{"pageNumber":"180","pageRowStart":"4475","pageSize":"25","recordCount":40778,"records":[{"id":70229738,"text":"70229738 - 2022 - A climate-mediated shift in the estuarine habitat mosaic limits prey availability and reduces nursery quality for juvenile salmon","interactions":[],"lastModifiedDate":"2022-08-01T16:54:11.965385","indexId":"70229738","displayToPublicDate":"2022-03-16T10:00:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A climate-mediated shift in the estuarine habitat mosaic limits prey availability and reduces nursery quality for juvenile salmon","docAbstract":"

The estuarine habitat mosaic supports the reproduction, growth, and survival of resident and migratory fish species by providing a diverse portfolio of unique habitats with varying physical and biological features. Global climate change is expected to result in increasing temperatures, rising sea levels, and changes in riverine hydrology, which will have profound effects on the extent and composition of the estuarine habitat mosaic and its associated nursery quality for juvenile fish. We used a spatially explicit bioenergetics model to assess how different climate change scenarios might affect juvenile salmon growth rate potential relative to present day conditions in the Nisqually River Delta, WA, USA. The model indicated that prey-rich habitats such as emergent salt marshes and eelgrass meadows were most likely to facilitate growth, and that reductions in their areal extent and accessibility could have severe consequences for salmon. For instance, unmitigated sea-level rise halved the predicted extent of low- and high-elevation emergent salt marsh, leading to a 30% reduction in end-of-season weights. Increasing water temperatures compounded these effects during the late spring and summer such that the average daily growth rate of an individual fish decreased by an additional 5–50% when compared to the effects of sea-level rise alone. Lethal temperatures (> 24 °C) were infrequently observed, but they were more likely to occur during summer low tides in the mudflat and eelgrass habitats when accessibility to prey-rich marsh was minimal, thereby limiting foraging capacity and the availability of thermal refugia. Our findings indicate that, barring the enactment of targeted management strategies, rising tidal levels and increasing ocean temperatures may reduce the quality of the estuarine habitat mosaic for out-migrating salmon and other sensitive fish species.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-01003-3","usgsCitation":"Davis, M.J., Woo, I., Ellings, C.S., Hodgson, S., Beauchamp, D., Nakai, G., and De La Cruz, S.E., 2022, A climate-mediated shift in the estuarine habitat mosaic limits prey availability and reduces nursery quality for juvenile salmon: Estuaries and Coasts, v. 45, p. 1445-1464, https://doi.org/10.1007/s12237-021-01003-3.","productDescription":"20 p.","startPage":"1445","endPage":"1464","ipdsId":"IP-129415","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":397156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta, Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7385711669922,\n 47.06731569299121\n ],\n [\n -122.73273468017578,\n 47.067900315766245\n ],\n [\n -122.71350860595702,\n 47.06836800936954\n ],\n [\n -122.69496917724608,\n 47.07526601334617\n ],\n [\n -122.67488479614258,\n 47.08239690925263\n ],\n [\n -122.67454147338866,\n 47.11172875008271\n ],\n [\n -122.73822784423828,\n 47.11137826571562\n ],\n [\n -122.7385711669922,\n 47.06731569299121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgson, Sayre","contributorId":172121,"corporation":false,"usgs":false,"family":"Hodgson","given":"Sayre","email":"","affiliations":[{"id":26985,"text":"Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":838149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838151,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230233,"text":"70230233 - 2022 - Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","interactions":[],"lastModifiedDate":"2022-04-06T14:45:12.0395","indexId":"70230233","displayToPublicDate":"2022-03-16T09:52:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","docAbstract":"

Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m2) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (−0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to −0.022 °C per % cover, while tree canopy effects are reduced from −0.026 °C during the day to −0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.154589","usgsCitation":"Ibsen, P.C., Jenerette, G.D., Dell, T., Bagstad, K.J., and Diffendorfer, J., 2022, Urban landcover differentially drives day and nighttime air temperature across a semi-arid city: Science of the Total Environment, v. 829, 154589, 13 p., https://doi.org/10.1016/j.scitotenv.2022.154589.","productDescription":"154589, 13 p.","ipdsId":"IP-137333","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":448465,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.154589","text":"Publisher Index Page"},{"id":435921,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91IC3WM","text":"USGS data release","linkHelpText":"Urban landcover differentially drives day and nighttime air temperature across a semi-arid city"},{"id":398111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.23803710937499,\n 39.47860556892209\n ],\n [\n -104.69970703125,\n 39.47860556892209\n ],\n [\n -104.69970703125,\n 40.002371935876475\n ],\n [\n -105.23803710937499,\n 40.002371935876475\n ],\n [\n -105.23803710937499,\n 39.47860556892209\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenerette, G. Darrel 0000-0003-2387-7537","orcid":"https://orcid.org/0000-0003-2387-7537","contributorId":289689,"corporation":false,"usgs":false,"family":"Jenerette","given":"G.","email":"","middleInitial":"Darrel","affiliations":[{"id":13325,"text":"University of California Riverside","active":true,"usgs":false}],"preferred":false,"id":839619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dell, Tyler","contributorId":289690,"corporation":false,"usgs":false,"family":"Dell","given":"Tyler","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":839620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839622,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229727,"text":"70229727 - 2022 - Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","interactions":[],"lastModifiedDate":"2022-03-16T14:42:57.642502","indexId":"70229727","displayToPublicDate":"2022-03-16T09:29:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","docAbstract":"

Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120131","usgsCitation":"Xu, W., He, H.S., Huang, C., Duan, S., Hawbaker, T., Henne, P., Liang, Y., and Zhu, Z., 2022, Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?: Forest Ecology and Management, v. 510, p. 1-10, https://doi.org/10.1016/j.foreco.2022.120131.","productDescription":"120131, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-130289","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":448469,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120131","text":"Publisher Index Page"},{"id":435923,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YREDMC","text":"USGS data 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Wenru","contributorId":245141,"corporation":false,"usgs":false,"family":"Xu","given":"Wenru","affiliations":[{"id":39904,"text":"University of Missouri, School of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"He, Hong S.","contributorId":257944,"corporation":false,"usgs":false,"family":"He","given":"Hong","email":"","middleInitial":"S.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":838110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Chao","contributorId":211611,"corporation":false,"usgs":false,"family":"Huang","given":"Chao","email":"","affiliations":[{"id":38274,"text":"Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China","active":true,"usgs":false}],"preferred":true,"id":838111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duan, Shengwu","contributorId":242925,"corporation":false,"usgs":false,"family":"Duan","given":"Shengwu","email":"","affiliations":[{"id":36845,"text":"School of Natural Resources, University of Missouri","active":true,"usgs":false}],"preferred":false,"id":838112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liang, Yu","contributorId":145642,"corporation":false,"usgs":false,"family":"Liang","given":"Yu","affiliations":[],"preferred":false,"id":838115,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use 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The single-station microtremor horizontal-to-vertical spectral ratio (MHVSR) method was initially proposed to retrieve the site amplification function and its resonance frequencies produced by unconsolidated sediments overlying high-velocity bedrock. Presently, MHVSR measurements are predominantly conducted to obtain an estimate of the fundamental site frequency at sites where a strong subsurface impedance contrast exists. Of the earthquake site characterization methods presented in this special issue, the MHVSR method is the furthest behind in terms of consensus towards standardized guidelines and commercial use. The greatest challenges to an international standardization of MHVSR acquisition and analysis are (1) the what — the underlying composition of the microtremor wavefield is site-dependent, and thus, the appropriate theoretical (forward) model for inversion is still debated; and (2) the how — many factors and options are involved in the data acquisition, processing, and interpretation stages. This paper reviews briefly a historical development of the MHVSR technique and the physical basis of an MHVSR (the what). We then summarize recommendations for MHVSR acquisition and analysis (the how). Specific sections address MHVSR interpretation and uncertainty assessment.

","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10062-9","usgsCitation":"Molnar, S., Sirohey, A., Assaf, J., Bard, P., Castellaro, C., Cornou, C., Cox, B., Guillier, B., Hassani, B., Kawase, H., Matsushima, S., Sánchez-Sesma, F., and Yong, A., 2022, A review of the microtremor horizontal-to-vertical spectral ratio (MHVSR) method: Journal of Seismology, v. 26, p. 653-685, https://doi.org/10.1007/s10950-021-10062-9.","productDescription":"33 p.","startPage":"653","endPage":"685","ipdsId":"IP-127918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10062-9","text":"Publisher Index Page"},{"id":406138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Molnar, S.","contributorId":203574,"corporation":false,"usgs":false,"family":"Molnar","given":"S.","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":850685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sirohey, A.","contributorId":296125,"corporation":false,"usgs":false,"family":"Sirohey","given":"A.","email":"","affiliations":[],"preferred":false,"id":850686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assaf, J.","contributorId":296126,"corporation":false,"usgs":false,"family":"Assaf","given":"J.","email":"","affiliations":[],"preferred":false,"id":850708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bard, P.-Y.","contributorId":296110,"corporation":false,"usgs":false,"family":"Bard","given":"P.-Y.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castellaro, C.","contributorId":296111,"corporation":false,"usgs":false,"family":"Castellaro","given":"C.","email":"","affiliations":[{"id":63993,"text":"Alma Mater Studiorum Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":850688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cornou, C.","contributorId":296112,"corporation":false,"usgs":false,"family":"Cornou","given":"C.","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cox, B.","contributorId":296113,"corporation":false,"usgs":false,"family":"Cox","given":"B.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":850690,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guillier, B.","contributorId":296114,"corporation":false,"usgs":false,"family":"Guillier","given":"B.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hassani, B.","contributorId":296115,"corporation":false,"usgs":false,"family":"Hassani","given":"B.","email":"","affiliations":[{"id":37568,"text":"BC Hydro","active":true,"usgs":false}],"preferred":false,"id":850692,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kawase, H.","contributorId":296116,"corporation":false,"usgs":false,"family":"Kawase","given":"H.","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850693,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Matsushima, S.","contributorId":296117,"corporation":false,"usgs":false,"family":"Matsushima","given":"S.","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850694,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sánchez-Sesma, F. J.","contributorId":296118,"corporation":false,"usgs":false,"family":"Sánchez-Sesma","given":"F. J.","affiliations":[{"id":25354,"text":"Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":850695,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850696,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70236346,"text":"70236346 - 2022 - A review of near-surface QS estimation methods using active and passive sources","interactions":[],"lastModifiedDate":"2022-09-02T14:12:47.588487","indexId":"70236346","displayToPublicDate":"2022-03-16T09:10:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A review of near-surface QS estimation methods using active and passive sources","title":"A review of near-surface QS estimation methods using active and passive sources","docAbstract":"

Seismic attenuation and the associated quality factor (Q) have long been studied in various sub-disciplines of seismology, ranging from observational and engineering seismology to near-surface geophysics and soil/rock dynamics with particular emphasis on geotechnical earthquake engineering and engineering seismology. Within the broader framework of seismic site characterization, various experimental techniques have been adopted over the years to measure the near-surface shear-wave quality factor (QS). Common methods include active- and passive-source recording techniques performed at the free surface of soil deposits and within boreholes, as well as laboratory tests. This paper intends to provide an in-depth review of what Q is and, in particular, how QS is estimated in the current practice. After motivating the importance of this parameter in seismology, we proceed by recalling various theoretical definitions of Q and its measurement through laboratory tests, considering various deformation modes, most notably QP and QS. We next provide a review of the literature on QS estimation methods that use data from surface and borehole sensor recordings. We distinguish between active- and passive-source approaches, along with their pros and cons, as well as the state-of-the-practice and state-of-the-art. Finally, we summarize the phenomena associated with the high-frequency shear-wave attenuation factor (kappa) and its relation to Q, as well as other lesser-known attenuation parameters.

","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10066-5","usgsCitation":"Parolai, S., Lai, C.G., Dreossi, I., Ktenidou, O., and Yong, A., 2022, A review of near-surface QS estimation methods using active and passive sources: Journal of Seismology, v. 26, p. 823-862, https://doi.org/10.1007/s10950-021-10066-5.","productDescription":"40 p.","startPage":"823","endPage":"862","ipdsId":"IP-132752","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10066-5","text":"Publisher Index Page"},{"id":406135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Parolai, Stefano 0000-0002-9084-7488","orcid":"https://orcid.org/0000-0002-9084-7488","contributorId":296105,"corporation":false,"usgs":false,"family":"Parolai","given":"Stefano","email":"","affiliations":[{"id":63989,"text":"Instituto Nazionale di Oceonografia","active":true,"usgs":false}],"preferred":false,"id":850680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lai, Carlo G.","contributorId":296106,"corporation":false,"usgs":false,"family":"Lai","given":"Carlo","email":"","middleInitial":"G.","affiliations":[{"id":63990,"text":"Department of Civil and Architectural Engineering, University of Pavia, Pavia, Italy","active":true,"usgs":false}],"preferred":false,"id":850681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreossi, Ilaria","contributorId":296107,"corporation":false,"usgs":false,"family":"Dreossi","given":"Ilaria","email":"","affiliations":[{"id":63991,"text":"National Institute of Oceanography and Applied Geophysics – OGS, Udine, Italy","active":true,"usgs":false}],"preferred":false,"id":850682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ktenidou, Olga-Joan","contributorId":271026,"corporation":false,"usgs":false,"family":"Ktenidou","given":"Olga-Joan","email":"","affiliations":[{"id":56255,"text":"National Observatory of Athens","active":true,"usgs":false}],"preferred":false,"id":850683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yong, Alan K. 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":296108,"corporation":false,"usgs":true,"family":"Yong","given":"Alan K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850684,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230023,"text":"70230023 - 2022 - Modeling the dynamics of salt marsh development in coastal land reclamation","interactions":[],"lastModifiedDate":"2022-03-24T14:12:06.779505","indexId":"70230023","displayToPublicDate":"2022-03-16T08:55:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the dynamics of salt marsh development in coastal land reclamation","docAbstract":"The valuable ecosystem services of salt marshes are spurring marsh restoration projects around the world. However, it is difficult to determine the final vegetated area based on physical drivers. Herein, we use a 3D fully coupled vegetation-hydrodynamic-morphological modeling system (COAWST), to simulate the final vegetation cover and the timescale to reach it under various forcing conditions. Marsh development in our simulations can be divided in three distinctive phases: a preparation phase characterized by sediment accumulation in the absence of vegetation, an encroachment phase in which the vegetated area grows, and an adjustment phase in which the vegetated area remains relatively constant while marsh accretes vertically to compensate for sea level rise. Sediment concentration, settling velocity, sea level rise and tidal range each comparably affect equilibrium coverage and timescale in different ways. Our simulations show that the Unvegetated-Vegetated Ratio (UVVR) also relates to sediment budget in marsh development under most conditions.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL095559","usgsCitation":"Xu, Y., Kalra, T., Ganju, N., and Fagherazzi, S., 2022, Modeling the dynamics of salt marsh development in coastal land reclamation: Geophysical Research Letters, v. 49, no. 6, e2021GL095559, 11 p., https://doi.org/10.1029/2021GL095559.","productDescription":"e2021GL095559, 11 p.","ipdsId":"IP-131905","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448480,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gl095559","text":"External Repository"},{"id":397522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Yiyang","contributorId":289206,"corporation":false,"usgs":false,"family":"Xu","given":"Yiyang","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":838716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":838781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":838718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagherazzi, Sergio","contributorId":207153,"corporation":false,"usgs":false,"family":"Fagherazzi","given":"Sergio","email":"","affiliations":[{"id":37465,"text":"Boston University, Earth and Environment, Boston, 02215, USA.","active":true,"usgs":false}],"preferred":false,"id":838719,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231194,"text":"70231194 - 2022 - Influence of offshore oil and gas structures on seascape ecological connectivity","interactions":[],"lastModifiedDate":"2022-05-03T12:12:50.95425","indexId":"70231194","displayToPublicDate":"2022-03-16T07:10:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of offshore oil and gas structures on seascape ecological connectivity","docAbstract":"

Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16134","usgsCitation":"McLean, D.L., Ferreira, L.C., Benthuysen, J.A., Miller, K.J., Schlappy, M., Ajemian, M.J., Berry, O., Birchenough, S.N., Bond, T., Boschetti, F., Bull, A.S., Claisse, J.T., Condie, S.A., Consoli, P., Coolen, J.W., Elliott, M.R., Fortune, I.S., Fowler, A.M., Gillanders, B.M., Harrison, H.B., Hart, K., Henry, L., Hewitt, C.L., Hicks, N., Hock, K., Hyder, K., Love, M.S., Macreadie, P., Miller, R.J., Montevecchi, W.A., Nishimoto, M., Page, H.M., Paterson, D.M., Pattiaratchi, C.B., Pecl, G.T., Porter, J.S., Reeves, D.B., Riginos, C., Rouse, S., Russell, D.J., Sherman, C.D., Teilmann, J., Todd, V.L., Treml, E.A., Williamson, D.H., and Thums, M., 2022, Influence of offshore oil and gas structures on seascape ecological connectivity: Global Change Biology, v. 28, no. 11, p. 3515-3536, https://doi.org/10.1111/gcb.16134.","productDescription":"22 p.","startPage":"3515","endPage":"3536","ipdsId":"IP-132328","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448486,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16134","text":"External Repository"},{"id":400033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Dianne L","contributorId":291260,"corporation":false,"usgs":false,"family":"McLean","given":"Dianne","email":"","middleInitial":"L","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":841923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferreira, Luciana C.","contributorId":222287,"corporation":false,"usgs":false,"family":"Ferreira","given":"Luciana","email":"","middleInitial":"C.","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":841924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benthuysen, Jessica A","contributorId":291261,"corporation":false,"usgs":false,"family":"Benthuysen","given":"Jessica","email":"","middleInitial":"A","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":841925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Karen J.","contributorId":201446,"corporation":false,"usgs":false,"family":"Miller","given":"Karen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":841926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schlappy, Marie-Lise","contributorId":291262,"corporation":false,"usgs":false,"family":"Schlappy","given":"Marie-Lise","email":"","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":841927,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ajemian, Matthew J.","contributorId":177080,"corporation":false,"usgs":false,"family":"Ajemian","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":841928,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Berry, Oliver","contributorId":291263,"corporation":false,"usgs":false,"family":"Berry","given":"Oliver","email":"","affiliations":[{"id":62643,"text":"CSIRO Environomics Future Science Platform","active":true,"usgs":false}],"preferred":false,"id":841929,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birchenough, Silvana N. 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  1. The increasing complexity and pace of ecological change requires natural resource managers to consider entire species assemblages. Acoustic recording units (ARUs) require minimal cost and effort to deploy and inform relative activity, or encounter rates, for multiple species simultaneously. ARU-based surveys require post-processing of the recordings via software algorithms that assign a species label to each recording. The automated classification process can result in cross-species misidentifications that should be accounted for when employing statistical modelling for conservation decision-making.
  2. Using simulation and ARU-based detection counts from 17 bat species in British Columbia, Canada, we investigate three strategies for adjusting statistical inference for species misclassification: (a) ‘coupling’ ambiguous and unambiguous detections by validating a subset of survey events post-hoc, (b) using a calibration dataset on the software algorithm's (in)accuracy for species identification or (c) specifying informative Bayesian priors on classification probabilities. We explore the impact of different Bayesian prior specifications for the classification probabilities on posterior estimation. We then consider how the quantity of data validated post-hoc impacts model convergence and resulting inferences for bat species relative activity as related to nightly conditions and yearly site occupancy after accounting for site-level environmental variables.
  3. Coupled methods resulted in less bias and uncertainty when estimating relative activity and species classification probabilities relative to calibration approaches. We found that species that were difficult-to-detect and those that were often inaccurately identified by the software required more validation effort than more easily detected and/or identified species.
  4. Our results suggest that, when possible, acoustic surveys should rely on coupled validated detection information to account for false-positive detections, rather than uncoupled calibration datasets. However, if the assemblage of interest contains a large number of rarely detected or less prevalent species, an intractable amount of effort may be required, suggesting there are benefits to curating a calibration dataset that is representative of the observation process. Our findings provide insights into the practical challenges associated with statistical analyses of ARU data and possible analytical solutions to support reliable and cost-effective decision-making for wildlife conservation/management in the face of known sources of observation errors.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13831","usgsCitation":"Stratton, C., Irvine, K., Banner, K., Wright, W.J., Lausen, C., and Rae, J., 2022, Coupling validation effort with in situ bioacoustic data improves estimating relative activity and occupancy for multiple species with cross-species misclassifications: Methods in Ecology and Evolution, v. 13, no. 6, p. 1288-1303, https://doi.org/10.1111/2041-210X.13831.","productDescription":"16 p.","startPage":"1288","endPage":"1303","ipdsId":"IP-135078","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":448489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13831","text":"Publisher Index Page"},{"id":403590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -139.21874999999997,\n 60.28340847828243\n ],\n [\n -138.427734375,\n 59.31076795603884\n ],\n [\n -137.373046875,\n 58.6769376725869\n ],\n [\n -135.791015625,\n 59.085738569819505\n ],\n [\n -134.560546875,\n 58.6769376725869\n ],\n [\n -132.802734375,\n 56.26776108757582\n ],\n [\n -132.099609375,\n 54.826007999094955\n ],\n [\n -132.1875,\n 53.27835301753182\n ],\n [\n -131.396484375,\n 51.781435604431195\n ],\n [\n -128.935546875,\n 50.401515322782366\n ],\n [\n -126.38671874999999,\n 48.80686346108517\n ],\n [\n -122.87109375,\n 47.989921667414194\n ],\n [\n -122.87109375,\n 49.210420445650286\n ],\n [\n -114.345703125,\n 49.03786794532644\n ],\n [\n -114.873046875,\n 50.62507306341435\n ],\n [\n -119.794921875,\n 53.85252660044951\n ],\n [\n -119.70703125,\n 59.977005492196\n ],\n [\n -139.21874999999997,\n 60.28340847828243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":846463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":293129,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":846464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banner, Katharine M.","contributorId":244876,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":846465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Wilson J.","contributorId":192867,"corporation":false,"usgs":false,"family":"Wright","given":"Wilson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":846466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lausen, Cori","contributorId":204261,"corporation":false,"usgs":false,"family":"Lausen","given":"Cori","affiliations":[{"id":36893,"text":"Wildlife Conservation Society Canada","active":true,"usgs":false}],"preferred":false,"id":846467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rae, Jason","contributorId":241643,"corporation":false,"usgs":false,"family":"Rae","given":"Jason","email":"","affiliations":[{"id":36893,"text":"Wildlife Conservation Society Canada","active":true,"usgs":false}],"preferred":false,"id":846468,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229688,"text":"70229688 - 2022 - Precision of headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA","interactions":[],"lastModifiedDate":"2023-11-08T16:38:37.80856","indexId":"70229688","displayToPublicDate":"2022-03-15T08:58:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Precision of headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA","docAbstract":"

Stream permanence classifications (i.e., perennial, intermittent, ephemeral) are a primary consideration to determine stream regulatory status in the United States (U.S.) and are an important indicator of environmental conditions and biodiversity. However, at present, no models or products adequately describe surface water presence for regulatory determinations. We modified the Thornthwaite monthly water balance model (MWBM) with a flow threshold parameter to estimate flow permanence and evaluated the model’s accuracy and precision for more than 1.3 million headwater stream reaches in the U.S. Pacific Northwest (PNW). Stream reaches were assigned to one of eight calibration groups by unsupervised classification based on sensitivity to MWBM parameters. Suitable MWBM parameter sets were identified by comparing modeled stream permanence estimates to surface water presence observations (SWPO). Parameter sets with accuracies > 65% were considered suitable. The MWBM estimated stream permanence with high precision at 40% of reaches, with poor precision at 20% of reaches, and no suitable parameter sets were identified for 40% of reaches. Results highlight the need for increased SWPO collection to improve calibration and assessment of stream permanence models. Additionally, implementation of the MWBM to estimate surface water presence indicates potential for process-based models to predict stream permanence with future development.

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Center","active":false,"usgs":true}],"preferred":true,"id":837965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rea, Alan H. 0000-0002-0406-9596 ahrea@usgs.gov","orcid":"https://orcid.org/0000-0002-0406-9596","contributorId":206357,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","email":"ahrea@usgs.gov","middleInitial":"H.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":837966,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230900,"text":"70230900 - 2022 - Forest cover lessens the impact of drought on streamflow in Puerto Rico","interactions":[],"lastModifiedDate":"2022-05-13T15:20:23.133171","indexId":"70230900","displayToPublicDate":"2022-03-15T08:56:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Forest cover lessens the impact of drought on streamflow in Puerto Rico","docAbstract":"

Tropical regions are experiencing high rates of forest cover loss coupled with changes in the volume and timing of rainfall. These shifts can compromise streamflow and water provision, highlighting the need to identify how forest cover influences streamflow generation under variable rainfall conditions. Although rainfall is the key driver of streamflow regimes, the role of forests is less clear, particularly in tropical regions where forest loss is an ongoing risk. Forest cover loss alters evapotranspiration, rainfall infiltration and storage, and may increase stream ecosystem vulnerability to rainfall extremes. Puerto Rico, an island with spatially heterogenous forest cover and a marked geographic rainfall gradient, is projected to experience more frequent droughts and flash flooding. Using 15-minute streamflow data collected between 2005 and 2016 from 20 USGS stream gages and 3-hourly Multi-Source Weighted-Ensemble Precipitation rainfall estimates, we utilized flow-duration curves and linear mixed regression models to examine the role of forest cover in regulating the timing and volume of streamflow. The mixed model approach helps to account for differences in watershed characteristics. We determined the effects of rainfall and forest cover on low and peak flows in Puerto Rican streams, then evaluated changes in these relationships under dry and wet antecedent rainfall conditions. Watersheds with high forest cover had consistently greater low and peak streamflow than deforested ones under all rainfall conditions, although the effect was more marked during wet antecedent conditions, suggesting that peak flow is largely the result of saturation excess overland flow. During dry antecedent rainfall conditions, highly forested watersheds had higher streamflow than deforested ones, suggesting greater hillslope storage and release may also be at play. Our results demonstrate that forest cover generated a net increase in hillslope infiltration and storage and may lessen drought impacts on streamflow in Puerto Rico. Resilience to prolonged drought may be limited by finite water storage potential in this steep, mountainous setting, highlighting maintenance of forest cover as an important water management strategy to increase infiltration.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14551","usgsCitation":"Hall, J.S., Scholl, M.A., Gorokhovich, Y., and Uriarte, M., 2022, Forest cover lessens the impact of drought on streamflow in Puerto Rico: Hydrological Processes, v. 36, no. 5, e14551, 16 p., https://doi.org/10.1002/hyp.14551.","productDescription":"e14551, 16 p.","ipdsId":"IP-122081","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":399811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto 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Yuri","contributorId":290689,"corporation":false,"usgs":false,"family":"Gorokhovich","given":"Yuri","email":"","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":841587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uriarte, Maria","contributorId":287019,"corporation":false,"usgs":false,"family":"Uriarte","given":"Maria","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":841588,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255076,"text":"70255076 - 2022 - Carnivores in color: Pelt color patterns among carnivores in Idaho","interactions":[],"lastModifiedDate":"2024-06-13T11:15:44.724402","indexId":"70255076","displayToPublicDate":"2022-03-15T06:12:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Carnivores in color: Pelt color patterns among carnivores in Idaho","docAbstract":"

Pelt color serves many functions from signaling to crypsis to thermoregulation and its purpose has been a lively source of debate in biology for over a century. Determining the effects of both habitat and human influences on pelt color patterns can be difficult. We made novel use of a multispecies occupancy model by defining “pelt color” as “species.” We then used this model to test predictions and estimate pelt color patterns concurrently for three carnivore species in Idaho, United States. We predicted pelt patterns of all three carnivores would be affected by environmental variables as well as human disturbance. Areas of Idaho where baiting was allowed and preferential harvest possible did not explain pelt patterns in black bears and neither did forest cover. Road density was positively associated with detection probability but negatively associated with occupancy of both black and brown pelt bears, however. Gray pelt wolves were found more often in areas with higher road densities than black wolves. As predicted, black, but not gray, wolves were positively associated with forest cover. Both red and black pelt foxes were positively associated with increasing elevation and road density. Black pelt foxes were negatively associated with forest cover, mirroring the habitat use described for native black pelt foxes. We demonstrate how using noninvasively collected data and extending multispecies occupancy models can allow biologists to study the distribution of different pelt colors in wild populations.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyab166","usgsCitation":"Ausband, D.E., and Krohner, J.M., 2022, Carnivores in color: Pelt color patterns among carnivores in Idaho: Journal of Mammalogy, v. 103, no. 3, p. 598-607, https://doi.org/10.1093/jmammal/gyab166.","productDescription":"10 p.","startPage":"598","endPage":"607","ipdsId":"IP-130703","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab166","text":"Publisher Index Page"},{"id":430060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"103","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krohner, Jessica M.","contributorId":338521,"corporation":false,"usgs":false,"family":"Krohner","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":903327,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229658,"text":"sir20225013 - 2022 - Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","interactions":[],"lastModifiedDate":"2026-04-08T17:28:23.084393","indexId":"sir20225013","displayToPublicDate":"2022-03-14T11:12:51","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5013","displayTitle":"Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970–2020","title":"Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","docAbstract":"

The Heart River Basin is predominantly an agricultural basin in western North Dakota and is approximately 3,350 square miles. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and the Grant County Soil Conservation District, completed a study to assess spatial and temporal patterns of water quality in the Heart River Basin. The purpose of this report is to describe the methods and results of a study to evaluate salinity and nutrients in the Heart River Basin in western North Dakota. Water-quality and streamflow data used in the study were compiled from 1970 to 2020 using the National Water Quality Monitoring Council Water Quality Portal and National Water Information System.

Changes in streamflow characteristics were investigated at three sites from 1970 to 2020, and changes in water quality were investigated at four sites from 1974 to 2019. Streamflow analysis indicated decreasing streamflow from 1970 until the late 1990s followed by increasing streamflow through 2020, with the largest increase in the 7-day minimum streamflow or base flow. For the historical water-quality trend period (1974–2019), total dissolved solids, sulfate, sodium, chloride, and sodium adsorption ratio concentrations have increased since the mid-1970s through 2019. Potassium concentrations during the historical period remained mostly constant with some small fluctuations. Calcium and magnesium concentrations increased since the mid-1970s at all sites, except for a decrease at one site between 1974 and 1999. During the recent trend period (1999–2019), increasing concentrations in total dissolved solids, sulfate, sodium, chloride, calcium, magnesium, and sodium adsorption ratios were observed across the Heart River Basin. The magnitude of the increases was smaller at tributary sites compared to main-stem sites. During the recent period, potassium was mostly constant, although small (−0.9 milligram per liter or less) decreases on tributaries and minor (1.3 milligrams per liter) increases on the main-stem sites were detected. Unlike dissolved ion concentrations, significant increases in nutrient concentrations were not detected from 1999 to 2019, but nitrate plus nitrite concentrations most likely decreased upstream from Lake Tschida.

Inverse modeling for period 1 (1974–99) in model zone 1 (Heart River reach from site 5 to site 6) had eight reasonable models that indicated the clay mineral-water interactions and dissolution of evaporites control the geochemistry. Results of the inverse modeling for period 2 (1999–2019) in model zone 1 also had eight reasonable models that indicated that the dissolution of evaporites was the major geochemical control. Results of the geochemical modeling for period 1 (1974–99) in model zone 2 (Heart River and Sweetbriar Creek reach from sites 20 and 21 to site 22) produced seven reasonable models, and the geochemical control of the system was the dissolution of sulfate evaporite minerals. Geochemical modeling results for period 2 (1999–2019) in model zone 2 produced 11 reasonable models and was also controlled by the dissolution of sulfate evaporite minerals. Differences between the two model zones indicated that geology controls some of the water-quality changes in the Heart River Basin.

Loads were estimated for total dissolved solids, sulfate, sodium, and chloride and total phosphorus. Annual loads estimated for the Heart River from 2013 through 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) were generally greatest in 2014 and least in 2016 for total dissolved solids, sulfate, sodium, and chloride. Most of the annual loads of total dissolved solids, sulfate, sodium, and chloride are delivered in March through July in the Heart River at these sites and are likely from snowmelt and spring and summer rains. The mean annual yields of total dissolved solids and sodium from 2013 to 2020 generally were largest in Big Muddy Creek (site 18), whereas yields of sulfate and chloride were largest at Sweetbriar Creek (site 21) compared to the other selected sites in the Heart River Basin. Larger yields of total dissolved solids, sulfate, sodium, and chloride at sites located on Big Muddy Creek and Sweet Briar Creek in the lower Heart River Basin were likely a result of differences in geology and soils upstream from the selected sites.

A mass balance of total dissolved solids, sulfate, sodium, and chloride was estimated for the lower Heart River Basin, specifically the reach below Lake Tschida to Mandan (site 7 to site 22). Intervening flow was the largest contributor to the dissolved ion loads in the lower Heart River Basin and is an important part of understanding the transport of dissolved ions in the basin. The intervening load can include groundwater discharge, irrigation return flow, local runoff, and input from smaller ephemeral tributaries. Tributaries in the lower Heart River Basin contributed portions of the total dissolved solids, sulfate, sodium, and chloride loads at the Heart River near Mandan (site 22) that generally were proportional to the streamflow contributions.

Annual loads for total phosphorus between 2013 and 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) generally were largest in 2019 and smallest in 2016. Most of the total phosphorus loads for main-stem sites 5 and 22 were transported in March, April, and June, likely from snowmelt and early summer rains. The mean annual yields of total phosphorus for 2013–20 were largest on the main-stem site upstream from Lake Tschida (site 5) and Sweetbriar Creek (site 21), whereas the smallest yields were in Big Muddy Creek (site 18). Much of the phosphorus that enters Lake Tschida from the upper basin does not get transported downstream to the lower basin, and much of the phosphorus in the lower basin was attributed to intervening flow.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225013","collaboration":"Prepared in cooperation with the Department of Agriculture Natural Resources Conservation Service and Grant County Soil Conservation District","usgsCitation":"Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2022, Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5013, 76 p., https://doi.org/10.3133/sir20225013.","productDescription":"Report: ix, 76; Data Release; Dataset","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-131163","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":397042,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397041,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P987APZ8","text":"USGS data release","linkHelpText":"Data and scripts used in water-quality trend and load analysis in the Heart River Basin, North Dakota, 1970–2020"},{"id":502299,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112690.htm","linkFileType":{"id":5,"text":"html"}},{"id":398527,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225013/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397040,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5013/images"},{"id":397039,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.XML"},{"id":397038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.pdf","text":"Report","size":"21.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5013"},{"id":397037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5013/coverthb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Heart River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.2769775390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 46.27863122156088\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-03-14","noUsgsAuthors":false,"publicationDate":"2022-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837840,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229660,"text":"70229660 - 2022 - Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights","interactions":[],"lastModifiedDate":"2022-03-14T13:57:19.916542","indexId":"70229660","displayToPublicDate":"2022-03-14T08:44:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights","docAbstract":"

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (&lt;\"><50 m) and wind conditions are known at facility scale (&lt;\"><3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio &gt;\">>1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.109876","usgsCitation":"Sandhu, R., Tripp, C., Quon, E., Thedin, R., Lawson, M., Brandes, D., Farmer, C., Miller, T.A., Draxl, C., Doubrawa, P., Williams, L., Duerr, A.E., Braham, M., and Katzner, T., 2022, Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights: Ecological Modelling, v. 466, p. 1-12, https://doi.org/10.1016/j.ecolmodel.2022.109876.","productDescription":"109876, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-132310","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":467190,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1845670","text":"Publisher Index Page"},{"id":397056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Paula","contributorId":288414,"corporation":false,"usgs":false,"family":"Doubrawa","given":"Paula","email":"","affiliations":[{"id":33782,"text":"National Renewable Energy Laboratory","active":true,"usgs":false}],"preferred":false,"id":837859,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Williams, Lindy","contributorId":288415,"corporation":false,"usgs":false,"family":"Williams","given":"Lindy","email":"","affiliations":[{"id":33782,"text":"National Renewable Energy Laboratory","active":true,"usgs":false}],"preferred":false,"id":837860,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":837861,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Braham, Melissa A.","contributorId":140127,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":837862,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837854,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70229663,"text":"70229663 - 2022 - Quantifying large-scale continental shelf margin growth and dynamics across mid-Cretaceous Arctic Alaska with detrital zircon U-Pb dating","interactions":[],"lastModifiedDate":"2022-04-26T12:10:04.272603","indexId":"70229663","displayToPublicDate":"2022-03-14T08:12:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying large-scale continental shelf margin growth and dynamics across mid-Cretaceous Arctic Alaska with detrital zircon U-Pb dating","docAbstract":"

Sequence stratigraphy provides a unifying framework for integrating diverse observations to interpret sedimentary basin evolution; however, key time assumptions about stratigraphic elements spanning hundreds of kilometers are rarely quantified. We integrate new detrital zircon U-Pb (DZ) dates from 28 samples with seismic mapping to establish a chronostratigraphic framework across 800 km and ~20 m.y. for the middle-Cretaceous Torok-Nanushuk clinothem of Arctic Alaska (USA). Shelf-margin DZ dates indicate continent-scale sediment routing with Russian Chukotka provenance and provide reliable maximum depositional ages derived from arc volcanism. Shelf-margin advance rates display a clear relationship to toplap trajectories and provide empirical support for long-held inferences linking sediment supply to margin architecture. Two distinct shelf-margin growth regimes are evident: (1) a ca. 115–107 Ma phase of rapid ~50 km/m.y. shelf advance rates with mainly progradational trajectories; and (2) a ca. 107–98 Ma phase of moderate ~13 km/m.y. shelf advance rates with progradational-retrogradational-aggradational trajectories. We established a subsequent shelf–to–deep water correlation by independently dating ca. 98–95 Ma low shelf accommodation and basin-floor deposition as far as 240 km east that indicate lowstand shedding and a change to localized routing with Brooks Range provenance. Finally, we dated a ca. 95 Ma basin-wide transgression at deep-water to shelfal settings across 350 km that exhibits apparent synchroneity consistent with an event-significant surface. In one of the world’s largest foreland-basin clinothems, our work constrains the timing and duration of key depositional elements to test large-scale sequence stratigraphic assumptions, enables reliable correlation and quantification of sediment dynamics across 800 km, and captures the chronology of a giant regressive-transgressive cycle.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49118.1","usgsCitation":"Lease, R.O., Houseknecht, D.W., and Kylander-Clark, A.R., 2022, Quantifying large-scale continental shelf margin growth and dynamics across mid-Cretaceous Arctic Alaska with detrital zircon U-Pb dating: Geology, v. 50, no. 5, p. 620-625, https://doi.org/10.1130/G49118.1.","productDescription":"6 p.","startPage":"620","endPage":"625","ipdsId":"IP-135413","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":448513,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g49118.1","text":"Publisher Index Page"},{"id":435927,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8BHTN","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Detrital Zircon and Volcanic Zircon Grains from the Torok and Nanushuk Formations, Arctic Alaska, 2021"},{"id":397055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.99853515625,\n 69.65708627301174\n ],\n [\n -139.81201171874997,\n 73.23937702441908\n ],\n [\n -162.59765625,\n 73.02900629225599\n ],\n [\n -169.8046875,\n 69.17037257214531\n ],\n [\n -163.828125,\n 67.05887024878373\n ],\n [\n -160.6640625,\n 67.30597574414466\n ],\n [\n -157.58789062499997,\n 67.04173496919447\n ],\n [\n -154.95117187499997,\n 66.93866882358137\n ],\n [\n -151.7431640625,\n 67.12729044909526\n ],\n [\n -147.3046875,\n 67.53377157140451\n ],\n [\n -145.1513671875,\n 68.46379955520322\n ],\n [\n -141.0205078125,\n 68.86351700272681\n ],\n [\n -140.99853515625,\n 69.65708627301174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":837863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kylander-Clark, Andrew R. C.","contributorId":212897,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","email":"","middleInitial":"R. C.","affiliations":[],"preferred":false,"id":837865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248934,"text":"70248934 - 2022 - A physical interpretation of asymmetric growth and decay of the geomagnetic dipole moment","interactions":[],"lastModifiedDate":"2023-09-27T12:25:01.645868","indexId":"70248934","displayToPublicDate":"2022-03-14T07:24:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"A physical interpretation of asymmetric growth and decay of the geomagnetic dipole moment","docAbstract":"

Observations of relative paleointensity reveal several forms of asymmetry in the time dependence of the virtual axial dipole moment (VADM). Slow decline of the VADM into a reversal is often followed by a more rapid rise back to a quasi-steady state. Asymmetry is also observed in trends of VADM during times of stable polarity. Trends of increasing VADM over time intervals of a few 10s of kyr are more intense and less frequent than decreasing trends. We examine the origin of this behavior using stochastic models. The usual (Langevin) model can account for asymmetries during reversals, but it cannot reproduce the observed asymmetry in trends during stable polarity. Better agreement is achieved with a different class of stochastic models in which the dipole is generated by a series of impulsive events in time. The timing of each event occurs randomly as a Poisson process and the amplitude is also randomly distributed. Predicted trends replicate the observed asymmetry when the generation events are large and the recurrence time is long (typically longer than 3 kyr). Large and infrequent generation events argue against dipole generation by small-scale turbulent flow. Instead, the observations favor a mechanism that relies on expulsion of poloidal magnetic field from the core.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC010239","usgsCitation":"Buffett, B., Avery, M.S., and Davis, W.E., 2022, A physical interpretation of asymmetric growth and decay of the geomagnetic dipole moment: Geochemistry, Geophysics, Geosystems, v. 23, no. 3, e2021GC010239, 18 p., https://doi.org/10.1029/2021GC010239.","productDescription":"e2021GC010239, 18 p.","ipdsId":"IP-135077","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":448515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gc010239","text":"Publisher Index Page"},{"id":421250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Buffett, Bruce 0000-0001-5488-7602","orcid":"https://orcid.org/0000-0001-5488-7602","contributorId":330183,"corporation":false,"usgs":false,"family":"Buffett","given":"Bruce","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":884268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avery, Margaret Susan 0000-0002-8504-7072","orcid":"https://orcid.org/0000-0002-8504-7072","contributorId":329991,"corporation":false,"usgs":true,"family":"Avery","given":"Margaret","email":"","middleInitial":"Susan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, William E. Jr.","contributorId":113000,"corporation":false,"usgs":false,"family":"Davis","given":"William","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":884270,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231658,"text":"70231658 - 2022 - Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks","interactions":[],"lastModifiedDate":"2022-05-19T12:19:15.49705","indexId":"70231658","displayToPublicDate":"2022-03-14T07:16:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks","docAbstract":"

Despite tectonic conditions and atmospheric CO2 levels (pCO2) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO2 radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO2. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO2 forcing.

","language":"English","publisher":"Nature","doi":"10.1038/s41467-022-28814-7","usgsCitation":"Feng, R., Bhattacharya, T., Otto-Bliesner, B., Brady, E., Haywood, A.M., Tindall, J., Hunter, S.J., Abe- Ouchi, A., Chan, W., Kageyama, M., Contoux, C., Guo, C., Li, X., Lohmann, G., Stepanek, C., Tan, N., Zhang, Q., Zhang, Z., Han, Z., Williams, J., Lunt, D.J., Dowsett, H., Chandan, D., and Peltier, W.R., 2022, Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks: Nature Communications, v. 13, 1306, 11 p., https://doi.org/10.1038/s41467-022-28814-7.","productDescription":"1306, 11 p.","ipdsId":"IP-129724","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":448517,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-022-28814-7","text":"Publisher Index Page"},{"id":400802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2022-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Feng, R.","contributorId":291865,"corporation":false,"usgs":false,"family":"Feng","given":"R.","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":843261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhattacharya, T.","contributorId":291866,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":843262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otto-Bliesner, B.","contributorId":291867,"corporation":false,"usgs":false,"family":"Otto-Bliesner","given":"B.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":843263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, E.","contributorId":291870,"corporation":false,"usgs":false,"family":"Brady","given":"E.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":843264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haywood, A. 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J.","contributorId":192915,"corporation":false,"usgs":false,"family":"Lunt","given":"D.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":843281,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":261665,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":843282,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Chandan, Deepak","contributorId":269588,"corporation":false,"usgs":false,"family":"Chandan","given":"Deepak","email":"","affiliations":[{"id":55996,"text":"Department of Physics, University of Toronto, Toronto, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":843362,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Peltier, W. Richard","contributorId":150752,"corporation":false,"usgs":false,"family":"Peltier","given":"W.","email":"","middleInitial":"Richard","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":843363,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70237849,"text":"70237849 - 2022 - Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem","interactions":[],"lastModifiedDate":"2022-10-26T12:23:06.994149","indexId":"70237849","displayToPublicDate":"2022-03-12T07:20:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem","docAbstract":"

Though primary sources of carbon (C) to soil are plant inputs (e.g., rhizodeposits), the role of microorganisms as mediators of soil organic carbon (SOC) retention is increasingly recognized. Yet, insufficient knowledge of sub-soil processes complicates attempts to describe microbial-driven C cycling at depth as most studies of microbial-mineral-C interactions focus on surface horizons. We leveraged a well-studied paleo-marine terrace (90 ka) located near Santa Cruz, CA, to characterize the short-term (days to weeks) and intermediate-term (months to years) fate of two low molecular weight organic carbon. compounds at three depths in the soil profile (∼25 cm, A horizon; ∼75 cm A/B transition; and ∼125 cm, B horizon). We employed isotopically-labeled glucose (GLU) and oxalic acid (OXA) to represent two common classes of rhizodeposits: carbohydrates and organic acids. Using a combination of laboratory (9 d) and field (490 d) incubations, we traced the fate of GLU-C and OXA-C through dissolved-, metal-associated-, and microbially-respired CO2 and bulk SOC pools. Our results suggest new SOC retention (i.e., defined as 13C label identified in solid or aqueous fractions) over intermediate time frames (490 d) is correlated with patterns in short-term (9 d) cycling dynamics, which in turn is related to the theoretical efficiency by which microorganisms process each substrate. For all horizons (A, A/B, and B) GLU-C was converted to CO2 more quickly than OXA-C with modeled decomposition rates ∼2–4 times faster for GLU depending on microbial density (higher in A than B horizon). The faster decomposition rates of GLU-C increased fractional recovery (0.399 ± 0.026 to 0.504 ± 0.030 for GLU-C) compared to OXA-C (0.035 ± 0.003 to 0.127 ± 0.010) among all horizons in our field experiment (490 d). Though the overall proportion of GLU-C recovered in solid fractions did not vary significantly with horizon, based on 13C recovered in aqueous fractions the apparent mechanism for retention did. After the 9-d laboratory incubation, fractional recovery for GLU-C among C pools associated with microbial biomass was almost 20× higher than OXA-C (0.192 versus 0.010, respectively across all horizons). More than a year later, 43–46% of GLU-C retained in the field incubation was extractable with a neutral salt (representing a pool of soil C residing within or available to microbial biomass) among A and A/B horizons, while only 6% of retained GLU-C was similarly extractable in the B horizon. Thus, it appears among depths with higher microbial density (A, A/B horizons), anabolic recycling is the most likely process contributing to the persistence of glucose C, whereas abiotic sinks contributed more to intermediate-term stability for GLU-C in the B horizon. By contrast, most OXA-C was lost, presumably as CO2, over the short-term from the A and A/B horizons (fractional recovery: 0.136 ± 0.011 and 0.091 ± 0.002, respectively). However, though substantially lower than GLU-C recovered at the conclusion of our field experiment, the fraction of oxalic acid C retained in the B horizon over both short- (0.72 ± 0.037) and intermediate-time (0.127 ± 0.010) frames was several-fold higher than for overlying horizons. The specific process(es) (e.g., more efficient microbial utilization, metal-organic complexation, direct adsorption to the mineral matrix, etc.) contributing to higher retention for OXA-C at depth are discussed but remain unresolved.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.soilbio.2022.108601","usgsCitation":"McFarland, J., Lawrence, C., Creamer, C., Schulz, M., Conaway, C., Peek, S., Waldrop, M., Sevilgen, S.N., and Haw, M., 2022, Mechanisms for retention of low molecular weight organic carbon varies with soil depth at a coastal prairie ecosystem: Soil Biology and Biochemistry, v. 168, 108601, 14 p., https://doi.org/10.1016/j.soilbio.2022.108601.","productDescription":"108601, 14 p.","ipdsId":"IP-133200","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":448524,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.soilbio.2022.108601","text":"Publisher Index Page"},{"id":435929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98AD5H5","text":"USGS data release","linkHelpText":"Short vs intermediate-term fate of glucose and oxalic acid in surface and subsurface soils of a coastal grassland near Santa Cruz California"},{"id":408746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"168","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":855854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":219251,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":855855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":855856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2022 - Volatile organic compounds in groundwater used for public supply across the United States: Occurrence, explanatory factors, and human-health context","interactions":[],"lastModifiedDate":"2022-03-15T14:43:15.787447","indexId":"70229686","displayToPublicDate":"2022-03-11T09:39:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Volatile organic compounds in groundwater used for public supply across the United States: Occurrence, explanatory factors, and human-health context","docAbstract":"

This systematic assessment of occurrence for 85 volatile organic compounds (VOCs) in raw (untreated) groundwater used for public supply across the United States (U.S.), which includes 43 compounds not previously monitored by national studies, relates VOC occurrence to explanatory factors and assesses VOC detections in a human-health context. Samples were collected in 2013 through 2019 from 1537 public-supply wells in aquifers representing 78% of the volume pumped for public drinking-water supply. Laboratory detection limits for VOCs generally were less than 0.1 μg/L. Detections were reported for 36% of the sampled principal-aquifer area (38% of sampled wells) and were most common in wells in shallow, unconfined aquifers in urban areas that produce high proportions of modern-age and oxic groundwater. The disinfection by-product trichloromethane (chloroform) was the most commonly detected VOC associated primarily with anthropogenic sources (24% of the sampled area, 25% of sampled wells), followed by the gasoline oxygenate methyl tert-butyl ether (8.4% of area, 11% of wells). Carbon disulfide (12% of area, 14% of wells) was examined separately because of likely substantial contributions from natural sources. Newly monitored VOCs were each detected in <1% of the sampled area. Although detections of 1,4-dioxane in this first national study of its occurrence in raw groundwater were rare, measured concentrations exceeded the most stringent (non-enforceable) human-health benchmark in 0.5% of the sampled area (9 wells). Two wells had exceedances of enforceable benchmarks for tetrachloroethylene and trichloroethylene, and 50 wells total (representing 2.0% of the sampled area, 3.3% of sampled wells) had combined VOC concentrations exceeding 10% of benchmarks of any type. Compared with previous national findings, this study reports lower rates of VOC detection, but confirms widespread anthropogenic influence on groundwater used for public supply, with relatively few concentrations of individual VOCs or mixtures that approach or exceed human-health benchmarks.

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]\n}","volume":"827","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":837961,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229513,"text":"sir20225004 - 2022 - Sediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019","interactions":[],"lastModifiedDate":"2026-04-08T17:09:45.954613","indexId":"sir20225004","displayToPublicDate":"2022-03-10T12:31:40","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5004","displayTitle":"Sediment Monitoring and Streamflow Modeling Before and After a Stream Restoration in Rice Creek, Minnesota, 2010–2019","title":"Sediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019","docAbstract":"

The Rice Creek Watershed District (RCWD) cooperated with the U.S. Geological Survey to establish a 10-year suspended sediment and bedload monitoring and streamflow modeling study to evaluate the effects of two restored meander sections on middle Rice Creek in Arden Hills, Minnesota. The RCWD goals of this stream restoration were to reduce water quality impairments, improve aquatic habitat, and reduce associated costs of dredging a sedimentation pond. During the study there were several factors that introduced uncertainty in the sampling results; however, the sampling results indicated there was an increase in the post-stream restoration sediment data because of higher streamflows during the post-stream than the pre-stream restoration monitoring period. The negative relation between suspended fines and streamflow was explained by a reduction in the supply of fines with increasing streamflows. The positive relation among suspended sand, bedload, and streamflow was because of those constituents having a functional relation with the hydraulic properties of flow and a consistent supply of sand. Two-dimensional flow modeling simulations indicated the downstream restored section had less shear stress, more pools, and could access the floodplain at a lower streamflow than the original channel. Overall, the uncertainty of the sampling results indicates the complexity of sediment transport in a river and suggests a need for multisite, multifaceted, multiyear data, and tools to simulate those data to effectively evaluate river restorations.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225004","collaboration":"Prepared in cooperation with Rice Creek Watershed District","usgsCitation":"Groten, J.T., Livdahl, C.T., DeLong, S.B., Lund, J.W., Nelson, J.M., Coenen, E.N., Ziegeweid, J.R., and Kocian, M.J., 2022, Sediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019: U.S. Geological Survey Scientific Investigations Report 2022–5004, 40 p., https://doi.org/10.3133/sir20225004.","productDescription":"Report: viii, 40 p.; Data Release; Dataset","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-126710","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396980,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJIY32","text":"USGS data release","linkHelpText":"Suspended sediment and bedload data, simple linear regression models, loads, elevation data, and FaSTMECH models for Rice Creek, Minnesota, 2010-2019"},{"id":396979,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":396978,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5004/images"},{"id":502292,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112549.htm","linkFileType":{"id":5,"text":"html"}},{"id":396976,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5004/sir20225004.pdf","text":"Report","size":"19.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5004"},{"id":396975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5004/coverthb.jpg"},{"id":396977,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5004/sir20225004.XML"}],"country":"United States","state":"Minnesota","otherGeospatial":"Rice Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.21710586547852,\n 45.08236949749694\n ],\n [\n -93.18449020385742,\n 45.08236949749694\n ],\n [\n -93.18449020385742,\n 45.09957848291159\n ],\n [\n -93.21710586547852,\n 45.09957848291159\n ],\n [\n -93.21710586547852,\n 45.08236949749694\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2022-03-10","noUsgsAuthors":false,"publicationDate":"2022-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Livdahl, Colin T. 0000-0002-1743-9891","orcid":"https://orcid.org/0000-0002-1743-9891","contributorId":288314,"corporation":false,"usgs":false,"family":"Livdahl","given":"Colin","email":"","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":837709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLong, Stephen B. 0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":837710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":211157,"corporation":false,"usgs":true,"family":"Lund","given":"J.","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":837712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coenen, Erin N. 0000-0003-2470-3854","orcid":"https://orcid.org/0000-0003-2470-3854","contributorId":211159,"corporation":false,"usgs":true,"family":"Coenen","given":"Erin N.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837714,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kocian, Matthew J.","contributorId":19654,"corporation":false,"usgs":false,"family":"Kocian","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837715,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230138,"text":"70230138 - 2022 - Functional wetland loss drives emerging risks to waterbird migration networks","interactions":[],"lastModifiedDate":"2022-03-30T15:51:12.581428","indexId":"70230138","displayToPublicDate":"2022-03-10T10:45:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Functional wetland loss drives emerging risks to waterbird migration networks","docAbstract":"

Migratory waterbirds (i.e., shorebirds, wading birds, and waterfowl) rely on a diffuse continental network of wetland habitats to support annual life cycle needs. Emerging threats of climate and land-use change raise new concerns over the sustainability of these habitat networks as water scarcity triggers cascading ecological effects impacting wetland habitat availability. Here we use important waterbird regions in Oregon and California, United States, as a model system to examine patterns of landscape change impacting wetland habitat networks in western North America. Wetland hydrology and flooded agricultural habitats were monitored monthly from 1988 to 2020 using satellite imagery to quantify the timing and duration of inundation—a key delimiter of habitat niche values associated with waterbird use. Trends were binned by management practice and wetland hydroperiods (semi-permanent, seasonal, and temporary) to identify differences in their climate and land-use change sensitivity. Wetland results were assessed using 33 waterbird species to detect non-linear effects of network change across a diversity of life cycle and habitat needs. Pervasive loss of semi-permanent wetlands was an indicator of systemic functional decline. Shortened hydroperiods caused by excessive drying transitioned semi-permanent wetlands to seasonal and temporary hydrologies—a process that in part counterbalanced concurrent seasonal and temporary wetland losses. Expansion of seasonal and temporary wetlands associated with closed-basin lakes offset wetland declines on other public and private lands, including wildlife refuges. Diving ducks, black terns, and grebes exhibited the most significant risk of habitat decline due to semi-permanent wetland loss that overlapped important migration, breeding, molting, and wintering periods. Shorebirds and dabbling ducks were beneficiaries of stable agricultural practices and top-down processes of functional wetland declines that operated collectively to maintain habitat needs. Outcomes from this work provide a novel perspective of wetland ecosystem change affecting waterbirds and their migration networks. Understanding the complexity of these relationships will become increasingly important as water scarcity continues to restructure the timing and availability of wetland resources.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.844278","usgsCitation":"Donnelly, J., Moore, J.N., Casazza, M.L., and Coons, S.P., 2022, Functional wetland loss drives emerging risks to waterbird migration networks: Frontiers in Ecology and Evolution, v. 10, 844278, 18 p., https://doi.org/10.3389/fevo.2022.844278.","productDescription":"844278, 18 p.","ipdsId":"IP-137357","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448530,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.844278","text":"Publisher Index Page"},{"id":397863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.71826171875,\n 35.35321610123823\n ],\n [\n -118.71826171875,\n 36.06686213257888\n ],\n [\n -119.35546875000001,\n 36.87962060502676\n ],\n [\n -120.62988281249999,\n 38.151837403006766\n ],\n [\n -121.31103515625,\n 39.36827914916014\n ],\n [\n -121.86035156249999,\n 40.59727063442024\n ],\n [\n -122.36572265625,\n 40.730608477796636\n ],\n [\n -122.87109375,\n 40.38002840251183\n ],\n [\n -122.56347656249999,\n 39.33429742980725\n ],\n [\n -121.9921875,\n 38.54816542304656\n ],\n [\n -121.06933593749999,\n 37.579412513438385\n ],\n [\n -120.498046875,\n 36.61552763134925\n ],\n [\n -119.2236328125,\n 35.28150065789119\n ],\n [\n -118.71826171875,\n 35.35321610123823\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.47607421874999,\n 40.730608477796636\n ],\n [\n -119.46533203125,\n 40.697299008636755\n ],\n [\n -119.46533203125,\n 41.64007838467894\n ],\n [\n -118.740234375,\n 42.32606244456202\n ],\n [\n -117.99316406249999,\n 43.004647127794435\n ],\n [\n -118.89404296875,\n 44.15068115978094\n ],\n [\n -119.90478515625,\n 44.465151013519616\n ],\n [\n -121.1572265625,\n 44.071800467511565\n ],\n [\n -121.66259765625001,\n 43.27720532212024\n ],\n [\n -121.13525390625,\n 42.24478535602799\n ],\n [\n -121.2451171875,\n 41.672911819602085\n ],\n [\n -121.06933593749999,\n 41.244772343082076\n ],\n [\n -120.56396484375,\n 41.16211393939692\n ],\n [\n -120.47607421874999,\n 40.730608477796636\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Donnelly, J Patrick","contributorId":289526,"corporation":false,"usgs":false,"family":"Donnelly","given":"J Patrick","affiliations":[{"id":62169,"text":"Intermountain West Joint Venture - U.S. Fish and Wildlife Service, Migratory Bird Program, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Johnnie N","contributorId":289527,"corporation":false,"usgs":false,"family":"Moore","given":"Johnnie","email":"","middleInitial":"N","affiliations":[{"id":62170,"text":"Group for Quantitative Study of Snow and Ice, Department of Geosciences, University of Montana, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":839229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coons, Shea P","contributorId":289528,"corporation":false,"usgs":false,"family":"Coons","given":"Shea","email":"","middleInitial":"P","affiliations":[{"id":62172,"text":"Avian Science Center - University of Montana, Missoula, MT, United States","active":true,"usgs":false}],"preferred":false,"id":839230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229510,"text":"sir20225003 - 2022 - Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima","interactions":[],"lastModifiedDate":"2026-04-08T17:07:36.608501","indexId":"sir20225003","displayToPublicDate":"2022-03-09T13:55:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5003","displayTitle":"Response of Green Lake, Wisconsin, to Changes in Phosphorus Loading, With Special Emphasis on Near-Surface Total Phosphorus Concentrations and Metalimnetic Dissolved Oxygen Minima","title":"Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima","docAbstract":"

Green Lake is the deepest natural inland lake in Wisconsin, with a maximum depth of about 72 meters. In the early 1900s, the lake was believed to have very good water quality (low nutrient concentrations and good water clarity) with low dissolved oxygen (DO) concentrations occurring in only the deepest part of the lake. Because of increased phosphorus (P) inputs from anthropogenic activities in its watershed, total phosphorus (TP) concentrations in the lake have increased; these changes have led to increased algal production and low DO concentrations not only in the deepest areas but also in the middle of the water column (metalimnion). The U.S. Geological Survey has routinely monitored the lake since 2004 and its tributaries since 1988. Results from this monitoring led the Wisconsin Department of Natural Resources (WDNR) to list the lake as impaired because of low DO concentrations in the metalimnion, and they identified elevated TP concentrations as the cause of impairment.

As part of this study by the U.S. Geological Survey, in cooperation with the Green Lake Sanitary District, the lake and its tributaries were comprehensively sampled in 2017–18 to augment ongoing monitoring that would further describe the low DO concentrations in the lake (especially in the metalimnion). Empirical and process-driven water-quality models were then used to determine the causes of the low DO concentrations and the magnitudes of P-load reductions needed to improve the water quality of the lake enough to meet multiple water-quality goals, including the WDNR’s criteria for TP and DO.

Data from previous studies showed that DO concentrations in the metalimnion decreased slightly as summer progressed in the early 1900s but, since the late 1970s, have typically dropped below 5 milligrams per liter (mg/L), which is the WDNR criterion for impairment. During 2014–18 (the baseline period for this study), the near-surface geometric mean TP concentration during June–September in the east side of the lake was 0.020 mg/L and in the west side was 0.016 mg/L (both were above the 0.015-mg/L WDNR criterion for the lake), and the metalimnetic DO minimum concentrations (MOMs) measured in August ranged from 1.0 to 4.7 mg/L. The degradation in water quality was assumed to have been caused by excessive P inputs to the lake; therefore, the TP inputs to the lake were estimated. The mean annual external P load during 2014–18 was estimated to be 8,980 kilograms per year (kg/yr), of which monitored and unmonitored tributary inputs contributed 84 percent, atmospheric inputs contributed 8 percent, waterfowl contributed 7 percent, and septic systems contributed 1 percent. During fall turnover, internal sediment recycling contributed an additional 7,040 kilograms that increased TP concentrations in shallow areas of the lake by about 0.020 mg/L. The elevated TP concentrations then persisted until the following spring. On an annual basis, however, there was a net deposition of P to the bottom sediments.

Empirical models were used to describe how the near-surface water quality of Green Lake would be expected to respond to changes in external P loading. Predictions from the models showed a relatively linear response between P loading and TP and chlorophyll-a (Chl-a) concentrations in the lake, with the changes in TP and Chl-a concentrations being less on a percentage basis (50–60 percent for TP and 30–70 percent for Chl-a) than the changes in P loading. Mean summer water clarity, quantified by Secchi disk depths, had a greater response to decreases in P loading than to increases in P loading. Based on these relations, external P loading to the lake would need to be decreased from 8,980 kg/yr to about 5,460 kg/yr for the geometric mean June–September TP concentration in the east side of the lake, with higher TP concentrations than in the west side, to reach the WDNR criterion of 0.015 mg/L. This reduction of 3,520 kg/yr is equivalent to a 46-percent reduction in the potentially controllable external P sources (all external sources except for precipitation, atmospheric deposition, and waterfowl) from those measured during water years 2014–18. The total external P loading would need to decrease to 7,680 kg/yr (a 17-percent reduction in potentially controllable external P sources) for near-surface June–September TP concentrations in the west side of the lake to reach 0.015 mg/L. Total external P loading would need to decrease to 3,870–5,320 kg/yr for the lake to be classified as oligotrophic, with a near-surface June–September TP concentration of 0.012 mg/L.

Results from the hydrodynamic water-quality model GLM–AED (General Lake Model coupled to the Aquatic Ecodynamics modeling library) indicated that MOMs are driven by external P loading and internal sediment recycling that lead to high TP concentrations during spring and early summer, which in turn lead to high phytoplankton production, high metabolism and respiration, and ultimately DO consumption in the upper, warmer areas of the metalimnion. GLM–AED results indicated that settling of organic material during summer might be slowed by the colder, denser, and more viscous water in the metalimnion and thus increase DO consumption. Based on empirical evidence from a comparison of MOMs with various meteorological, hydrologic, water quality, and in-lake physical factors, MOMs were lower during summers, when metalimnetic water temperatures were warmer, near-surface Chl-a and TP concentrations were higher, and Secchi depths were lower. GLM–AED results indicated that the external P load would need to be reduced to about 4,060 kg/yr, a 57-percent reduction from that measured in 2014–18, to eliminate the occurrence of MOMs less than 5 mg/L during more than 75 percent of the years (the target provided by the WDNR).

Large reductions in external P loading are expected to have an immediate effect on the near-surface TP concentrations and metalimnetic DO concentrations in Green Lake; however, it may take several years for the full effects of the external-load reduction to be observed because internal sediment recycling is an important source of P for the following spring.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225003","collaboration":"Prepared in cooperation with the Green Lake Sanitary District","usgsCitation":"Robertson, D.M., Siebers, B.J., Ladwig, R., Hamilton, D.P., Reneau, P.C., McDonald, C.P., Prellwitz, S., and Lathrop, R.C., 2022, Response of Green Lake, Wisconsin, to changes in phosphorus loading, with special emphasis on near-surface total phosphorus concentrations and metalimnetic dissolved oxygen minima: U.S. Geological Survey Scientific Investigations Report 2022–5003, 77 p., https://doi.org/10.3133/sir20225003.","productDescription":"Report: xi, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123380","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502291,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112545.htm","linkFileType":{"id":5,"text":"html"}},{"id":396912,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5003/images/"},{"id":396910,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H85BK0","text":"USGS data release","linkHelpText":"Eutrophication models to simulate changes in the water quality of Green Lake, Wisconsin in response to changes in phosphorus loading, with supporting water-quality data for the lake, its tributaries, and atmospheric deposition"},{"id":396911,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5003/sir20225003.XML"},{"id":396909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5003/sir20225003.pdf","text":"Report","size":"8.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5003"},{"id":396908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5003/coverthb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.09225463867188,\n 43.756712928570245\n ],\n [\n -88.86428833007814,\n 43.756712928570245\n ],\n [\n -88.86428833007814,\n 43.85384062624276\n ],\n [\n -89.09225463867188,\n 43.85384062624276\n ],\n [\n -89.09225463867188,\n 43.756712928570245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-03-09","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siebers, Benjamin J. 0000-0002-2900-5169","orcid":"https://orcid.org/0000-0002-2900-5169","contributorId":206518,"corporation":false,"usgs":true,"family":"Siebers","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladwig, Robert","contributorId":265278,"corporation":false,"usgs":false,"family":"Ladwig","given":"Robert","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":837661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamilton, David P. 0000-0002-9341-8777 hamiltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9341-8777","contributorId":130968,"corporation":false,"usgs":false,"family":"Hamilton","given":"David","email":"hamiltond@usgs.gov","middleInitial":"P.","affiliations":[{"id":7184,"text":"Environmental Research Institute, University of Waikato, Hamilton, New Zealand","active":true,"usgs":false}],"preferred":true,"id":837662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reneau, Paul C. 0000-0002-1335-7573 pcreneau@usgs.gov","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":4385,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul","email":"pcreneau@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837663,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Cory P. 0000-0002-1208-8471 cmcdonald@usgs.gov","orcid":"https://orcid.org/0000-0002-1208-8471","contributorId":4238,"corporation":false,"usgs":true,"family":"McDonald","given":"Cory","email":"cmcdonald@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":837664,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prellwitz, Stephanie","contributorId":265281,"corporation":false,"usgs":false,"family":"Prellwitz","given":"Stephanie","email":"","affiliations":[{"id":54642,"text":"Green Lake Association","active":true,"usgs":false}],"preferred":false,"id":837665,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lathrop, Richard C.","contributorId":221002,"corporation":false,"usgs":false,"family":"Lathrop","given":"Richard","email":"","middleInitial":"C.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":837666,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236698,"text":"70236698 - 2022 - Possible anthropogenic enhancement of precipitation in the Sahel-Sudan Savanna by remote agricultural irrigation","interactions":[],"lastModifiedDate":"2022-09-16T14:35:16.780446","indexId":"70236698","displayToPublicDate":"2022-03-09T09:30:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Possible anthropogenic enhancement of precipitation in the Sahel-Sudan Savanna by remote agricultural irrigation","docAbstract":"

The local climatic impacts of historical expansion of irrigation are substantial, but the distant impacts are poorly understood, and their governing mechanisms generally have not been rigorously analyzed. Our experiments with an earth-system model suggest that irrigation in the Middle East and South Asia may enhance rainfall in a large portion of the Sahel-Sudan Savanna (SSS) to an extent comparable and opposite to its suppression by other anthropogenic climate drivers during the last several decades. The enhancement arises through a reduction in the meridional gradient of moist static energy from the Sahara Desert to the tropical rainforests. An implication of this study is that remote irrigation is a possible factor affecting the risk of drought and famine and, thus, future water security in the SSS region.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL096972","usgsCitation":"Zeng, Y., Milly, P.C., Shevliakova, E., Malyshev, S., von Huijgevoort, M., and Dunne, K.A., 2022, Possible anthropogenic enhancement of precipitation in the Sahel-Sudan Savanna by remote agricultural irrigation: Geophysical Research Letters, v. 49, no. 6, e2021GL096972, 10 p., https://doi.org/10.1029/2021GL096972.","productDescription":"e2021GL096972, 10 p.","ipdsId":"IP-110306","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl096972","text":"Publisher Index Page"},{"id":406840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Sahel-Sudan Savanna","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -1,\n 10\n ],\n [\n 35,\n 10\n ],\n [\n 35,\n 20\n ],\n [\n -1,\n 20\n ],\n [\n -1,\n 10\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeng, Yujin","contributorId":295884,"corporation":false,"usgs":false,"family":"Zeng","given":"Yujin","email":"","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":851922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":851923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":851924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":851925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"von Huijgevoort, Marjolein","contributorId":296590,"corporation":false,"usgs":false,"family":"von Huijgevoort","given":"Marjolein","email":"","affiliations":[{"id":64100,"text":"KWR (Netherlands)","active":true,"usgs":false}],"preferred":false,"id":851926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunne, Krista A. 0000-0002-1220-6140 kadunne@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-6140","contributorId":203816,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":851927,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255284,"text":"70255284 - 2022 - Greater than the sum of its parts: Computationally flexible Bayesian hierarchical modeling","interactions":[],"lastModifiedDate":"2024-06-14T13:43:23.197776","indexId":"70255284","displayToPublicDate":"2022-03-09T08:39:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9352,"text":"Journal of Agricultural, Biological and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Greater than the sum of its parts: Computationally flexible Bayesian hierarchical modeling","docAbstract":"

We propose a multistage method for making inference at all levels of a Bayesian hierarchical model (BHM) using natural data partitions to increase efficiency by allowing computations to take place in parallel form using software that is most appropriate for each data partition. The full hierarchical model is then approximated by the product of independent normal distributions for the data component of the model. In the second stage, the Bayesian maximum a posteriori (MAP) estimator is found by maximizing the approximated posterior density with respect to the parameters. If the parameters of the model can be represented as normally distributed random effects, then the second-stage optimization is equivalent to fitting a multivariate normal linear mixed model. We consider a third stage that updates the estimates of distinct parameters for each data partition based on the results of the second stage. The method is demonstrated with two ecological data sets and models, a generalized linear mixed effects model (GLMM) and an integrated population model (IPM). The multistage results were compared to estimates from models fit in single stages to the entire data set. In both cases, multistage results were very similar to a full MCMC analysis. Supplementary materials accompanying this paper appear online.

","language":"English","publisher":"Springer","doi":"10.1007/s13253-021-00485-9","usgsCitation":"Johnson, D., Brost, B., and Hooten, M., 2022, Greater than the sum of its parts: Computationally flexible Bayesian hierarchical modeling: Journal of Agricultural, Biological and Environmental Statistics, v. 27, https://doi.org/10.1007/s13253-021-00485-9.","productDescription":"19 p.","startPage":"400","ipdsId":"IP-123441","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448547,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13253-021-00485-9","text":"Publisher Index Page"},{"id":430203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","edition":"382","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Devin S.","contributorId":337626,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":904099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brost, Brian M.","contributorId":244504,"corporation":false,"usgs":false,"family":"Brost","given":"Brian M.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":904100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":904098,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230166,"text":"70230166 - 2022 - Maximizing species distribution model performance when using historical occurrences and variables of varying persistency","interactions":[],"lastModifiedDate":"2022-04-01T22:02:19.08828","indexId":"70230166","displayToPublicDate":"2022-03-09T08:07:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Maximizing species distribution model performance when using historical occurrences and variables of varying persistency","docAbstract":"

Occurrence data used to build species distribution models often include historical records from locations in which the species no longer exists. When these records are paired with contemporary environmental values that no longer represent the conditions the species experienced, the model creates false associations that hurt predictive performance. The extent of mismatching increases with the number of historical occurrences and with inclusion of environmental variables that are prone to change over time. Indeed, the mismatch between occurrence data and contemporaneous environmental variables is a common dilemma when modeling rare or cryptic species, especially those of conservation concern that were once more abundant. Herein, we assess (1) the impact of historical occurrences on model performance across three sets of environmental variables of increasing persistency and (2) the performance of models built using selected-historical occurrences from locations that showed evidence of limited environmental change over time. Concepts are tested on federally listed flatwoods salamanders, reflecting real-world conservation management efforts. We predicted that, compared to other occurrence sets, (1) historical occurrences would perform best with environmental variables that were more persistent, (2) recent occurrences would perform best when the environmental variables were more impersistent, and that (3) our selected-historical occurrences would perform best with a combination of persistent and impersistent variables. Our results showed the expected inversion of model performance of recent and historical occurrences across environmental variables of increasing persistency when evaluated by correct predictions. However, the inversion was not seen in area under the curve performance, in which historical occurrences outperformed recent occurrence models across all variable sets. Selected-historical occurrences did not notably improve performance over all-historical occurrences in any metric or variable set. To maximize utility and performance, modelers could acknowledge potential trade-offs from inclusion of historical occurrences and consider number and age of recent and historical occurrences available, the persistency of environmental variables considered, and how their conservation goals are reflected in model design and evaluation, particularly with respect to sensitivity versus specificity. Our study lends support for inclusion of historical occurrences, with the potential exception of mostly impersistent variables when sensitivity is the highest priority.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3951","usgsCitation":"Bracken, J.T., Davis, A., O’Donnell, K., Barichivich, W., Walls, S., and Jezkova, T., 2022, Maximizing species distribution model performance when using historical occurrences and variables of varying persistency: Ecosphere, v. 13, no. 3, e3951, 13 p., https://doi.org/10.1002/ecs2.3951.","productDescription":"e3951, 13 p.","ipdsId":"IP-126905","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":489148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3951","text":"Publisher Index Page"},{"id":397930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.4619140625,\n 30.391830328088137\n ],\n [\n -87.62695312499999,\n 30.107117887092357\n ],\n [\n -86.8359375,\n 30.240086360983426\n ],\n [\n -85.97900390625,\n 30.06909396443887\n ],\n [\n -85.517578125,\n 29.592565403314087\n ],\n [\n -84.9462890625,\n 29.516110386062277\n ],\n [\n -84.111328125,\n 29.954934549656144\n ],\n [\n -83.27636718749999,\n 29.209713225868185\n ],\n [\n -82.79296874999999,\n 28.786918085420226\n ],\n [\n -83.07861328125,\n 28.013801376380712\n ],\n [\n -82.96875,\n 27.702983735525862\n ],\n [\n -80.52978515625,\n 28.265682390146477\n ],\n [\n -80.419921875,\n 28.555576049185973\n ],\n [\n -80.79345703125,\n 28.92163128242129\n ],\n [\n -81.474609375,\n 30.80791068136646\n ],\n [\n -80.88134765625,\n 31.98944183792288\n ],\n [\n -79.89257812499999,\n 32.54681317351514\n ],\n [\n -79.189453125,\n 33.063924198120645\n ],\n [\n -78.59619140625,\n 33.90689555128866\n ],\n [\n -88.41796875,\n 32.93492866908233\n ],\n [\n -88.52783203125,\n 31.82156451492074\n ],\n [\n -88.4619140625,\n 30.391830328088137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bracken, Jason T.","contributorId":289570,"corporation":false,"usgs":false,"family":"Bracken","given":"Jason","email":"","middleInitial":"T.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":839350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Amelie Y.","contributorId":289572,"corporation":false,"usgs":false,"family":"Davis","given":"Amelie Y.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":839351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Katherine M. 0000-0001-9023-174X kmodonnell@usgs.gov","orcid":"https://orcid.org/0000-0001-9023-174X","contributorId":176897,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katherine M.","email":"kmodonnell@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barichivich, William 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":215988,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":3055,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":true,"id":839354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jezkova, Tereza","contributorId":209721,"corporation":false,"usgs":false,"family":"Jezkova","given":"Tereza","email":"","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":839355,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237671,"text":"70237671 - 2022 - Nitrogen enrichment during soil organic matter burning and molecular evidence of maillard reactions","interactions":[],"lastModifiedDate":"2022-10-18T12:10:10.750448","indexId":"70237671","displayToPublicDate":"2022-03-09T07:05:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen enrichment during soil organic matter burning and molecular evidence of maillard reactions","docAbstract":"

Wildfires in forested watersheds dramatically alter stored and labile soil organic matter (SOM) pools and the export of dissolved organic matter (DOM). Ecosystem recovery after wildfires depends on soil microbial communities and revegetation and therefore is limited by the availability of nutrients, such as nitrogen-containing and labile, water-soluble compounds. However, SOM byproducts produced at different wildfire intensities are poorly understood, leading to difficulties in assessing wildfire severity and predicting ecosystem recovery. In this work, water-extractable organic matter (WEOM) from laboratory microcosms of soil burned at discrete temperatures was characterized by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry to study the impacts of fire temperature on SOM and DOM composition. The molecular composition derived from different burn temperatures indicated that nitrogen-containing byproducts were enriched with heating and composed of a wide range of aromatic features and oxidation states. Mass difference-based analysis also suggested that products formed during heating could be modeled using transformations along the Maillard reaction pathway. The enrichment of N-containing SOM and DOM at different soil burning intensities has important implications for ecosystem recovery and downstream water quality.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c06745","usgsCitation":"Bahureksa, W., Young, R.B., McKenna, A.M., Chen, H., Thorn, K., Rosario-Ortiz, F.L., and Borch, T., 2022, Nitrogen enrichment during soil organic matter burning and molecular evidence of maillard reactions: Environmental Science and Technology, v. 56, no. 7, p. 4597-4609, https://doi.org/10.1021/acs.est.1c06745.","productDescription":"13 p.","startPage":"4597","endPage":"4609","ipdsId":"IP-135387","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":408466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bahureksa, William","contributorId":298031,"corporation":false,"usgs":false,"family":"Bahureksa","given":"William","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":854926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Robert B.","contributorId":298032,"corporation":false,"usgs":false,"family":"Young","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":854927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKenna, Amy M.","contributorId":298033,"corporation":false,"usgs":false,"family":"McKenna","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":854928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Huan","contributorId":298034,"corporation":false,"usgs":false,"family":"Chen","given":"Huan","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":854929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorn, Kevin A. 0000-0003-2236-5193","orcid":"https://orcid.org/0000-0003-2236-5193","contributorId":220016,"corporation":false,"usgs":true,"family":"Thorn","given":"Kevin A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":854930,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosario-Ortiz, Fernando L.","contributorId":240990,"corporation":false,"usgs":false,"family":"Rosario-Ortiz","given":"Fernando","email":"","middleInitial":"L.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":854931,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borch, Thomas","contributorId":195631,"corporation":false,"usgs":false,"family":"Borch","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":854932,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}