working for science agencies on how best to use humor to help people cope during times of crisis. This model can be further tested for future research to determine its effectiveness and utility for scientific agencies responding to geological crises.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2022.102995","usgsCitation":"McBride, S., and Ball, J.L., 2022, #TheSmoreYouKnow and #emergencycute: A conceptual model on the use of humor by science agencies during crisis to create connection, empathy, and compassion: International Journal of Disaster Risk Reduction, v. 27, 102995, 14 p., https://doi.org/10.1016/j.ijdrr.2022.102995.","productDescription":"102995, 14 p.","ipdsId":"IP-106352","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":447660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2022.102995","text":"Publisher Index Page"},{"id":401742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":844209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Jessica L. 0000-0002-7837-8180 jlball@usgs.gov","orcid":"https://orcid.org/0000-0002-7837-8180","contributorId":205012,"corporation":false,"usgs":true,"family":"Ball","given":"Jessica","email":"jlball@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":844210,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70252816,"text":"70252816 - 2022 - Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2024-04-08T23:47:34.73073","indexId":"70252816","displayToPublicDate":"2022-05-22T08:46:21","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":"Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River","docAbstract":"<p>High densities of cyanobacteria in aquatic ecosystems can cause impacts to ecosystem services because they serve as a poor-quality food resource, produce toxins and can indirectly cause a variety of other negative impacts to water quality. There are many hypotheses about the potential environmental drivers of variation in cyanobacterial abundance and toxicity, but these hypotheses have rarely been considered in combination and rarely been examined in large river ecosystems. Here we use monthly data from backwater habitats of the Upper Mississippi River (UMR) to evaluate associations between environmental conditions and cyanobacterial abundance and toxicity (microcystin and anatoxin-a) that would be expected based on several hypotheses. Backwaters in the Mississippi River vary in flushing rate, temperature, turbidity, nutrient availability, water depth and vegetative cover. We find support for hypotheses that suggest physical conditions in backwaters (flushing rate, temperature, turbidity, rooted vegetation cover and water depth) and nutrient availability influence cyanobacterial abundance and toxicity. We then used structural equation modeling to incorporate several hypotheses into a causal modeling framework, which indicated that backwater connectivity (flushing) strongly influences cyanobacterial abundance via the regulation of water temperature, and that nutrient availability strongly influences the presence of microcystin concentrations above our detection limit. Our data suggest that management of backwater connectivity could influence cyanobacterial abundance and toxicity in UMR backwaters. Reconnecting backwaters (via alteration of levees) could serve as a local adaptation to minimize the effects of climate change and excessive nutrient loading.&nbsp;</p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3987","usgsCitation":"Giblin, S.M., Larson, J.H., and King, J.D., 2022, Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River: River Research and Applications, v. 38, no. 6, p. 1115-1128, https://doi.org/10.1002/rra.3987.","productDescription":"14 p.","startPage":"1115","endPage":"1128","ipdsId":"IP-134311","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":427556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Stares","state":"Wisconsin","otherGeospatial":"Blue Lake, Great River Backwater, Indian Slough, Lizzy Paul's Pond, Mertes Lake, Second Lake, Stoddard Backwater, Trempealeau Wildlife Refuge, Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.7533542542472,\n              44.157127527506105\n            ],\n            [\n              -91.7533542542472,\n              43.58283679178368\n            ],\n            [\n              -90.94310098095912,\n              43.58283679178368\n            ],\n            [\n              -90.94310098095912,\n              44.157127527506105\n            ],\n            [\n              -91.7533542542472,\n              44.157127527506105\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"38","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Giblin, Shawn M.","contributorId":335419,"corporation":false,"usgs":false,"family":"Giblin","given":"Shawn","email":"","middleInitial":"M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Jeremy D.","contributorId":335420,"corporation":false,"usgs":false,"family":"King","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70249311,"text":"70249311 - 2022 - Orbital and in-situ investigation of periodic bedrock ridges in Glen Torridon, Gale Crater, Mars","interactions":[],"lastModifiedDate":"2023-10-05T00:08:41.026654","indexId":"70249311","displayToPublicDate":"2022-05-19T11:10:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Orbital and in-situ investigation of periodic bedrock ridges in Glen Torridon, Gale Crater, Mars","docAbstract":"<p>Wind has been the dominant agent of landscape modification on Mars for the past ~3 billion years. Among the diversity of features formed by aeolian abrasion on the surface of Mars are periodic bedrock ridges (PBRs), a relatively recently recognized class of erosional bedforms on Mars for which Earth analogues are rare. Gale crater, the field site for NASA’s Mars Science Laboratory <i>Curiosity</i> rover since it landed there in 2012, contains a diverse and extensive record of aeolian deposition and erosion. This study focuses on a series of periodic, linear bedrock ridges that occur within the Fe/Mg-smectite clay-bearing Glen Torridon region of Aeolis Mons (informally Mount Sharp). During <i>Curiosity’s</i> exploration of the Glen Torridon region between sols ~2300-3080, the rover drove through this field of ridges, providing the first opportunity for the in situ observation of these enigmatic erosional features. This study characterizes the Glen Torridon ridges using orbiter and rover data to determine their morphology, spatial distribution, compositional and material properties, and association with other aeolian features in the area. Based on these observations, the Glen Torridon ridges are interpreted to be consistent with an origin as wind-eroded periodic bedrock ridges carved during the most recent exhumation of Mount Sharp into the present-day mound. Although there is evidence for multidirectional winds in the Glen Torridon region based on the orientation of modern ripples, megaripples, TARs and other bedrock indicators, the consistent orientation of the Glen Torridon ridges, coupled with morphologic asymmetries within the ridges, support formation and elongation of the Glen Torridon PBRs forms parallel to a net regional northerly wind direction in and around Gale crater.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JE007096","usgsCitation":"Stack, K.M., Dietrich, W.E., Lamb, M.P., Sullivan, R., Christian, J.R., Newman, C.E., O’Connell-Cooper, C., Sneed, J.W., Day, M.D., Baker, M., Arvidson, R.A., Fedo, C.M., Khan, S., Williams, R., Bennett, K.A., Bryk, A.B., Cofield, S., Edgar, L.A., Fox, V.F., Fraeman, A.A., House, C.H., Rubin, D.M., Sun, V.Z., and Van Beek, J., 2022, Orbital and in-situ investigation of periodic bedrock ridges in Glen Torridon, Gale Crater, Mars: Journal of Geophysical Research E: Planets, v. 127, no. 6, e2021JE007096, 33 p., https://doi.org/10.1029/2021JE007096.","productDescription":"e2021JE007096, 33 p.","ipdsId":"IP-133144","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":447723,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021je007096","text":"External Repository"},{"id":421607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gale Crater, Glen Torridon, Mars","volume":"127","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Stack, K. M.","contributorId":177654,"corporation":false,"usgs":false,"family":"Stack","given":"K.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":885054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietrich, W. E.","contributorId":47538,"corporation":false,"usgs":false,"family":"Dietrich","given":"W.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":885055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, M. 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,{"id":70238488,"text":"70238488 - 2022 - Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl","interactions":[],"lastModifiedDate":"2022-11-28T12:30:11.615399","indexId":"70238488","displayToPublicDate":"2022-05-16T06:27:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting).</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-022-00324-7","usgsCitation":"Overton, C.T., Casazza, M.L., Bretz, J., McDuie, F., Matchett, E., Mackell, D.A., Lorenz, A., Mott, A., Herzog, M.P., and Ackerman, J.T., 2022, Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl: Movement Ecology, v. 10, 23, 13 p., https://doi.org/10.1186/s40462-022-00324-7.","productDescription":"23, 13 p.","ipdsId":"IP-133430","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447785,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-022-00324-7","text":"Publisher Index 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Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857615,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857616,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70231653,"text":"70231653 - 2022 - Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity","interactions":[],"lastModifiedDate":"2022-08-15T13:51:56.290092","indexId":"70231653","displayToPublicDate":"2022-05-12T07:23:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity","docAbstract":"<p>1. Autonomous Recording Units (ARUs) are now widely used to survey communities of species. These surveys generate spatially and temporally replicated counts of unmarked animals, but such data typically include false negatives and misclassified detections, both of which may vary across sites in proportion to abundance. These data challenges can bias estimates of occupancy, and the typical approach of verifying individual detections is expensive.</p><p>2. We developed a Bayesian implementation of a two-species, false-positive N-mixture model for estimating occupancy from ARU data or other counts of unmarked animals that does not require manual verification. The model accounts for species misclassification and abundance-induced detection heterogeneity, as well as false negatives. To evaluate this model, we simulated 200 data sets for each of 29 scenarios, including scenarios in which misclassifications outnumbered correct classifications for rare species. We also applied the model to acoustic surveys of bats conducted on Fort Carson Army Post and Piñon Canyon Maneuver Site, Colorado, USA.</p><p>3. In the simulation study, bias, coverage, and root mean square error for occupancy estimates obtained from the two-species false-positive N-mixture model were superior to metrics obtained from two competing two-species false-positive occupancy models. Across 29 scenarios, absolute bias was consistently low (range: -0.03–0.07), while coverage averaged 93% (range: 74%–98%). For alternative occupancy models, absolute bias was often high (range: -0.36–0.39), and coverage averaged from 47%–65%. Although our model included an abundance parameter, abundance estimates were not reliable. For two species of<span>&nbsp;</span><i>Myotis</i><span>&nbsp;</span>bats, we estimated that 1%–5% of field-recorded detections were misclassified. Estimated occupancy (0.91 and 0.76) was lower than naïve estimates (1.00 and 0.94). Competing occupancy models implausibly estimated local occupancy of 0.00 at sites with numerous detections.</p><p>4. Our two-species, false-positive N-mixture model is significant because it accounts for detection heterogeneity and improves occupancy estimates without expensive manual verification of detections. Our field application indicated that misclassifications were not common, yet affected occupancy inferences. Given that ARUs are increasingly used to survey a broad range of taxa, such an occupancy model could be widely useful.</p>","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13895","usgsCitation":"Clement, M., Royle, A., and Mixan, R., 2022, Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity: Methods in Ecology and Evolution, v. 13, no. 8, p. 1719-1729, https://doi.org/10.1111/2041-210X.13895.","productDescription":"11 p.","startPage":"1719","endPage":"1729","ipdsId":"IP-139383","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447816,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13895","text":"Publisher Index Page"},{"id":400804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Clement, Matt","contributorId":291855,"corporation":false,"usgs":false,"family":"Clement","given":"Matt","email":"","affiliations":[{"id":62776,"text":"AZ fish and game","active":true,"usgs":false}],"preferred":false,"id":843247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":843250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mixan, Ronald","contributorId":291857,"corporation":false,"usgs":false,"family":"Mixan","given":"Ronald","email":"","affiliations":[{"id":62778,"text":"AZ Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":843251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241477,"text":"70241477 - 2022 - What common-garden experiments tell us about climate responses in plants","interactions":[],"lastModifiedDate":"2023-03-21T12:20:18.416592","indexId":"70241477","displayToPublicDate":"2022-05-09T07:19:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"What common-garden experiments tell us about climate responses in plants","docAbstract":"<ol class=\"\"><li>Common garden experiments are indoor or outdoor plantings of species or populations collected from multiple distinct geographic locations, grown together under shared conditions. These experiments examine a range of questions for theory and application using a variety of methods for analysis. The eight papers of this special feature comprise a cross section of contemporary approaches, summarized and synthesized here by what they tell us about the relationships between climate-related trait spectra and fitness optima.</li><li>Four of the eight papers are based on field experiments in prairie, desert, Mediterranean and boreal biomes. Representative of many common garden experiments, these experiments reveal consistent evidence of traits varying with population climate provenance, but evidence of a tradeoff between growth and tolerance traits or of consistent fitness optimization at home is scant, in contrast to trait theory. Two synthesis papers highlight dominant patterns of trait divergence, including for an exotic invasive species. One theoretical paper warned that unknown kinship relationships between populations can result in the misidentification of adaptive trait divergence. A third synthesis paper formulated novel and ambitious goals for common-garden studies through including measurement of response variables at multiple levels of biological organization.</li><li>The featured papers discuss multiple avenues for improving common garden studies. Genomic analysis, together with the quantification of kinship relationships, will continue to reveal the influence of environmental drivers on gene selection. Measuring a more complete set of fitness traits, especially for traits related to regeneration, will permit the development of projection models to explicitly link trait spectra, climate patterns and fitness consequences. More standardized data reporting will additionally improve abilities to synthesize findings across experiments. Testing population performance in competition with other species will produce more robust fitness comparisons between genotypes, especially for slower-growing genotypes in higher-resource environments. Adding gardens in and beyond climatic edge locations will furthermore strengthen the understanding of population failure and species exclusion. Finally, there is unrealized potential in adding ecosystem-level observations to common-garden studies that will enhance integrative analysis across scales of biological organization and scientific domains.</li><li><i>Synthesis</i>. With novel, creative designs, data integration and synthesis, common garden experiments will continue to advance the understanding of trait ensembles interacting with climate across scales of biological organization, provide pivotal data for global change models and guide ecological applications such as restoration of habitats for rare and climate sensitive species.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13887","usgsCitation":"Schwinning, S., Lorti, C.J., Esque, T., and DeFalco, L., 2022, What common-garden experiments tell us about climate responses in plants: Journal of Ecology, v. 110, no. 5, p. 986-996, https://doi.org/10.1111/1365-2745.13887.","productDescription":"11 p.","startPage":"986","endPage":"996","ipdsId":"IP-138947","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13887","text":"Publisher Index Page"},{"id":414429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwinning, Susanne","contributorId":303275,"corporation":false,"usgs":false,"family":"Schwinning","given":"Susanne","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":866974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorti, Christopher J.","contributorId":303276,"corporation":false,"usgs":false,"family":"Lorti","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":866975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":866976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":866977,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70237696,"text":"70237696 - 2022 - The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","interactions":[],"lastModifiedDate":"2022-10-19T12:09:20.689887","indexId":"70237696","displayToPublicDate":"2022-05-07T07:03:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3275,"text":"Review of Palaeobotany and Palynology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0185\"><span>Pollen morphology on its own and in conjunction with other characteristics has elucidated the origin and evolution of various plant groups. Previous studies of fossil pollen rarely discuss the effects of&nbsp;diagenesis&nbsp;and sample preparation on pollen characteristics, i.e., variability in staining, pollen morphology, and pollen wall ultrastructural characteristics. This paper examines the effect of acetolysis on reflectance and spectral epi-fluorescence measurements. Based on empirical studies, different species under similar experimental conditions display different reflectance values, indicating individual species respond differently to similar post-depositional thermal events. The quantitative pollen fluorescence spectra showed significant variability, but there is an overall increase in the mean wavelength of maximum emission with acetolysis. Increases in these spectral parameters are used to infer thermal maturation and diagenetic pathways in fossil pollen. The paper also discusses observations made on fossil pollen of a known&nbsp;thermal maturity&nbsp;using Pearson's Pollen/Spore Color Standard. Assessment of pollen thermal maturity using this color standard can be an indicator of the quality of morphological and ultrastructural information that can be extracted from fossil pollen. Increasing thermal maturity of pollen may have an effect on staining variability. Based on observations, staining for brightfield or&nbsp;electron microscopy&nbsp;in fossil pollen, although useful for improving contrast in the specimen, must be used with caution when interpreting pollen wall structure. Although single fossil pollen investigations are useful, replication of these studies on similar or the same specimens from the same locality or various localities will collectively provide more information for elucidation of the morphology and&nbsp;</span>ultrastructure<span>&nbsp;</span>of the once living pollen, and is helpful in sorting out characteristics that may be artifacts from post-depositional diagenesis.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.revpalbo.2022.104679","usgsCitation":"Zavada, M., and Hackley, P.C., 2022, The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen: Review of Palaeobotany and Palynology, v. 302, 104679, 13 p., https://doi.org/10.1016/j.revpalbo.2022.104679.","productDescription":"104679, 13 p.","ipdsId":"IP-134937","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":408531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"302","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zavada, Michael","contributorId":298073,"corporation":false,"usgs":false,"family":"Zavada","given":"Michael","affiliations":[{"id":64489,"text":"Univ. TX Permian Basin","active":true,"usgs":false}],"preferred":false,"id":855044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855045,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70255103,"text":"70255103 - 2022 - The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts","interactions":[],"lastModifiedDate":"2024-06-17T15:10:24.743676","indexId":"70255103","displayToPublicDate":"2022-05-06T09:57:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts","docAbstract":"<p><span>Methods are being developed to capitalize on citizen science data for research and monitoring, but these data are rarely used within established decision-making frameworks of wildlife agencies. Citizen science data are often collected at higher resolution and extent than targeted monitoring programs, and may provide complementary information. Here, we demonstrate that carefully filtered semi-structured citizen science observations, when paired with targeted survey data, can produce ecological predictions at higher resolution and extent than targeted surveys alone, and both datasets can represent complementary aspects of species' ecology. We present case studies demonstrating how citizen science data can enhance or supplement decision-making of government and conservation organizations. First, we show how the continuous spatial coverage of citizen science projects, when coupled with targeted surveys, can improve estimates of metrics used by the U.S. Fish and Wildlife Service in regulatory processes to estimate population size, and inform take limits of federally managed species nationwide. Second, we show that the spatial coverage of citizen science accommodates dynamic avian space use patterns during key times of the year, relative to standardized monitoring protocols carried out by the Illinois Natural History Survey. Lastly, we demonstrate that citizen science information can replicate estimates of migratory chronologies for the Illinois Natural History Survey and the U.S. Fish and Wildlife Service for some waterfowl species, and in some contexts can supplement missing data on abundance. These findings illustrate the value of integrating validated information from semi-structured citizen science into the current evidence base used to justify, inform, and evaluate conservation decision-making.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109556","usgsCitation":"Stuber, E.F., Robinson, O., Bjerre, E.R., Otto, M.C., Millsap, B., Zimmerman, G., Brasher, M., Ringelman, K., Fournier, A., Yetter, A., Isola, J., and Ruiz-Gutierrez, V., 2022, The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts: Biological Conservation, v. 270, 109556, 11 p., https://doi.org/10.1016/j.biocon.2022.109556.","productDescription":"109556, 11 p.","ipdsId":"IP-134088","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":488728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109556","text":"Publisher Index Page"},{"id":430277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Illinois, Iowa, Missouri","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.49828581034168,\n              39.76455400687408\n            ],\n            [\n              -122.49828581034168,\n              38.81660641718298\n            ],\n            [\n              -121.0222303704384,\n              38.81660641718298\n            ],\n            [\n              -121.0222303704384,\n              39.76455400687408\n            ],\n            [\n              -122.49828581034168,\n              39.76455400687408\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.90160005903965,\n              41.45769825249826\n            ],\n            [\n              -92.50893391243744,\n              41.45769825249826\n            ],\n            [\n              -92.50893391243744,\n              38.85655448556952\n            ],\n            [\n              -88.90160005903965,\n              38.85655448556952\n            ],\n            [\n              -88.90160005903965,\n              41.45769825249826\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":903404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Orin","contributorId":338622,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":903405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjerre, Emily R.","contributorId":338623,"corporation":false,"usgs":false,"family":"Bjerre","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Otto, Mark C.","contributorId":338624,"corporation":false,"usgs":false,"family":"Otto","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millsap, Brian A.","contributorId":338625,"corporation":false,"usgs":false,"family":"Millsap","given":"Brian A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Guthrie S.","contributorId":338626,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brasher, Michael G.","contributorId":338627,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael G.","affiliations":[{"id":81180,"text":"Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":903410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ringelman, Kevin M.","contributorId":338628,"corporation":false,"usgs":false,"family":"Ringelman","given":"Kevin M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":903411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fournier, Auriel","contributorId":338631,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":81181,"text":"University of Illinois at Urbana-Champaign, Havana","active":true,"usgs":false}],"preferred":false,"id":903412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yetter, Aaron","contributorId":338634,"corporation":false,"usgs":false,"family":"Yetter","given":"Aaron","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":903413,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Isola, Jennifer","contributorId":242027,"corporation":false,"usgs":false,"family":"Isola","given":"Jennifer","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":904306,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ruiz-Gutierrez, Viviana","contributorId":261212,"corporation":false,"usgs":false,"family":"Ruiz-Gutierrez","given":"Viviana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":904307,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70250315,"text":"70250315 - 2022 - Ignoring species availability biases occupancy estimates in single-scale occupancy models","interactions":[],"lastModifiedDate":"2023-12-07T14:08:48.423205","indexId":"70250315","displayToPublicDate":"2022-05-04T09:34:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ignoring species availability biases occupancy estimates in single-scale occupancy models","docAbstract":"<ol class=\"\"><li>Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one.</li><li>Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability?</li><li>Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (&lt;0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (&gt;0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model.</li><li>Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app<span>&nbsp;</span><a class=\"linkBehavior\" href=\"https://gdirenzo.shinyapps.io/multi-scale-occ/\" data-mce-href=\"https://gdirenzo.shinyapps.io/multi-scale-occ/\">https://gdirenzo.shinyapps.io/multi-scale-occ/</a>. Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13881","usgsCitation":"DiRenzo, G.V., David A. W. Miller, and Campbell Grant, E.H., 2022, Ignoring species availability biases occupancy estimates in single-scale occupancy models: Methods in Ecology and Evolution, v. 13, no. 8, p. 1790-1804, https://doi.org/10.1111/2041-210X.13881.","productDescription":"15 p.","startPage":"1790","endPage":"1804","ipdsId":"IP-130185","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":502598,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":423175,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"David A. W. Miller","contributorId":332097,"corporation":false,"usgs":false,"family":"David A. W. Miller","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":889422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889423,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231571,"text":"70231571 - 2022 - Circa 1.50–1.45 Ga metasedimentary rocks in southwestern Laurentia provide distinctive records of Mesoproterozoic regional orogenesis and craton interactions","interactions":[],"lastModifiedDate":"2022-05-16T11:46:36.233945","indexId":"70231571","displayToPublicDate":"2022-05-01T06:45:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1726,"text":"GSA Memoirs","active":true,"publicationSubtype":{"id":10}},"title":"Circa 1.50–1.45 Ga metasedimentary rocks in southwestern Laurentia provide distinctive records of Mesoproterozoic regional orogenesis and craton interactions","docAbstract":"<div class=\"widget widget-BookChapterMainView widget-instance-BookChapterMainView\"><div class=\"content-inner-wrap\"><div class=\"book-chapter-body\"><div id=\"ContentTab\" class=\"content active\"><div class=\"widget widget-BookSectionsText widget-instance-BookChaptertext\"><div class=\"module-widget\"><div class=\"widget-items\" data-widgetname=\"BookSectionsText\"><div class=\"category-section content-section js-content-section\" data-statsid=\"133280247\"><p>The discovery of multiple deformed and metamorphosed sedimentary successions in southwestern Laurentia that have depositional ages between ca. 1.50 and 1.45 Ga marked a turning point in our understanding of the Mesoproterozoic tectonic evolution of the continent and its interactions with formerly adjacent cratons. Detrital zircon U-Pb ages from metasedimentary strata and igneous U-Pb zircon ages from interbedded metavolcanic rocks in Arizona and New Mexico provide unequivocal evidence for ca. 1.50–1.45 Ga deposition and burial, followed by ca. 1.45 and younger deformation, metamorphism, and plutonism. These events reflect regional shortening and crustal thickening that are most consistent with convergent to collisional orogenesis—the Mesoproterozoic Picuris orogeny—in southwestern Laurentia. Similar metasedimentary successions documented in the midcontinent of the United States and in eastern Canada help to establish ca. 1.45 Ga orogenesis as a continent-scale phenomenon associated with a complex and evolving convergent margin along southern Laurentia. Metasedimentary successions of similar age are also exposed across ~5000 km of the western Laurentian margin and contain distinctive 1.6–1.5 Ga detrital zircon populations that are globally rare except in select cratonic provinces in Australia and Antarctica. The recognition of these distinctive detrital zircon ages provides a transient record of plate interactions prior to breakup of Nuna or Columbia ca. 1.45 Ga and provides key constraints on global plate reconstructions.</p></div></div></div></div></div></div></div></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.1220(09)","usgsCitation":"Jones, J.V., and Daniel, C.G., 2022, Circa 1.50–1.45 Ga metasedimentary rocks in southwestern Laurentia provide distinctive records of Mesoproterozoic regional orogenesis and craton interactions: GSA Memoirs, v. 220, 14 p., https://doi.org/10.1130/2022.1220(09).","productDescription":"14 p.","ipdsId":"IP-130033","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":400651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"220","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":843045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Christopher G.","contributorId":195246,"corporation":false,"usgs":false,"family":"Daniel","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":843046,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70231525,"text":"70231525 - 2022 - Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability","interactions":[],"lastModifiedDate":"2022-08-02T14:21:41.486398","indexId":"70231525","displayToPublicDate":"2022-04-21T08:43:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability","docAbstract":"<ol class=\"\"><li>Drylands have low nitrogen stocks and are predicted to be sensitive to modest increases in reactive nitrogen availability, but direct evidence that atmospheric nitrogen deposition will have sustained effects on dryland ecosystems is sparse and conflicting.</li><li>We used three long-running<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>nitrogen deposition simulation experiments and a complementary laboratory incubation experiment to address fundamental questions about how nitrogen inputs affect drylands: 1) What are the long- and short-term consequences of nitrogen inputs for biogeochemical and ecosystem properties?; 2) Do these consequences depend on soil moisture availability?; and 3) Does soil texture modify the effects of nitrogen inputs and/or soil moisture availability?</li><li>In 2011, we established three study sites along a soil texture gradient in Arches National Park with plots receiving 0, 2, 5, or 8 kg N ha<sup>-1</sup><span>&nbsp;</span>annually (<i>n</i><span>&nbsp;</span>= 5 per treatment per site). We assessed a suite of biogeochemical metrics over the long- and short-term. To assess longer-term effects, we sampled annually (2013-2019), just prior to spring nitrogen fertilization. To assess short-term effects, we sampled immediately before and after spring nitrogen fertilization in 2013. Additionally, we compared foliar chemistry, soil extracellular enzyme activities, heterotrophic respiration rates, and nitrogen trace gas fluxes at select intervals during the study period (2011-2019). Finally, we conducted a laboratory incubation to measure the individual and interacting effects of soil moisture and nitrogen additions on soil microbial activity.</li><li>We identified some short-term effects<span>&nbsp;</span><i>in situ</i>, but no lasting consequences of added nitrogen for any of the metrics measured. In the incubation, soil moisture treatments independently increased heterotrophic respiration rates but did not modify the effects of added nitrogen. In contrast to nitrogen treatments, soil texture was associated with large differences in biogeochemical cycling.</li><li>Our results oppose the common prediction that coupled dryland biogeochemical cycles are sensitive to nitrogen inputs and suggest that fine scale edaphic heterogeneity is a key driver of dryland ecosystem properties.</li><li><i>Synthesis</i>. This study synthesizes a rare, long-term dataset, which provides robust evidence that carbon and nutrient cycling and availability are resistant to realistic levels of atmospheric nitrogen deposition in remote dryland ecosystems.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13896","usgsCitation":"Osborne, B.B., Roybal, C., Reibold, R.H., Collier, C.D., Geiger, E.L., Phillips, M.L., Weintraub, M.N., and Reed, S., 2022, Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability: Journal of Ecology, v. 110, no. 7, p. 1615-1631, https://doi.org/10.1111/1365-2745.13896.","productDescription":"17 p.","startPage":"1615","endPage":"1631","ipdsId":"IP-133283","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":435867,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MUQ7ZE","text":"USGS data release","linkHelpText":"Ecological property data and experimental lab incubation results from a long-term nitrogen deposition simulation experiment in three semi-arid grasslands, Arches National Park, Utah, USA, 2013-2019"},{"id":400578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Arches National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.71771240234375,\n              38.73480362521081\n            ],\n            [\n              -109.55291748046875,\n              38.73480362521081\n            ],\n            [\n              -109.55291748046875,\n              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M","affiliations":[{"id":36303,"text":"unknown","active":true,"usgs":false}],"preferred":false,"id":842926,"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":842927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collier, Christopher D","contributorId":290496,"corporation":false,"usgs":false,"family":"Collier","given":"Christopher","email":"","middleInitial":"D","affiliations":[{"id":62439,"text":"Trout Unlimited, 1777 N Kent St., Suite 100, Arlington, VA 22209","active":true,"usgs":false}],"preferred":false,"id":842928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geiger, Erika L. 0000-0003-4546-3503","orcid":"https://orcid.org/0000-0003-4546-3503","contributorId":207502,"corporation":false,"usgs":true,"family":"Geiger","given":"Erika","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":842929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":842930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weintraub, Michael N 0000-0002-9623-2855","orcid":"https://orcid.org/0000-0002-9623-2855","contributorId":290497,"corporation":false,"usgs":false,"family":"Weintraub","given":"Michael","email":"","middleInitial":"N","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":842931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":842932,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70231662,"text":"70231662 - 2022 - Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals","interactions":[],"lastModifiedDate":"2022-08-15T13:53:03.596218","indexId":"70231662","displayToPublicDate":"2022-04-21T08:24:44","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals","docAbstract":"<p>The transition from a global hydrocarbon economy to a green energy economy and the rapidly growing middle class in developing countries are driving the need for considerable new sources of critical materials. Deep-ocean minerals, namely cobalt-rich ferromanganese crusts and polymetallic nodules, are two such new resources generating interest.</p><p>Polymetallic nodules are essentially two-dimensional mineral deposits sitting on abyssal plain sediments at about 3,500–6,000 m water depths. Metals of economic interest enriched in nodules include nickel, copper, manganese, cobalt and molybdenum. Cobalt-rich ferromanganese crusts are also two-dimensional deposits forming pavements on rock outcrops on seamounts and ridges at water depths of 400–7,000 m. Metals of economic interest for crusts include cobalt, manganese, nickel, molybdenum, tellurium, platinum, vanadium and rare earth elements.</p><p>A conservative estimate is that 21.1 billion dry tons of polymetallic nodules exist in the Clarion-Clipperton Zone (<span>CCZ</span>) manganese nodule field, the largest in area and tonnage of the known global nodule fields. Based on that estimate, tonnages of many critical metals in the<span>&nbsp;</span><span>CCZ</span><span>&nbsp;</span>nodules are greater than those found in global terrestrial reserves. About 7.5 billion dry tons of cobalt-rich ferromanganese crusts are estimated to occur in the Pacific Ocean Prime Crust Zone, the area with the highest tonnage of critical-metal-rich crust deposits, with many elements contained therein estimated to be greater than those found in global terrestrial reserves.</p><p>Deep-ocean mining has not yet been carried out in the Exclusive Economic Zone of any nation, nor in the Areas beyond national jurisdiction, although extensive mineral exploration and environmental studies are being conducted and exploitation regulations codified, indicating that mining activities will likely begin in the near future. If deep-ocean mining follows the evolution of offshore production of petroleum, we can expect that about 35–45 per cent of the demand for critical metals will come from deep-ocean mines by 2065.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The United Nations convention on the law of the sea, part XI regime and the international seabed authority: A twenty-five year journey","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Brill","doi":"10.1163/9789004507388_013","usgsCitation":"Hein, J.R., and Mizell, K., 2022, Deep-ocean polymetallic nodules and cobalt-rich ferromanganese crusts in the global ocean: New sources for critical metals, chap. 8 <i>of</i> The United Nations convention on the law of the sea, part XI regime and the international seabed authority: A twenty-five year journey, p. 177-197, https://doi.org/10.1163/9789004507388_013.","productDescription":"21 p.","startPage":"177","endPage":"197","ipdsId":"IP-120065","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400795,"type":{"id":15,"text":"Index Page"},"url":"https://brill.com/view/book/edcoll/9789004507388/BP000021.xml"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843290,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70239874,"text":"70239874 - 2022 - Life and death in a dynamic environment: Invasive trout, floods, and intraspecific drivers of translocated populations","interactions":[],"lastModifiedDate":"2023-01-24T12:48:53.687121","indexId":"70239874","displayToPublicDate":"2022-04-11T06:46:52","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":"Life and death in a dynamic environment: Invasive trout, floods, and intraspecific drivers of translocated populations","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Understanding the relative strengths of intrinsic and extrinsic factors regulating populations is a long-standing focus of ecology and critical to advancing conservation programs for imperiled species. Conservation could benefit from an increased understanding of factors influencing vital rates (somatic growth, recruitment, survival) in small, translocated populations, which is lacking owing to difficulties in long-term monitoring of rare species. Translocations, here defined as the transfer of wild-captured individuals from source populations to new habitats, are widely used for species conservation, but outcomes are often minimally monitored, and translocations that are monitored often fail. To improve our understanding of how translocated populations respond to environmental variation, we developed and tested hypotheses related to intrinsic (density dependent) and extrinsic (introduced rainbow trout<span>&nbsp;</span><i>Oncorhynchus mykiss</i>, stream flow and temperature regime) causes of vital rate variation in endangered humpback chub (<i>Gila cypha</i>) populations translocated to Colorado River tributaries in the Grand Canyon (GC), USA. Using biannual recapture data from translocated populations over 10 years, we tested hypotheses related to seasonal somatic growth, and recruitment and population growth rates with linear mixed-effects models and temporal symmetry mark–recapture models. We combined data from recaptures and resights of dispersed fish (both physical captures and continuously recorded antenna detections) from throughout GC to test survival hypotheses, while accounting for site fidelity, using joint live-recapture/live-resight models. While recruitment only occurred in one site, which also drove population growth (relative to survival), evidence supported hypotheses related to density dependence in growth, survival, and recruitment, and somatic growth and recruitment were further limited by introduced trout. Mixed-effects models explained between 67% and 86% of the variation in somatic growth, which showed increased growth rates with greater flood-pulse frequency during monsoon season. Monthly survival was 0.56–0.99 and 0.80–0.99 in the two populations, with lower survival during periods of higher intraspecific abundance and low flood frequency. Our results suggest translocations can contribute toward the recovery of large-river fishes, but continued suppression of invasive fishes to enhance recruitment may be required to ensure population resilience. Furthermore, we demonstrate the importance of flooding to population demographics in food-depauperate, dynamic, invaded systems.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2635","usgsCitation":"Healy, B.D., Budy, P., Conner, M., and Omana Smith, E.C., 2022, Life and death in a dynamic environment: Invasive trout, floods, and intraspecific drivers of translocated populations: Ecological Applications, v. 32, no. 6, e2635, 28 p., https://doi.org/10.1002/eap.2635.","productDescription":"e2635, 28 p.","ipdsId":"IP-133488","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2635","text":"Publisher Index Page"},{"id":412276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.22104062583205,\n              37.1531119094322\n            ],\n            [\n              -114.22104062583205,\n              35.597035865673504\n            ],\n            [\n              -111.47562451867627,\n              35.597035865673504\n            ],\n            [\n              -111.47562451867627,\n              37.1531119094322\n            ],\n            [\n              -114.22104062583205,\n              37.1531119094322\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Healy, Brian D","contributorId":287820,"corporation":false,"usgs":false,"family":"Healy","given":"Brian","email":"","middleInitial":"D","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":862243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":862244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conner, Mary M.","contributorId":301156,"corporation":false,"usgs":false,"family":"Conner","given":"Mary M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":862245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Omana Smith, Emily C.","contributorId":301157,"corporation":false,"usgs":false,"family":"Omana Smith","given":"Emily","email":"","middleInitial":"C.","affiliations":[{"id":65320,"text":"Native Fish Ecology and Conservation Program","active":true,"usgs":false}],"preferred":false,"id":862246,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240995,"text":"70240995 - 2022 - Food web perspectives and methods for riverine fish conservation","interactions":[],"lastModifiedDate":"2023-03-03T12:42:17.726761","indexId":"70240995","displayToPublicDate":"2022-04-11T06:40:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13444,"text":"Wiley Interdisciplinary Reviews (WIREs): Water","active":true,"publicationSubtype":{"id":10}},"title":"Food web perspectives and methods for riverine fish conservation","docAbstract":"<p>Food web analyses offer useful insights into understanding how species interactions, trophic relationships, and energy flow underpin important demographic parameters of fish populations such as survival, growth, and reproduction. However, the vast amount of food web literature and the diversity of approaches can be a deterrent to fisheries practitioners engaged in on-the-ground research, monitoring, or restoration. Incorporation of food web perspectives into contemporary fisheries management and conservation is especially rare in riverine systems, where approaches often focus more on the influence of physical habitat and water temperature on fish populations. In this review, we first discuss the importance of food webs in the context of several common fisheries management issues, including assessing carrying capacity, evaluating the effects of habitat change, examining species introductions or extinctions, considering bioaccumulation of toxins, and predicting the effects of climate change and other anthropogenic stressors on riverine fishes. We then examine several relevant perspectives: basic food web description, metabolic models, trophic basis of production, mass-abundance network approaches, ecological stoichiometry, and mathematical modeling. Finally, we highlight several existing and emerging methodologies including diet and prey surveys, eDNA, stable isotopes, fatty acids, and community and network analysis. Although our emphasis and most examples are focused on salmonids in riverine environments, the concepts are easily generalizable to other freshwater fish taxa and ecosystems.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1590","usgsCitation":"Naman, S.M., White, S.M., Bellmore, J.R., McHugh, P.A., Kaylor, M.J., Baxter, C., Danehy, R.J., Naiman, R., and Puls, A.L., 2022, Food web perspectives and methods for riverine fish conservation: Wiley Interdisciplinary Reviews (WIREs): Water, v. 9, no. 4, e1590, 21 p., https://doi.org/10.1002/wat2.1590.","productDescription":"e1590, 21 p.","ipdsId":"IP-134531","costCenters":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"links":[{"id":448168,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1590","text":"Publisher Index Page"},{"id":413654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Naman, Sean M.","contributorId":302860,"corporation":false,"usgs":false,"family":"Naman","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":865646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Seth M.","contributorId":302862,"corporation":false,"usgs":false,"family":"White","given":"Seth","email":"","middleInitial":"M.","affiliations":[{"id":13314,"text":"Columbia River Inter-Tribal Fish Commission","active":true,"usgs":false}],"preferred":false,"id":865647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bellmore, J. Ryan","contributorId":271034,"corporation":false,"usgs":false,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[{"id":56260,"text":"U.S. Forest Service, Pacific Northwest Research Station, 11175 Auke Lake Way, Juneau, Alaska, 99801","active":true,"usgs":false}],"preferred":false,"id":865648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHugh, Peter A.","contributorId":302865,"corporation":false,"usgs":false,"family":"McHugh","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":65566,"text":"Eco Logical Research / Utah State University","active":true,"usgs":false}],"preferred":false,"id":865649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaylor, Matthew J.","contributorId":302867,"corporation":false,"usgs":false,"family":"Kaylor","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":865650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baxter, Colden V.","contributorId":272243,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":56375,"text":"isu","active":true,"usgs":false}],"preferred":false,"id":865651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Danehy, Robert J.","contributorId":302868,"corporation":false,"usgs":false,"family":"Danehy","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":39532,"text":"Catchment Aquatic Ecology","active":true,"usgs":false}],"preferred":false,"id":865652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Naiman, Robert J.","contributorId":302869,"corporation":false,"usgs":false,"family":"Naiman","given":"Robert J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":865653,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Puls, Amy L. 0000-0002-2686-4187 apuls@usgs.gov","orcid":"https://orcid.org/0000-0002-2686-4187","contributorId":204734,"corporation":false,"usgs":true,"family":"Puls","given":"Amy","email":"apuls@usgs.gov","middleInitial":"L.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":865654,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70230445,"text":"70230445 - 2022 - Decline in biological soil crust N-fixing lichens linked to increasing summertime temperatures","interactions":[],"lastModifiedDate":"2022-04-13T11:39:41.160794","indexId":"70230445","displayToPublicDate":"2022-04-11T06:38:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10548,"text":"Proceedings of the National Academies of Science (PNAS)","active":true,"publicationSubtype":{"id":10}},"title":"Decline in biological soil crust N-fixing lichens linked to increasing summertime temperatures","docAbstract":"<div>Across many global drylands, biocrusts form a protective barrier on the soil surface and fill many critical roles in these harsh yet fragile environments. Previous short-term research suggests that climate change and invasive plant introduction can damage and alter biocrust communities, yet few long-term observations exist. Using a globally unique long-term record of continuous biocrust surveys from a rare never-grazed, protected grassland on the US Colorado Plateau, we found lichen species diversity and cover to be negatively correlated with increasing summer air temperatures, while moss species showed more sensitivity to variation in precipitation and invasive grass cover. These results suggest that dryland systems may be at a critical tipping point where ongoing warming could result in biological soil crust degradation.</div>","language":"English","publisher":"National Academy of Science","doi":"10.1073/pnas.2120975119","usgsCitation":"Finger-Higgens, R.A., Duniway, M.C., Fick, S.E., Geiger, E.L., Hoover, D.L., Pfennigwerth, A., Van Scoyoc, M.W., and Belnap, J., 2022, Decline in biological soil crust N-fixing lichens linked to increasing summertime temperatures: Proceedings of the National Academies of Science (PNAS), v. 119, no. 16, e2120975119, 8 p., https://doi.org/10.1073/pnas.2120975119.","productDescription":"e2120975119, 8 p.","ipdsId":"IP-129948","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448171,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9169860","text":"Publisher Index Page"},{"id":435885,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MA0LZG","text":"USGS data release","linkHelpText":"Biocrust cover, vegetation, and climate data from a protected grassland within Canyonlands National Park, Utah (ver. 2.0, Sept. 2023)"},{"id":398625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Finger-Higgens, Rebecca A 0000-0002-7645-504X","orcid":"https://orcid.org/0000-0002-7645-504X","contributorId":290211,"corporation":false,"usgs":true,"family":"Finger-Higgens","given":"Rebecca","email":"","middleInitial":"A","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":840456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":840457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fick, Stephen E. 0000-0002-3548-6966","orcid":"https://orcid.org/0000-0002-3548-6966","contributorId":214319,"corporation":false,"usgs":true,"family":"Fick","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":840458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geiger, Erika L. 0000-0003-4546-3503","orcid":"https://orcid.org/0000-0003-4546-3503","contributorId":207502,"corporation":false,"usgs":true,"family":"Geiger","given":"Erika","email":"","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":840459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":245331,"corporation":false,"usgs":false,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":49151,"text":"USDA-ARS Rangeland Resources Research Unit, Crops Research Laboratory, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":840460,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pfennigwerth, Alix A. 0000-0001-5102-7324","orcid":"https://orcid.org/0000-0001-5102-7324","contributorId":265925,"corporation":false,"usgs":false,"family":"Pfennigwerth","given":"Alix A.","affiliations":[{"id":54826,"text":"Southwest Biological Science Center-Affiliate","active":true,"usgs":false}],"preferred":false,"id":840461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Scoyoc, Matthew W. 0000-0001-6821-4476","orcid":"https://orcid.org/0000-0001-6821-4476","contributorId":290213,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":62383,"text":"Southeast Utah Group, National Park Service, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":840462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":840463,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70255174,"text":"70255174 - 2022 - Optimizing management of invasions in an uncertain world using dynamic spatial models","interactions":[],"lastModifiedDate":"2024-06-13T15:11:21.379743","indexId":"70255174","displayToPublicDate":"2022-04-09T10:01:04","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":"Optimizing management of invasions in an uncertain world using dynamic spatial models","docAbstract":"<p><span>Dispersal drives invasion dynamics of nonnative species and pathogens. Applying knowledge of dispersal to optimize the management of invasions can mean the difference between a failed and a successful control program and dramatically improve the return on investment of control efforts. A common approach to identifying optimal management solutions for invasions is to optimize dynamic spatial models that incorporate dispersal. Optimizing these spatial models can be very challenging because the interaction of time, space, and uncertainty rapidly amplifies the number of dimensions being considered. Addressing such problems requires advances in and the integration of techniques from multiple fields, including ecology, decision analysis, bioeconomics, natural resource management, and optimization. By synthesizing recent advances from these diverse fields, we provide a workflow for applying ecological theory to advance optimal management science and highlight priorities for optimizing the control of invasions. One of the striking gaps we identify is the extremely limited consideration of dispersal uncertainty in optimal management frameworks, even though dispersal estimates are highly uncertain and greatly influence invasion outcomes. In addition, optimization frameworks rarely consider multiple types of uncertainty (we describe five major types) and their interrelationships. Thus, feedbacks from management or other sources that could magnify uncertainty in dispersal are rarely considered. Incorporating uncertainty is crucial for improving transparency in decision risks and identifying optimal management strategies. We discuss gaps and solutions to the challenges of optimization using dynamic spatial models to increase the practical application of these important tools and improve the consistency and robustness of management recommendations for invasions.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2628","usgsCitation":"Pepin, K., Davis, A., Epanchin-Niell, R.S., Gormley, A.M., Moore, J., Smyser, T.J., Shaffer, H., Kendall, W.L., Shea, K., Runge, M.C., and McKee, S., 2022, Optimizing management of invasions in an uncertain world using dynamic spatial models: Ecological Applications, v. 32, no. 6, e2628, 21 p., https://doi.org/10.1002/eap.2628.","productDescription":"e2628, 21 p.","ipdsId":"IP-119939","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":903662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Amy J.","contributorId":279408,"corporation":false,"usgs":false,"family":"Davis","given":"Amy J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":903663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Epanchin-Niell, Rebecca S.","contributorId":175364,"corporation":false,"usgs":false,"family":"Epanchin-Niell","given":"Rebecca","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":903664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gormley, Andrew M.","contributorId":338892,"corporation":false,"usgs":false,"family":"Gormley","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":81209,"text":"Manaaki Whenua – Landcare Research","active":true,"usgs":false}],"preferred":false,"id":903665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Joslin L.","contributorId":257914,"corporation":false,"usgs":false,"family":"Moore","given":"Joslin L.","affiliations":[{"id":27278,"text":"Monash University","active":true,"usgs":false}],"preferred":false,"id":903666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smyser, Timothy J.","contributorId":279407,"corporation":false,"usgs":false,"family":"Smyser","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":903667,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaffer, H. Bradley","contributorId":71051,"corporation":false,"usgs":true,"family":"Shaffer","given":"H. Bradley","affiliations":[],"preferred":false,"id":903668,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903661,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shea, Katriona 0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":903669,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"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":903670,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McKee, Sophie","contributorId":279410,"corporation":false,"usgs":false,"family":"McKee","given":"Sophie","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":903671,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70230314,"text":"70230314 - 2022 - Evaluating sources of bias in pedigree-based estimates of breeding population size","interactions":[],"lastModifiedDate":"2022-07-08T15:41:48.075522","indexId":"70230314","displayToPublicDate":"2022-04-05T08:47:42","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":"Evaluating sources of bias in pedigree-based estimates of breeding population size","docAbstract":"<p>Applications of genetic-based estimates of population size are expanding, especially for species for which traditional demographic estimation methods are intractable due to the rarity of adult encounters. Estimates of breeding population size (<i>N<sub>S</sub></i>) are particularly amenable to genetic-based approaches as the parameter can be estimated using pedigrees reconstructed from genetic data gathered from discrete juvenile cohorts, therefore eliminating the need to sample adults in the population. However, a critical evaluation of how genotyping and sampling effort influence bias in pedigree reconstruction, and how these biases subsequently influence estimates of <i>N<sub>S</sub></i>, is needed to evaluate the efficacy of the approach under a range of scenarios. We simulated a model system to understand the interactive effects of genotyping and sampling effort on error in genetic pedigrees reconstructed from the program <i>COLONY</i>. We then evaluated how errors in pedigree reconstruction influenced bias and precision in estimates of <i>N<sub>S</sub></i> using three different rarefaction estimators. Results indicated that pedigree error can be minimal when adequate genetic data are available, such as when juvenile sample sizes are large and/or individuals are genotyped at many informative loci. However, even in cases for which data are limited, using results of the simulation analysis to understand the magnitude and sources of bias in reconstructed pedigrees can still be informative when estimating <i>N<sub>S</sub></i>. We applied results of the simulation analysis to evaluate <i>Nˆ<sub>S</sub></i> for a population of federally endangered Atlantic sturgeon (<i>Acipenser oxyrinchus oxyrinchus</i>) in the Delaware River, USA. Our results indicated that <i>N<sub>S</sub></i> is likely to be three orders of magnitude lower compared with historic breeding population sizes, which is a considerable advancement in our understanding of the population status of Atlantic sturgeon in the Delaware River. Our analyses are broadly applicable in the design and interpretation of studies seeking to estimate <i>N<sub>S</sub></i> and can help to guide conservation decisions when ecological uncertainty is high. The utility of these results is expected to grow as rapid advances in genetic technologies increase the popularity of genetic population monitoring and estimation.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2602","usgsCitation":"White, S.L., Sard, N.M., Brundage III, H., Johnson, R.L., Lubinski, B.A., Eackles, M.S., Park, I.A., Fox, D.A., and Kazyak, D., 2022, Evaluating sources of bias in pedigree-based estimates of breeding population size: Ecological Applications, v. 32, no. 5, e2602, 13 p., https://doi.org/10.1002/eap.2602.","productDescription":"e2602, 13 p.","ipdsId":"IP-114638","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2602","text":"Publisher Index Page"},{"id":398310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.794677734375,\n              39.614152077002664\n            ],\n            [\n              -74.542236328125,\n              39.614152077002664\n            ],\n            [\n              -74.542236328125,\n              41.40153558289846\n            ],\n            [\n              -75.794677734375,\n              41.40153558289846\n            ],\n            [\n              -75.794677734375,\n              39.614152077002664\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"32","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":839957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sard, Nicholas M","contributorId":289872,"corporation":false,"usgs":false,"family":"Sard","given":"Nicholas","email":"","middleInitial":"M","affiliations":[{"id":48660,"text":"SUNY Oswego","active":true,"usgs":false}],"preferred":false,"id":839958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brundage III, Harold M","contributorId":289873,"corporation":false,"usgs":false,"family":"Brundage III","given":"Harold M","affiliations":[{"id":62274,"text":"Environmental Research and Consulting Inc","active":true,"usgs":false}],"preferred":false,"id":839959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":839960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":839961,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eackles, Michael S. 0000-0001-5624-5769 meackles@usgs.gov","orcid":"https://orcid.org/0000-0001-5624-5769","contributorId":218936,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":839962,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Park, Ian A","contributorId":289876,"corporation":false,"usgs":false,"family":"Park","given":"Ian","email":"","middleInitial":"A","affiliations":[{"id":62277,"text":"DNREC","active":true,"usgs":false}],"preferred":false,"id":839963,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fox, Dewayne A.","contributorId":117052,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","email":"","middleInitial":"A.","affiliations":[{"id":12970,"text":"Department of Agriculture and Natural Resources, Delaware State University","active":true,"usgs":false}],"preferred":false,"id":839964,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":839965,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70230431,"text":"70230431 - 2022 - Post-Early Miocene silicic volcanism in the northern Mojave Desert, California","interactions":[],"lastModifiedDate":"2022-04-13T13:21:26.717806","indexId":"70230431","displayToPublicDate":"2022-04-01T08:14:16","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Post-Early Miocene silicic volcanism in the northern Mojave Desert, California","docAbstract":"Silicic volcanism that postdates widespread early Miocene volcanism in the Mojave Desert is underappreciated. We compiled age, petrographic, and geochemical data for volcanic rocks in a wide swath of the desert south of the Garlock fault using an age threshold of post-18.8 Ma, approximately the limit of the earlier Miocene volcanism as marked by the eruption of the widespread Peach Spring Tuff. In addition to the well-known young basaltic volcanic centers not considered in this paper, several dozen silicic volcanic edifices are known or likely to be younger than 18.8 Ma. Several examples of rhyolite tuffs and basalt lava in middle Miocene basin occur in sequences of the Barstow Formation and its correlatives. Dacite domes are common in the Calico Mountains, dated at ~17 Ma, and similar, but mostly undated, domes are scattered nearby in the Barstow area and east of the Calico Mountains. North of Barstow, chains of rhyolite domes and scattered dacite domes are known. A few of these domes and flows are dated in the range of 13-7 Ma. Farther north, the Lava Mountains have several volcanic sequences from 12 to 7 Ma and ranging in composition from basalt to rhyolite. Farther east and west are more rhyolite and dacite domes, in general undated, as well as the extensive ~17.8 Ma Woods Mountains rhyolite center. Sparse geochemical data for the silicic rocks indicate distinct rhyolite and dacite groups, and rare andesite. Understanding of these potentially young silicic volcanic rocks is hampered by poor age control and geochemical data, but more study holds promise for better understanding the origins of volcanism in the Mojave Desert.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Volcanoes in the Mojave: 2022 Desert symposium field guide and proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Desert Symposium Inc","usgsCitation":"Miller, D., Gans, P.B., Felger, T.J., and Vazquez, J.A., 2022, Post-Early Miocene silicic volcanism in the northern Mojave Desert, California, <i>in</i> Volcanoes in the Mojave: 2022 Desert symposium field guide and proceedings, p. 124-141.","productDescription":"18 p.","startPage":"124","endPage":"141","ipdsId":"IP-137943","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":398642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398614,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertsymposium.org"}],"country":"United States","state":"California, Nevada","otherGeospatial":"northern Mojave Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119,\n              34\n            ],\n            [\n              -114,\n              34\n            ],\n            [\n              -114,\n              37\n            ],\n            [\n              -119,\n              37\n            ],\n            [\n              -119,\n              34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":238721,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gans, Phillip B 0000-0003-0373-9639","orcid":"https://orcid.org/0000-0003-0373-9639","contributorId":204410,"corporation":false,"usgs":false,"family":"Gans","given":"Phillip","email":"","middleInitial":"B","affiliations":[{"id":36937,"text":"Dept of Earth Science, Univ of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":840410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Felger, Tracey J. 0000-0003-0841-4235 tfelger@usgs.gov","orcid":"https://orcid.org/0000-0003-0841-4235","contributorId":290175,"corporation":false,"usgs":true,"family":"Felger","given":"Tracey","email":"tfelger@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":840412,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70230703,"text":"70230703 - 2022 - To catch a (marsh) predator: Modified trapping methods for breeding and wintering Northern Harriers (Circus hudsonius)","interactions":[],"lastModifiedDate":"2022-05-13T15:09:50.467724","indexId":"70230703","displayToPublicDate":"2022-04-01T06:46:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"To catch a (marsh) predator: Modified trapping methods for breeding and wintering Northern Harriers (Circus hudsonius)","docAbstract":"<div><div id=\"14172486\" class=\"article-section-wrapper js-article-section js-content-section  \"><p>Although there are a variety of methods available for trapping raptors, some species, such as Northern Harriers (<i>Circus hudsonius</i>), are not easily captured with standard methods. We tested several existing trapping methods and modified two of them based on Northern Harrier ecology and behavior across seasons in a study population in California. No previously successful methods described in the literature were effective for our study population. Two modified methods were most effective for trapping Northern Harriers: (1) placing two dho-gazas around the nest in a V-shape and flushing the adult female into the nets during the breeding season, and (2) using remote-triggered bow nets baited with waterbird carcasses in winter. Dho-gazas at the nest worked well during the early nestling-rearing stage, when nestlings were younger than 2 wk old and adult females were most attentive. This method was not suitable during the incubation stage because Northern Harriers are prone to nest abandonment. In the winter, Northern Harriers are known to scavenge, yet this aspect of their behavioral ecology has previously been rarely exploited for trapping purposes. These two methods allow for selective Northern Harrier trapping across seasons and provide modified options for research on this understudied and declining species in North America.</p></div></div>","language":"English","publisher":"Allen Press","doi":"10.3356/JRR-21-79","usgsCitation":"Skalos, S., Casazza, M.L., Falcon, M.J., Thein, W., and Hull, J.M., 2022, To catch a (marsh) predator: Modified trapping methods for breeding and wintering Northern Harriers (Circus hudsonius): Journal of Raptor Research, v. 56, no. 2, p. 190-200, https://doi.org/10.3356/JRR-21-79.","productDescription":"11 p.","startPage":"190","endPage":"200","ipdsId":"IP-133127","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":399388,"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        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.01553344726561,\n              38.029703972192\n            ],\n            [\n              -121.86721801757812,\n              38.029703972192\n            ],\n            [\n              -121.86721801757812,\n              38.20365531807149\n            ],\n            [\n              -122.01553344726561,\n              38.20365531807149\n            ],\n            [\n              -122.01553344726561,\n              38.029703972192\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skalos, Shannon 0000-0003-1229-8580 sskalos@usgs.gov","orcid":"https://orcid.org/0000-0003-1229-8580","contributorId":167191,"corporation":false,"usgs":true,"family":"Skalos","given":"Shannon","email":"sskalos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":841187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":841188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falcon, Matthew J.","contributorId":260146,"corporation":false,"usgs":false,"family":"Falcon","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":841189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thein, William","contributorId":290525,"corporation":false,"usgs":false,"family":"Thein","given":"William","email":"","affiliations":[],"preferred":false,"id":841190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hull, Joshua M.","contributorId":127686,"corporation":false,"usgs":false,"family":"Hull","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":841191,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70266316,"text":"70266316 - 2022 - Post-fledging spatial dispersion and movement behaviour differs between cavity-nesting and open-cup nesting passerines","interactions":[],"lastModifiedDate":"2025-05-05T14:57:19.102499","indexId":"70266316","displayToPublicDate":"2022-04-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Post-fledging spatial dispersion and movement behaviour differs between cavity-nesting and open-cup nesting passerines","docAbstract":"Spatial dispersion and movement behaviour vary across animal taxa and can affect fitness. The reasons why species differ in movement behaviour of young and why some species form family groups and other species have dispersed young have been rarely addressed. We tested a hypothesis that spatial dispersion and movement behaviour of dependent young were influenced by their developmental state and mobile capacity. In songbirds, offspring of species that nest in holes leave the nest with well-developed wings and initially are more mobile than species that nest in open cups. We used radio-telemetry to track fledglings of three hole- and three open-nesting songbird species to test if young differ in spatial dispersion and movement behaviour between nest types. We found that mobile young of hole-nesting species moved farther on a daily basis but remained more aggregated as a family than the less mobile young of open-nesting species. Movement distances increased with mobile capacity as young aged, especially in open-nesting species, but families of open-nesting species remained dispersed throughout the first week after fledging. This variation in spatial dispersion and movement behaviour of young can have important implications for parental care strategies and juvenile survival.","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13027","usgsCitation":"Arslan, N.S., and Martin, T.E., 2022, Post-fledging spatial dispersion and movement behaviour differs between cavity-nesting and open-cup nesting passerines: Ibis, v. 164, no. 2, p. 486-493, https://doi.org/10.1111/ibi.13027.","productDescription":"8 p.","startPage":"486","endPage":"493","ipdsId":"IP-130046","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Coconino National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.04010085378371,\n              35.41147618097317\n            ],\n            [\n              -112.04010085378371,\n              34.25447924403382\n            ],\n            [\n              -110.8598291205829,\n              34.25447924403382\n            ],\n            [\n              -110.8598291205829,\n              35.41147618097317\n            ],\n            [\n              -112.04010085378371,\n              35.41147618097317\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"164","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Arslan, Necmiye Sahin","contributorId":272527,"corporation":false,"usgs":false,"family":"Arslan","given":"Necmiye","email":"","middleInitial":"Sahin","affiliations":[{"id":50219,"text":"um","active":true,"usgs":false}],"preferred":false,"id":935565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935564,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70230106,"text":"70230106 - 2022 - Quantifying the relationship between prey density, livestock and illegal killing of leopards","interactions":[],"lastModifiedDate":"2022-06-16T15:24:17.223503","indexId":"70230106","displayToPublicDate":"2022-03-30T11:23:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the relationship between prey density, livestock and illegal killing of leopards","docAbstract":"<ol class=\"\"><li>Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events. Despite the importance of illegal killing of large carnivores in comparison with other causes of mortality, its relationship with potential drivers such as livestock density and wild prey abundance is rarely described.</li><li>Using ranger-collected data (2007-2019) of leopard killing events and data on covariates (livestock density, wild prey abundance, road length, protected area size, elevation) across Iran, we applied a single-visit N-mixture model to jointly model variation in detection probability and expected annualized number of leopard killing events.</li><li>Over the study period, we estimated 428 leopard mortalities (95% CI 184–1014), which was 45% larger than the observed number. Expected intensity of leopard killing was positively related to protected area size, livestock density and wild prey abundance. Detection of leopard killing was higher in areas with more developed road networks.</li><li>Synthesis and applications: Ranger based monitoring data on poaching of carnivores are cost effective, but traditional analysis does not take into account imperfect detection. We show that innovative statistics (single-visit N-mixture modeling) can reliably quantify poaching events and address their drivers, at large geographical scales. We used the example of the Persian leopard across Iran, but our approach is also applicable to understand killing dynamics of other species. Results suggest that a high frequency of leopard killing is likely to occur in areas with &gt; 100 livestock per km<sup>2</sup>&nbsp;and &gt; 450 individuals of wild prey per km<sup>2</sup>. This highlights the need for improved management of livestock grazing and effective measures around high-risk protected areas to mitigate human-leopard conflict and reduce killing of leopards.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.14163","usgsCitation":"Soofi, M., Qashqaei, A.T., Mousavi, M., Hadipour, E., Filla, M., Kiabi, B.H., Bleyhl, B., Ghoddousi, A., Balkenhol, N., Royle, A., Pavey, C.R., Khorozyan, I., and Waltert, M., 2022, Quantifying the relationship between prey density, livestock and illegal killing of leopards: Journal of Applied Ecology, v. 59, no. 6, p. 1536-1547, https://doi.org/10.1111/1365-2664.14163.","productDescription":"12 p.","startPage":"1536","endPage":"1547","ipdsId":"IP-136705","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://research.wur.nl/en/publications/quantifying-the-relationship-between-prey-density-livestock-and-i","text":"Publisher Index Page"},{"id":397872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[53.9216,37.19892],[54.8003,37.39242],[55.51158,37.96412],[56.18037,37.93513],[56.61937,38.12139],[57.33043,38.02923],[58.43615,37.52231],[59.23476,37.41299],[60.37764,36.52738],[61.12307,36.4916],[61.21082,35.65007],[60.80319,34.4041],[60.52843,33.67645],[60.9637,33.52883],[60.53608,32.98127],[60.86365,32.18292],[60.94194,31.54807],[61.69931,31.37951],[61.78122,30.73585],[60.87425,29.82924],[61.36931,29.30328],[61.77187,28.69933],[62.72783,28.25964],[62.75543,27.37892],[63.2339,27.21705],[63.31663,26.75653],[61.87419,26.23997],[61.49736,25.07824],[59.61613,25.38016],[58.52576,25.60996],[57.39725,25.7399],[56.97077,26.96611],[56.49214,27.1433],[55.72371,26.96463],[54.71509,26.48066],[53.4931,26.81237],[52.4836,27.58085],[51.52076,27.86569],[50.85295,28.81452],[50.11501,30.14777],[49.57685,29.98572],[48.94133,30.31709],[48.56797,29.92678],[48.01457,30.45246],[48.0047,30.98514],[47.68529,30.98485],[47.8492,31.70918],[47.33466,32.46916],[46.10936,33.01729],[45.41669,33.9678],[45.64846,34.74814],[46.15179,35.09326],[46.07634,35.67738],[45.42062,35.97755],[44.77267,37.17045],[44.22576,37.97158],[44.4214,38.28128],[44.10923,39.42814],[44.79399,39.713],[44.95269,39.33576],[45.45772,38.87414],[46.14362,38.7412],[46.50572,38.77061],[47.68508,39.50836],[48.0601,39.58224],[48.35553,39.28876],[48.01074,38.79401],[48.63438,38.27038],[48.88325,38.32025],[49.19961,37.58287],[50.14777,37.37457],[50.84235,36.87281],[52.26402,36.70042],[53.82579,36.96503],[53.9216,37.19892]]]},\"properties\":{\"name\":\"Iran\"}}]}","volume":"59","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-04-11","publicationStatus":"PW","contributors":{"editors":[{"text":"Hayward, Matt W.","contributorId":168588,"corporation":false,"usgs":false,"family":"Hayward","given":"Matt","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":839294,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Soofi, Mahmood","contributorId":287507,"corporation":false,"usgs":false,"family":"Soofi","given":"Mahmood","affiliations":[{"id":61590,"text":"School of Biological Sciences, University of Aberdeen","active":true,"usgs":false}],"preferred":false,"id":839044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qashqaei, Ali T.","contributorId":287508,"corporation":false,"usgs":false,"family":"Qashqaei","given":"Ali","email":"","middleInitial":"T.","affiliations":[{"id":61592,"text":"Sahel Square, Parsia Complex, Tehran","active":true,"usgs":false}],"preferred":false,"id":839045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mousavi, Marzieh","contributorId":289355,"corporation":false,"usgs":false,"family":"Mousavi","given":"Marzieh","email":"","affiliations":[{"id":62108,"text":"Wildlife Conservation and Management Bureau, Biodiversity and Natural Environment Division, Iran Department of Environment","active":true,"usgs":false}],"preferred":false,"id":839046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hadipour, Ehsan","contributorId":289356,"corporation":false,"usgs":false,"family":"Hadipour","given":"Ehsan","email":"","affiliations":[{"id":62109,"text":"Dept of the Environment, Iran","active":true,"usgs":false}],"preferred":false,"id":839047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Filla, Marc","contributorId":289357,"corporation":false,"usgs":false,"family":"Filla","given":"Marc","email":"","affiliations":[{"id":62110,"text":"Department of Conservation Biology, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":839048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kiabi, Bahram H.","contributorId":287518,"corporation":false,"usgs":false,"family":"Kiabi","given":"Bahram","email":"","middleInitial":"H.","affiliations":[{"id":61603,"text":"Eskandari 14, PO. Box 14195149, Tehran, Iran.","active":true,"usgs":false}],"preferred":false,"id":839049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bleyhl, Benjamin","contributorId":289359,"corporation":false,"usgs":false,"family":"Bleyhl","given":"Benjamin","email":"","affiliations":[{"id":62112,"text":"Geography Department, Humboldt-Universität zu Berlin, Unter den Linden","active":true,"usgs":false}],"preferred":false,"id":839050,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ghoddousi, Arash","contributorId":289360,"corporation":false,"usgs":false,"family":"Ghoddousi","given":"Arash","email":"","affiliations":[{"id":62114,"text":"Wildlife Sciences, University of Goettingen, Buesgenweg","active":true,"usgs":false}],"preferred":false,"id":839051,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Balkenhol, Niko","contributorId":287519,"corporation":false,"usgs":false,"family":"Balkenhol","given":"Niko","affiliations":[{"id":61604,"text":"Wildlife Sciences, University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":839052,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":839053,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pavey, Chris R.","contributorId":287520,"corporation":false,"usgs":false,"family":"Pavey","given":"Chris","email":"","middleInitial":"R.","affiliations":[{"id":39017,"text":"CSIRO Land and Water","active":true,"usgs":false}],"preferred":false,"id":839291,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Khorozyan, Igor","contributorId":289545,"corporation":false,"usgs":false,"family":"Khorozyan","given":"Igor","affiliations":[{"id":62105,"text":"University of Goettingen","active":true,"usgs":false}],"preferred":false,"id":839292,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Waltert, Matthias","contributorId":287597,"corporation":false,"usgs":false,"family":"Waltert","given":"Matthias","affiliations":[{"id":37650,"text":"University of Goettingen, Goettingen, Germany","active":true,"usgs":false}],"preferred":false,"id":839293,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70248721,"text":"70248721 - 2022 - Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density","interactions":[],"lastModifiedDate":"2023-09-18T14:05:04.028786","indexId":"70248721","displayToPublicDate":"2022-03-27T08:53:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density","docAbstract":"<p><span>Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium,&nbsp;</span><i>Gloeotrichia echinulata</i><span>. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of&nbsp;</span><i>G. echinulata</i><span>&nbsp;densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2590","usgsCitation":"Lofton, M., Brentrup, J.A., Beck, W.S., Zwart, J.A., Bhattacharya, R., Brighenti, L.S., Burnett, S.H., McCullough, I.M., Steele, B., Carey, C.C., Cottingham, K., Dietze, M., Ewing, H.A., Weathers, K.C., and LaDeau, S.L., 2022, Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density: Ecological Applications, v. 32, e2590, 24 p., https://doi.org/10.1002/eap.2590.","productDescription":"e2590, 24 p.","ipdsId":"IP-119852","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2590","text":"Publisher Index Page"},{"id":420889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire","otherGeospatial":"Lake Sunapee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.10639790180213,\n              43.45916503807919\n            ],\n            [\n              -72.10639790180213,\n              43.3077735355308\n            ],\n            [\n              -72.01805843117764,\n              43.3077735355308\n            ],\n            [\n              -72.01805843117764,\n              43.45916503807919\n            ],\n            [\n              -72.10639790180213,\n              43.45916503807919\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"32","noUsgsAuthors":false,"publicationDate":"2022-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lofton, Mary","contributorId":329783,"corporation":false,"usgs":false,"family":"Lofton","given":"Mary","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":883298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brentrup, Jennifer A.","contributorId":194457,"corporation":false,"usgs":false,"family":"Brentrup","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":883299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, Whitney S.","contributorId":268335,"corporation":false,"usgs":false,"family":"Beck","given":"Whitney","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":883300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bhattacharya, Ruchi","contributorId":297412,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Ruchi","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":883302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brighenti, Ludmila S","contributorId":317713,"corporation":false,"usgs":false,"family":"Brighenti","given":"Ludmila","email":"","middleInitial":"S","affiliations":[{"id":69135,"text":"Universidade do Estado de Minas Gerais","active":true,"usgs":false}],"preferred":false,"id":883303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burnett, Sarah H.","contributorId":288140,"corporation":false,"usgs":false,"family":"Burnett","given":"Sarah","email":"","middleInitial":"H.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":883304,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":883305,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steele, Bethel 0000-0003-4365-4103","orcid":"https://orcid.org/0000-0003-4365-4103","contributorId":329785,"corporation":false,"usgs":false,"family":"Steele","given":"Bethel","email":"","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":883306,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":883307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cottingham, Kathryn L","contributorId":329786,"corporation":false,"usgs":false,"family":"Cottingham","given":"Kathryn L","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":883308,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dietze, Michael","contributorId":248349,"corporation":false,"usgs":false,"family":"Dietze","given":"Michael","affiliations":[],"preferred":false,"id":883309,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ewing, Holly A.","contributorId":191962,"corporation":false,"usgs":false,"family":"Ewing","given":"Holly","email":"","middleInitial":"A.","affiliations":[{"id":33413,"text":"Bates College","active":true,"usgs":false}],"preferred":false,"id":883310,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weathers, Kathleen C.","contributorId":202417,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","email":"","middleInitial":"C.","affiliations":[{"id":36424,"text":"Cary Institute of Ecosystems Studies","active":true,"usgs":false}],"preferred":false,"id":883311,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"LaDeau, Shannon L.","contributorId":172640,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":883312,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70229833,"text":"70229833 - 2022 - A comparison of eDNA and visual survey methods for detection of longnose darter Percina nasuta in Missouri","interactions":[],"lastModifiedDate":"2022-03-21T13:49:21.154022","indexId":"70229833","displayToPublicDate":"2022-03-18T08:46:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A comparison of eDNA and visual survey methods for detection of longnose darter <i>Percina nasuta</i> in Missouri","title":"A comparison of eDNA and visual survey methods for detection of longnose darter Percina nasuta in Missouri","docAbstract":"<p><span>The longnose darter&nbsp;</span><i><span class=\"html-italic\">Percina nasuta</span></i><span>&nbsp;is a rare and cryptic fish that recently disappeared from much of its historic range. We developed and used an environmental DNA (eDNA) assay for longnose darter paired with visual surveys to better determine the species’ range and compare detection probability between sampling approaches in an occupancy modeling framework. We detected longnose darter eDNA further upstream in the mainstem St. Francis River than previously reported and in a tributary for the first time. Our multi-scale occupancy approach compared models where detection was constant against a model that allowed detection to vary by survey method. The constant model received the most support indicating survey method was not a strong predictor and detection was estimated at 0.70 (0.45–0.86; 95% CI) across both methods. Our study produced effective longnose darter eDNA primers and demonstrated the application of eDNA for sampling small-bodied, cryptic fish. We detected longnose darter eDNA 27 km upstream of their known range and determined that snorkel surveys are the most efficient sampling method if water clarity allows. We recommend target sample sizes to achieve various detection goals for both sample methods and our results inform future design of distributional and monitoring efforts.</span></p>","language":"English","publisher":"MPDI","doi":"10.3390/fishes7020070","usgsCitation":"Westhoff, J.T., Berkman, L.K., Klymus, K.E., Thompson, N., and Richter, C.A., 2022, A comparison of eDNA and visual survey methods for detection of longnose darter Percina nasuta in Missouri: Fishes, v. 7, no. 2, 70, 16 p., https://doi.org/10.3390/fishes7020070.","productDescription":"70, 16 p.","ipdsId":"IP-121698","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":448443,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes7020070","text":"Publisher Index Page"},{"id":435919,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z597LN","text":"USGS data 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