{"pageNumber":"232","pageRowStart":"5775","pageSize":"25","recordCount":184635,"records":[{"id":70249642,"text":"70249642 - 2023 - Alternative measures of trait–niche relationships: A test on dispersal traits in saproxylic beetles","interactions":[],"lastModifiedDate":"2023-10-21T13:43:50.552769","indexId":"70249642","displayToPublicDate":"2023-10-19T08:39:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Alternative measures of trait–niche relationships: A test on dispersal traits in saproxylic beetles","docAbstract":"

Functional trait approaches are common in ecology, but a lack of clear hypotheses on how traits relate to environmental gradients (i.e., trait–niche relationships) often makes uncovering mechanisms difficult. Furthermore, measures of community functional structure differ in their implications, yet inferences are seldom compared among metrics. Community-weighted mean trait values (CWMs), a common measure, are largely driven by the most common species and thus do not reflect community-wide trait–niche relationships per se. Alternatively, trait–niche relationships can be estimated across a larger group of species using hierarchical joint species distribution models (JSDMs), quantified by a parameter Γ. We investigated how inferences about trait–niche relationships are affected by the choice of metric. Using deadwood-dependent (saproxylic) beetles in fragmented Finnish forests, we followed a protocol for investigating trait–niche relationships by (1) identifying environmental filters (climate, forest age, and deadwood volume), (2) relating these to an ecological function (dispersal ability), and (3) identifying traits related to this function (wing morphology). We tested 18 hypothesized dispersal relationships using both CWM and Γ estimates across these environmental gradients. CWMs were more likely than Γ to show support for trait–niche relationships. Up to 13% of species' realized niches were explained by dispersal traits, but the directions of effects were consistent with fewer than 11%–39% of our 18 trait–niche hypotheses (depending on the metric used). This highlights the difficulty in connecting morphological traits and ecological functions in insects, despite the clear conceptual link between landscape connectivity and flight-related traits. Caution is thus warranted in hypothesis development, particularly where apparent trait–function links are less clear. Inferences differ when CWMs versus Γ estimates are used, necessitating the choice of a metric that reflects study questions. CWMs help explain the effects of environmental gradients on community trait composition, whereas the effects of traits on species' niches are better estimated using hierarchical JSDMs.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10588","usgsCitation":"Burner, R.C., Stephan, J., Drag, L., Potterf, M., Birkemoe, T., Siitonen, J., Müller, J., Ovaskainen, O., Sverdrup-Thygeson, A., and Snäll, T., 2023, Alternative measures of trait–niche relationships: A test on dispersal traits in saproxylic beetles: Ecology and Evolution, v. 13, no. 10, e10588, 14 p., https://doi.org/10.1002/ece3.10588.","productDescription":"e10588, 14 p.","ipdsId":"IP-151508","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441838,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10588","text":"Publisher Index Page"},{"id":422033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Finland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[28.59193,69.06478],[28.44594,68.36461],[29.97743,67.6983],[29.05459,66.94429],[30.21765,65.80598],[29.54443,64.94867],[30.44468,64.20445],[30.03587,63.55281],[31.51609,62.86769],[31.13999,62.35769],[30.21111,61.78003],[28.07,60.50352],[26.25517,60.42396],[24.49662,60.05732],[22.86969,59.84637],[22.29076,60.39192],[21.32224,60.72017],[21.54487,61.70533],[21.05921,62.60739],[21.53603,63.18974],[22.44274,63.81781],[24.73051,64.90234],[25.39807,65.11143],[25.29404,65.53435],[23.90338,66.00693],[23.56588,66.39605],[23.53947,67.93601],[21.97853,68.61685],[20.64559,69.10625],[21.24494,69.37044],[22.35624,68.84174],[23.66205,68.89125],[24.73568,68.64956],[25.68921,69.09211],[26.17962,69.8253],[27.73229,70.16419],[29.01557,69.76649],[28.59193,69.06478]]]},\"properties\":{\"name\":\"Finland\"}}]}","volume":"13","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":886564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephan, Jörg G.","contributorId":331036,"corporation":false,"usgs":false,"family":"Stephan","given":"Jörg G.","affiliations":[{"id":79096,"text":"SLU Swedish Species Information Centre, Swedish University of Agricultural Sciences, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":886565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drag, Lukas 0000-0002-6002-9214","orcid":"https://orcid.org/0000-0002-6002-9214","contributorId":304151,"corporation":false,"usgs":false,"family":"Drag","given":"Lukas","email":"","affiliations":[{"id":65984,"text":"University of Würzburg","active":true,"usgs":false}],"preferred":false,"id":886566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Potterf, Mária","contributorId":331037,"corporation":false,"usgs":false,"family":"Potterf","given":"Mária","affiliations":[{"id":79097,"text":"Department of Life Science Systems, Technical University of Munich, Freising, Bavaria, Germany","active":true,"usgs":false}],"preferred":false,"id":886567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birkemoe, Tone","contributorId":304154,"corporation":false,"usgs":false,"family":"Birkemoe","given":"Tone","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":886568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siitonen, Juha","contributorId":331038,"corporation":false,"usgs":false,"family":"Siitonen","given":"Juha","email":"","affiliations":[{"id":29898,"text":"Natural Resources Institute Finland (Luke), Helsinki, Finland","active":true,"usgs":false}],"preferred":false,"id":886569,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Müller, Jörg","contributorId":331039,"corporation":false,"usgs":false,"family":"Müller","given":"Jörg","affiliations":[{"id":79099,"text":"Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Rauhenebrach, Germany","active":true,"usgs":false}],"preferred":false,"id":886570,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ovaskainen, Otso 0000-0001-9750-4421","orcid":"https://orcid.org/0000-0001-9750-4421","contributorId":304157,"corporation":false,"usgs":false,"family":"Ovaskainen","given":"Otso","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":886571,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sverdrup-Thygeson, Anne 0000-0002-3122-2250","orcid":"https://orcid.org/0000-0002-3122-2250","contributorId":304161,"corporation":false,"usgs":false,"family":"Sverdrup-Thygeson","given":"Anne","email":"","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":886572,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Snäll, Tord","contributorId":331040,"corporation":false,"usgs":false,"family":"Snäll","given":"Tord","affiliations":[{"id":79096,"text":"SLU Swedish Species Information Centre, Swedish University of Agricultural Sciences, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":886573,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70259657,"text":"70259657 - 2023 - Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i","interactions":[],"lastModifiedDate":"2024-10-19T13:24:47.508554","indexId":"70259657","displayToPublicDate":"2023-10-19T08:23:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i","docAbstract":"

Sustained-yield hunting of introduced ungulates in the Hawaiian Islands often conflicts with the conservation of native species, but there is little reliable data to guide effective management. European mouflon sheep (Ovis musimon; mouflon) and axis deer (Axis axis; deer) were introduced on the island of Lāna‘i to provide additional hunting opportunities. Managers will require better information regarding the ecological associations of introduced ungulate species, relative to the habitats occupied, to resolve longstanding conflicts between native species conservation and sustained-yield hunting on islands. To address this information need, we modeled sheep and deer ecological associations, habitat-use, and suitability using data obtained from an intensive aerial survey completed in 2013 and temporally matching environmental data. In habitat suitability models evaluated by Receiver Operating Characteristic (ROC) metrics, predictor importance in a generalized linear model (GLM) of deer decreased in the following order: afternoon cloud cover, topographic slope, mean annual precipitation (MAP), elevation, normalized difference vegetation index (NDVI), and bare soil index. In a random GLM model of mouflon, predictor importance decreased in the following order: afternoon cloud cover, deer habitat suitability, NDVI, bare soil index, topographic slope, elevation, and MAP. Mouflon were restricted to lower elevation arid slopes, whereas deer were more broadly distributed throughout upland environments of the island. The presence of deer was also an important predictor for mouflon distribution, although mouflon was not an important predictor of deer, suggesting asymmetrical competition. Removal of the more abundant deer population may lead to an increase in abundance and distribution of mouflon without containment. This work represents the first habitat suitability analysis for all nonnative ungulates on any entire Hawaiian island. Our results are applicable to other islands where conflicts may arise with introduced ungulates, sustained-yield hunting, and native species conservation.


","language":"English","publisher":"Berryman Insititute","doi":"10.26077/be03-b519","usgsCitation":"Hess, S.C., Brinck, K., Leopold, C.R., Muise, J., and Sprague, J., 2023, Ecological associations of non-native ungulates on the Hawaiian Island of Lāna‘i: Human-Wildlife Interactions, v. 17, no. 2, 14 p., https://doi.org/10.26077/be03-b519.","productDescription":"14 p.","ipdsId":"IP-134608","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":463043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Lāna‘i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.25852174158157,\n 21.072831141997597\n ],\n [\n -157.25852174158157,\n 20.56423494187817\n ],\n [\n -156.5879617183619,\n 20.56423494187817\n ],\n [\n -156.5879617183619,\n 21.072831141997597\n ],\n [\n -157.25852174158157,\n 21.072831141997597\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hess, Steven C.","contributorId":176679,"corporation":false,"usgs":false,"family":"Hess","given":"Steven","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":916161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":916162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leopold, Christina R","contributorId":345275,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","email":"","middleInitial":"R","affiliations":[{"id":82536,"text":"0000-0003-0499-3196","active":true,"usgs":false}],"preferred":false,"id":916163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muise, Jacob","contributorId":240997,"corporation":false,"usgs":false,"family":"Muise","given":"Jacob","email":"","affiliations":[{"id":48185,"text":"KIA Hawaii","active":true,"usgs":false}],"preferred":false,"id":916164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sprague, Jonathan","contributorId":240998,"corporation":false,"usgs":false,"family":"Sprague","given":"Jonathan","email":"","affiliations":[{"id":48186,"text":"Pulama Lana‘i","active":true,"usgs":false}],"preferred":false,"id":916165,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249692,"text":"70249692 - 2023 - Leaf litter decomposition and detrital communities following the removal of two large dams on the Elwha River (Washington, USA)","interactions":[],"lastModifiedDate":"2023-10-25T13:22:27.176833","indexId":"70249692","displayToPublicDate":"2023-10-19T08:08:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14245,"text":"Frontiers of Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Leaf litter decomposition and detrital communities following the removal of two large dams on the Elwha River (Washington, USA)","docAbstract":"

Large-scale dam removals provide opportunities to restore river function in the long-term and are massive disturbances to riverine ecosystems in the short-term. The removal of two dams on the Elwha River (WA, USA) between 2011 and 2014 was the largest dam removal project to be completed by that time and has since resulted in major changes to channel dynamics, river substrates, in-stream communities, and the size and shape of the river delta. To assess ecosystem function across the restored Elwha watershed, we compared leaf litter decomposition at twenty sites: 1) four tributary sites not influenced by restoration activities; 2) four river sites downstream of the upper dam (Glines Canyon Dam); 3) four river sites within the footprint of the former Aldwell Reservoir upstream of the lower dam (Elwha Dam); 4) four river sites downstream of the lower dam; and 5) four lentic sites in the newly developing Elwha delta. Three major findings emerged: 1) decomposition rates differed among sections of the Elwha watershed, with slowest decomposition rates at the delta sites and fastest decomposition rates just downstream of the upper dam; 2) aquatic macroinvertebrate communities establishing in leaf litterbags differed significantly among sections of the Elwha watershed; and 3) aquatic fungal communities growing on leaf litter differed significantly among sections. Aquatic macroinvertebrate and fungal diversity were sensitive to differences in canopy cover, water chemistry, and river bottom sediments across sites, with a stronger relationship to elevation for aquatic macroinvertebrates. As the Elwha River undergoes recovery following the massive sediment flows associated with dam removal, we expect to see changes in leaf litter processing dynamics and shifts in litter-dependent decomposer communities (both fungal and invertebrate) involved in this key ecosystem process.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1231689","usgsCitation":"LeRoy, C.J., Morley, S.A., Duda, J.J., Zinck, A.A., Lamoureux, P.J., Pennell, C., Bailey, A., Oswell, C., Silva, M., Kamakawiwo’ole, B.K., Hartford, S., Van Der Hout, J., Peters, R., Mahan, R., Stapleton, J., Johnson, R.C., and Foley, M.M., 2023, Leaf litter decomposition and detrital communities following the removal of two large dams on the Elwha River (Washington, USA): Frontiers of Ecology and Evolution, v. 11, 1231689, 17 p., https://doi.org/10.3389/fevo.2023.1231689.","productDescription":"1231689, 17 p.","ipdsId":"IP-154059","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":441841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/fevo.2023.1231689","text":"Publisher Index Page"},{"id":422096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.70384847912715,\n 48.18248970246785\n ],\n [\n -123.69747256054883,\n 47.89956988612926\n ],\n [\n -123.36728352594747,\n 47.903844451880445\n ],\n [\n -123.3573654303813,\n 48.18248970246785\n ],\n [\n -123.70384847912715,\n 48.18248970246785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"LeRoy, Carri J.","contributorId":331098,"corporation":false,"usgs":false,"family":"LeRoy","given":"Carri","email":"","middleInitial":"J.","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":886743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":886744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zinck, Alex A.","contributorId":331099,"corporation":false,"usgs":false,"family":"Zinck","given":"Alex","email":"","middleInitial":"A.","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lamoureux, Paris J.","contributorId":331100,"corporation":false,"usgs":false,"family":"Lamoureux","given":"Paris","email":"","middleInitial":"J.","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pennell, Cameron","contributorId":331101,"corporation":false,"usgs":false,"family":"Pennell","given":"Cameron","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, Ali","contributorId":331102,"corporation":false,"usgs":false,"family":"Bailey","given":"Ali","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886748,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oswell, Caitlyn","contributorId":331103,"corporation":false,"usgs":false,"family":"Oswell","given":"Caitlyn","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886749,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Silva, Mary","contributorId":331104,"corporation":false,"usgs":false,"family":"Silva","given":"Mary","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886750,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kamakawiwo’ole, Brandy K.","contributorId":331105,"corporation":false,"usgs":false,"family":"Kamakawiwo’ole","given":"Brandy","email":"","middleInitial":"K.","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886751,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hartford, Sorrel","contributorId":331106,"corporation":false,"usgs":false,"family":"Hartford","given":"Sorrel","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886752,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Van Der Hout, Jacqueline","contributorId":331107,"corporation":false,"usgs":false,"family":"Van Der Hout","given":"Jacqueline","email":"","affiliations":[{"id":79118,"text":"Environmental Studies Program, The Evergreen State College, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886753,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peters, Roger","contributorId":219502,"corporation":false,"usgs":false,"family":"Peters","given":"Roger","affiliations":[],"preferred":false,"id":886754,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mahan, Rebecca","contributorId":331108,"corporation":false,"usgs":false,"family":"Mahan","given":"Rebecca","email":"","affiliations":[{"id":79121,"text":"Clallam County Department of Community Development, Port Angeles, WA, USA","active":true,"usgs":false}],"preferred":false,"id":886755,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stapleton, Justin","contributorId":241974,"corporation":false,"usgs":false,"family":"Stapleton","given":"Justin","email":"","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":886756,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":886757,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Foley, Melissa M.","contributorId":316727,"corporation":false,"usgs":false,"family":"Foley","given":"Melissa","email":"","middleInitial":"M.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":886758,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70252521,"text":"70252521 - 2023 - Use of physical blockers to control invasive red swamp crayfish in burrows","interactions":[],"lastModifiedDate":"2024-03-27T12:06:47.68054","indexId":"70252521","displayToPublicDate":"2023-10-19T07:05:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Use of physical blockers to control invasive red swamp crayfish in burrows","docAbstract":"The red swamp crayfish Procambarus clarkii is native to the southeast United States\nbut has successfully invaded nearly every continent around the world. Although physical,\nbiological, and chemical controls are employed to reduce or eliminate populations\nin open-water systems, terrestrial burrows provide a potential refuge from aquatic\ncontrol treatments. We conducted burrow trials to test whether two physical blocker\ntreatments would kill P. clarkii in their burrows. Bentonite clay (a sealing agent) and\nexpanding foam (an insulating sealant) were each applied to 37 crayfish burrows,\nand 36 burrows served as treatment controls (i.e., 110 total burrows). Burrows were\nexcavated 48 hr after the application of the physical blockers to assess the status of\ncrayfish in treated and control burrows. There was 74% mortality of crayfish in\noccupied burrows treated with bentonite clay, 62% in burrows treated with expanding\nfoam, and 6% mortality in control burrows. We believe bentonite clay should continue\nto be field-tested; however, because expanding foam is toxic to aquatic organisms and\nis expected to persist in the environment, we do not believe it is a suitable physical\nblocker for the control of invasive crayfish in burrows. Bentonite clay applications\nlikely will not need permits, will mitigate damage to banks and levees caused by\nburrowing crayfish, and can be used with other control agents such as pesticides.\nHowever, the use of physical blockers may be limited at field sites that have burrows\nwith complex morphologies. We believe the use of bentonite clay to control invasive\ncrayfish in terrestrial burrows will provide resource managers with an effective tool\nfor their integrative pest management programs.","language":"English","publisher":"Reabic","doi":"10.3391/mbi.2023.14.4.09","usgsCitation":"Bates, B.L., Allert, A., Wildhaber, M.L., and Stoeckel, J., 2023, Use of physical blockers to control invasive red swamp crayfish in burrows: Management of Biological Invasions, v. 14, no. 4, p. 709-729, https://doi.org/10.3391/mbi.2023.14.4.09.","productDescription":"21 p.","startPage":"709","endPage":"729","ipdsId":"IP-153209","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":441843,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.3391/mbi.2023.14.4.09","text":"Publisher Index Page"},{"id":435147,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96V08D0","text":"USGS data release","linkHelpText":"Crayfish morphometric measurements, burrow attributes and occupancy in response to physical burrow barriers"},{"id":427139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bates, Benjamin Lee 0000-0001-5142-8881","orcid":"https://orcid.org/0000-0001-5142-8881","contributorId":330857,"corporation":false,"usgs":true,"family":"Bates","given":"Benjamin","email":"","middleInitial":"Lee","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":897398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allert, Ann 0000-0001-7063-8016 aallert@usgs.gov","orcid":"https://orcid.org/0000-0001-7063-8016","contributorId":178200,"corporation":false,"usgs":true,"family":"Allert","given":"Ann","email":"aallert@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":897399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":897400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoeckel, Jim","contributorId":299806,"corporation":false,"usgs":false,"family":"Stoeckel","given":"Jim","email":"","affiliations":[],"preferred":false,"id":897401,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249598,"text":"fs20233043 - 2023 - Hydrologic investigations of green infrastructure by the Central Midwest Water Science Center","interactions":[],"lastModifiedDate":"2026-02-09T17:47:45.10106","indexId":"fs20233043","displayToPublicDate":"2023-10-18T16:01:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3043","displayTitle":"Hydrologic Investigations of Green Infrastructure by the Central Midwest Water Science Center","title":"Hydrologic investigations of green infrastructure by the Central Midwest Water Science Center","docAbstract":"

The water management system within developed communities includes stormwater, wastewater, and drinking-water sources and sinks. Each water management system component provides critical services that support public health in these areas. Stormwater can be quite variable and difficult to manage in developed communities because the amount of stormwater that must be routed through a developed area depends on changing land cover and variable precipitation. In addition to flooding concerns, stormwater also is a major cause of water contamination in developed communities because it carries contaminants such as trash, bacteria, heavy metals, and sediments to local waterways. Historically, communities have managed stormwater with gray infrastructure such as street gutters, culverts, sewer systems, and tunnels. Although these structures efficiently capture and route stormwater to a local waterway or treatment plant, they do not filter any contaminants. Furthermore, many older communities have combined storm sewer and sanitary sewer systems. These combined systems result in an excessive amount of wastewater to be treated before being released into receiving water or the untreated waters are released directly to receiving waters during storms.  

Many communities are now incorporating green infrastructure stormwater mitigating solutions—pervious surfaces (allows water through), grassed swales, bioretention basins, and rain gardens—into their stormwater-management systems. Green infrastructure can absorb and filter stormwater where it falls by taking advantage of natural soil and plant storage and filtration capabilities. Thus, green infrastructure projects can potentially reduce the amount of stormwater and the concentration and transport of contaminants. Increasing green infrastructure in a developed community may reduce the requirements for new storm sewer infrastructure, improve the water quality of nearby waterways, and enhance aesthetics. 

The U.S. Geological Survey has partnered with several cooperators to quantify the effects of green infrastructure projects in several developed communities throughout the central Midwest. As part of these green infrastructure projects, the U.S. Geological Survey Central Midwest Water Science Center and cooperators installed, calibrated, and monitored equipment to measure hydrologic responses (including flooding and water movement) and selected water-quality constituents in developed communities.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233043","usgsCitation":"Atkinson, A.A., Heimann, D.C., and Bailey, C.R., 2023, Hydrologic investigations of green infrastructure by the Central Midwest Water Science Center: U.S. Geological Survey Fact Sheet 2023–3043, 4 p., https://doi.org/10.3133/fs20233043.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-147766","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499695,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115581.htm","linkFileType":{"id":5,"text":"html"}},{"id":499694,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115580.htm","linkFileType":{"id":5,"text":"html"}},{"id":421980,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3043/fs20233043.pdf","text":"Report","size":"2.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3043"},{"id":421979,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3043/images"},{"id":421978,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3043/fs20233043.XML","text":"XML"},{"id":421976,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3043/coverthb.jpg"},{"id":421981,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233043/full","text":"HTML","linkFileType":{"id":5,"text":"html"}}],"contact":"

Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL  61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-10-18","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Atkinson, Allison A. 0009-0001-7572-0729 aatkinson@usgs.gov","orcid":"https://orcid.org/0009-0001-7572-0729","contributorId":330979,"corporation":false,"usgs":true,"family":"Atkinson","given":"Allison","email":"aatkinson@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Clinton R. 0000-0003-3951-2268 cbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-3951-2268","contributorId":5457,"corporation":false,"usgs":true,"family":"Bailey","given":"Clinton","email":"cbailey@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241162,"text":"70241162 - 2023 - Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA","interactions":[],"lastModifiedDate":"2023-11-08T11:48:36.011532","indexId":"70241162","displayToPublicDate":"2023-10-18T11:44:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA","docAbstract":"

Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or even thousands of landslide occurrences. This study evaluates strategies for training landslide forecasting models with a scanty record of landslide-triggering events, which is a typical limitation in remote, sparsely populated regions. We evaluate 136 statistical models trained on a precipitation dataset with five landslide-triggering precipitation events recorded near Sitka, Alaska, USA, as well as > 6000 d of non-triggering rainfall (2002–2020). We also conduct extensive statistical evaluation for three primary purposes: (1) to select the best-fitting models, (2) to evaluate performance of the preferred models, and (3) to select and evaluate warning thresholds. We use Akaike, Bayesian, and leave-one-out information criteria to compare the 136 models, which are trained on different cumulative precipitation variables at time intervals ranging from 1 h to 2 weeks, using both frequentist and Bayesian methods to estimate the daily probability and intensity of potential landslide occurrence (logistic regression and Poisson regression). We evaluate the best-fit models using leave-one-out validation as well as by testing a subset of the data. Despite this sparse landslide inventory, we find that probabilistic models can effectively distinguish days with landslides from days without slide activity. Our statistical analyses show that 3 h precipitation totals are the best predictor of elevated landslide hazard, and adding antecedent precipitation (days to weeks) did not improve model performance. This relatively short timescale of precipitation combined with the limited role of antecedent conditions likely reflects the rapid draining of porous colluvial soils on the very steep hillslopes around Sitka. Although frequentist and Bayesian inferences produce similar estimates of landslide hazard, they do have different implications for use and interpretation: frequentist models are familiar and easy to implement, but Bayesian models capture the rare-events problem more explicitly and allow for better understanding of parameter uncertainty given the available data. We use the resulting estimates of daily landslide probability to establish two decision boundaries that define three levels of warning. With these decision boundaries, the frequentist logistic regression model incorporates National Weather Service quantitative precipitation forecasts into a real-time landslide early warning “dashboard” system (https://sitkalandslide.org/, last access: 9 October 2023). This dashboard provides accessible and data-driven situational awareness for community members and emergency managers.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-23-3261-2023","usgsCitation":"Patton, A., Luna, L., Roering, J.J., Jacobs, A., Korup, O., and Mirus, B., 2023, Landslide initiation thresholds in data-sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA: Natural Hazards and Earth System Sciences, v. 23, no. 10, p. 3261-3284, https://doi.org/10.5194/nhess-23-3261-2023.","productDescription":"24 p.","startPage":"3261","endPage":"3284","ipdsId":"IP-148647","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":441845,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-23-3261-2023","text":"Publisher Index Page"},{"id":422429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Sitka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -135.5083890264902,\n 57.18995904083906\n ],\n [\n -135.5083890264902,\n 56.972958920434166\n ],\n [\n -135.177168114468,\n 56.972958920434166\n ],\n [\n -135.177168114468,\n 57.18995904083906\n ],\n [\n -135.5083890264902,\n 57.18995904083906\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Annette","contributorId":303028,"corporation":false,"usgs":false,"family":"Patton","given":"Annette","email":"","affiliations":[{"id":65615,"text":"Sitka Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":866314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luna, Lisa","contributorId":303029,"corporation":false,"usgs":false,"family":"Luna","given":"Lisa","email":"","affiliations":[{"id":52955,"text":"University of Potsdam","active":true,"usgs":false}],"preferred":false,"id":866315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roering, Josh J.","contributorId":303030,"corporation":false,"usgs":false,"family":"Roering","given":"Josh","email":"","middleInitial":"J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":866316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobs, Aaron","contributorId":204855,"corporation":false,"usgs":false,"family":"Jacobs","given":"Aaron","email":"","affiliations":[{"id":36995,"text":"NWS","active":true,"usgs":false}],"preferred":false,"id":866317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korup, Oliver","contributorId":218071,"corporation":false,"usgs":false,"family":"Korup","given":"Oliver","email":"","affiliations":[{"id":39735,"text":"Institute of Earth and Environmental Science, University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":866318,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":866319,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256600,"text":"70256600 - 2023 - Assessing potential spawning locations of Silver Chub in Lake Erie","interactions":[],"lastModifiedDate":"2024-08-23T16:05:33.325572","indexId":"70256600","displayToPublicDate":"2023-10-18T10:57:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing potential spawning locations of Silver Chub in Lake Erie","docAbstract":"

Objective

Silver Chub Macrhybopsis storeriana, a predominately riverine species throughout its native range, exists within Lake Erie as the only known lake population. Its population declined in the 1950s and never fully recovered. Canada has listed Silver Chub in the Great Lakes–St. Lawrence River as endangered and has initiated a recovery plan that recognized the identification of spawning areas as a critical component to inform Silver Chub's recovery potential.

Methods

We investigated potential spawning locations of Silver Chub using capture records, otolith microchemistry, and daily age analysis. Lapillus otolith Sr:Ca ratios from 27 age-0 Silver Chub were used to identify potential spawning areas. Daily ages estimated from lapilli were used to calculate hatch dates, which then were compared with capture data of adults and river flows to further inform potential spawning areas.

Result

The Detroit River (and its nearshore area) was all but ruled out as a potential spawning location. The Maumee, Portage, and Sandusky rivers or their nearshore areas were all possible spawning locations. Projected hatch dates spanned the end of May through the end of June and occurred across a wide range of flows, although some peaks in hatch dates corresponded to flow peaks, indicating recruitment is potentially enhanced by high flows.

Conclusion

Silver Chub spawning period and hypothesized spawning rivers or lacustuaries overlap those of invasive Grass Carp Ctenopharyngodon idella, creating a need to jointly consider Grass Carp control efforts with conservation of Silver Chub when assessing management alternatives. Further research on spawning guild and the use of rivers themselves or nearshore areas influenced by rivers as spawning areas are required to maximize potential for conservation and recovery of Silver Chub.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10870","usgsCitation":"McKenna, J.R., Bowen, A., Farver, J.R., Long, J.M., Miner, J.G., Stott, N.D., and Kocovsky, P.M., 2023, Assessing potential spawning locations of Silver Chub in Lake Erie: North American Journal of Fisheries Management, v. 43, no. 5, p. 1166-1179, https://doi.org/10.1002/nafm.10870.","productDescription":"14 p.","startPage":"1166","endPage":"1179","ipdsId":"IP-139223","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":441847,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10870","text":"Publisher Index Page"},{"id":433107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n 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]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Jorden R.","contributorId":341316,"corporation":false,"usgs":false,"family":"McKenna","given":"Jorden","email":"","middleInitial":"R.","affiliations":[{"id":81722,"text":"Lake Erie Biological Station","active":true,"usgs":false}],"preferred":false,"id":908227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Anjanette","contributorId":341317,"corporation":false,"usgs":false,"family":"Bowen","given":"Anjanette","affiliations":[{"id":81723,"text":"US Fish and Wildlife Service Alpena Fish and Wildlife Conservation Office","active":true,"usgs":false}],"preferred":false,"id":908228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farver, John R.","contributorId":341318,"corporation":false,"usgs":false,"family":"Farver","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miner, Jeffrey G.","contributorId":341319,"corporation":false,"usgs":false,"family":"Miner","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stott, Nathan D.","contributorId":341320,"corporation":false,"usgs":false,"family":"Stott","given":"Nathan","email":"","middleInitial":"D.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":908232,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":908233,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70249600,"text":"70249600 - 2023 - Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019","interactions":[],"lastModifiedDate":"2023-10-20T13:19:06.53518","indexId":"70249600","displayToPublicDate":"2023-10-18T09:23:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019","docAbstract":"

Wet deposition monitoring is a critical part of the long-term monitoring of acid deposition, which aims to assess the ecological impact of anthropogenic emissions of SO2 and NOx. In North America, long-term wet deposition has been monitored through two national networks: the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program (NADP), for Canada and the USA, respectively. In order to assess the comparability of measurements from the two networks, collocated measurements have been made at two sites, one in each country, since 1986 (Sirois et al., in Environmental Monitoring and Assessment, 62, 273–303, 2000; Wetherbee et al., in Environmental Monitoring and Assessment, 1995–2004, 2010). In this study, we compared the measurements from NADP and CAPMoN instrumentation at the collocated sites at the Pennsylvania State University (Penn State), USA, from 1989 to 2016, and Frelighsburg, Quebec, Canada, from 2002 to 2019. We also included in the study the collocated daily-vs-weekly measurements by the CAPMoN network during 1999–2001 and 2016–2017 in order to evaluate the differences in wet concentration of ions due to sampling frequency alone. The study serves as an extension to two previous CAPMoN-NADP inter-comparisons by Sirois et al. (Environmental Monitoring and Assessment, 62, 273–303, 2000) and Wetherbee et al., in (Environmental Monitoring and Assessment, 1995–2004, 2010). At the Penn State University site, for 1986–2019, CAPMoN was higher than NADP for all ions, in terms of weekly concentration, precipitation-weighted annual mean concentration, and annual wet deposition. The precipitation-weighted annual mean concentrations were higher for SO42− (2%), NO3− (12%), NH4+ (16%), H+ (6%), and base cations and Cl− (11–15%). For annual wet deposition, CAPMoN was higher for SO4−2, NO3−, NH4+ and H+ (5–17%), and base cations and Cl− (12–17%) during 1986–2019. At the Frelighsburg site, NADP changed the sample collector in October 2011. For 2002–2011, the relative differences at the Frelighsburg site were positive and similar in magnitude to those at the Penn State site. For 2012–2019, the precipitation-weighted annual mean concentrations were 5–27% lower than NADP, except for H+, which was 23% higher. The change in sample collector by NADP had the largest effect on between-network biases. The comparisons of daily-vs-weekly measurements conducted by the CAPMoN network during 1999–2001 and 2016–2017 show that the weekly measurements were higher than the daily measurements by 1–3% for SO42−, NO3−, and NH4+; 3–9% for Ca2+, Mg2+, Na+, and Cl−; 10–24% for K+; and lower for H+ by 8–30% in terms of precipitation-weighted mean concentration. Thus, differences in sampling frequencies did not contribute to the systematically higher CAPMoN measurements. Understanding the biases in the data for these networks is important for interpretation of continental scale deposition models and transboundary comparison of wet deposition trends.

","language":"English","publisher":"Springer Link","doi":"10.1007/s10661-023-11771-z","usgsCitation":"Feng, J., Cole, A., Wetherbee, G.A., and Banwait, K., 2023, Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986–2019: Environmental Monitoring and Assessment, v. 195, 1333, 34 p., https://doi.org/10.1007/s10661-023-11771-z.","productDescription":"1333, 34 p.","ipdsId":"IP-153496","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":441851,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-023-11771-z","text":"Publisher Index Page"},{"id":422000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"195","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Feng, Jian","contributorId":330980,"corporation":false,"usgs":false,"family":"Feng","given":"Jian","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Amanda","contributorId":330981,"corporation":false,"usgs":false,"family":"Cole","given":"Amanda","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":215100,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":886402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banwait, Kulbir","contributorId":330982,"corporation":false,"usgs":false,"family":"Banwait","given":"Kulbir","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":886403,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249795,"text":"70249795 - 2023 - Florida Kingsnake (Lampropeltis floridana) consumes a juvenile Burmese Python (Python molurus bivitattus) in southern Florida","interactions":[],"lastModifiedDate":"2023-10-28T13:09:17.645288","indexId":"70249795","displayToPublicDate":"2023-10-18T08:06:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3263,"text":"Reptiles & Amphibians","active":true,"publicationSubtype":{"id":10}},"title":"Florida Kingsnake (Lampropeltis floridana) consumes a juvenile Burmese Python (Python molurus bivitattus) in southern Florida","docAbstract":"The Burmese python (Python molurus bivittatus) is an invasive constrictor established across southern Florida. These snakes are dietary generalists with large home ranges and broad habitat requirements and their introduction has had severe impacts on native species and ecosystems in the region. We describe the first observation of a Florida kingsnake (Lampropeltis floridana) that consumed a hatchling Burmese python.","language":"English","publisher":"International Reptile Conservation Foundation","doi":"10.17161/randa.v30i1.19971","usgsCitation":"Crawford, P.F., Torres, J.A., Guzy, J.C., Currylow, A.F., McBride, L.M., Anderson, G.E., McCollister, M.F., Romagosa, C.M., Yackel Adams, A.A., and Hart, K., 2023, Florida Kingsnake (Lampropeltis floridana) consumes a juvenile Burmese Python (Python molurus bivitattus) in southern Florida: Reptiles & Amphibians, v. 30, no. 1, e19971, 3 p., https://doi.org/10.17161/randa.v30i1.19971.","productDescription":"e19971, 3 p.","ipdsId":"IP-151311","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17161/randa.v30i1.19971","text":"Publisher Index Page"},{"id":422230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.11626012922294,\n 26.785704738544794\n ],\n [\n -82.11626012922294,\n 24.8873077357417\n ],\n [\n -79.56743200422333,\n 24.8873077357417\n ],\n [\n -79.56743200422333,\n 26.785704738544794\n ],\n [\n -82.11626012922294,\n 26.785704738544794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, Peter F.","contributorId":331251,"corporation":false,"usgs":false,"family":"Crawford","given":"Peter","email":"","middleInitial":"F.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":887084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torres, Jose A.","contributorId":331252,"corporation":false,"usgs":false,"family":"Torres","given":"Jose","email":"","middleInitial":"A.","affiliations":[{"id":79169,"text":"USGS Cooperative Summer Field Training Program","active":true,"usgs":false}],"preferred":false,"id":887085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":887086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBride, Lisa Marie 0000-0003-4558-5391","orcid":"https://orcid.org/0000-0003-4558-5391","contributorId":303824,"corporation":false,"usgs":true,"family":"McBride","given":"Lisa","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887088,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887089,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCollister, Matthew F.","contributorId":264909,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","email":"","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":887090,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887091,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887092,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":887093,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70252214,"text":"70252214 - 2023 - Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast","interactions":[],"lastModifiedDate":"2024-03-20T11:53:06.811606","indexId":"70252214","displayToPublicDate":"2023-10-18T06:50:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast","docAbstract":"

Arctic coastal environments are eroding and rapidly changing. A lack of pan-Arctic observations limits our ability to understand controls on coastal erosion rates across the entire Arctic region. Here, we capitalize on an abundance of geospatial and remotely sensed data, in addition to model output, from the North Slope of Alaska to identify relationships between historical erosion rates and landscape characteristics to guide future modeling and observational efforts across the Arctic. Using existing datasets from the Alaska Beaufort Sea coast and a hierarchical clustering algorithm, we developed a set of 16 coastal typologies that captures the defining characteristics of environments susceptible to coastal erosion. Relationships between landscape characteristics and historical erosion rates show that no single variable alone is a good predictor of erosion rates. Variability in erosion rate decreases with increasing coastal elevation, but erosion rate magnitudes are highest for intermediate elevations. Areas along the Alaskan Beaufort Sea coast (ABSC) protected by barrier islands showed a three times lower erosion rate on average, suggesting that barrier islands are critical to maintaining mainland shore position. Finally, typologies with the highest erosion rates are not broadly representative of the ABSC and are generally associated with low elevation, north- to northeast-facing shorelines, a peaty pebbly silty lithology, and glaciomarine deposits with high ice content. All else being equal, warmer permafrost is also associated with higher erosion rates, suggesting that warming permafrost temperatures may contribute to higher future erosion rates on permafrost coasts. The suite of typologies can be used to guide future modeling and observational efforts by quantifying the distribution of coastlines with specific landscape characteristics and erosion rates.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ad04b8","usgsCitation":"Piliouras, A., Jones, B.M., Clevenger, T., Gibbs, A.E., and Rowland, J.C., 2023, Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast: Environmental Research Letters, v. 18, 114050, 10 p., https://doi.org/10.1088/1748-9326/ad04b8.","productDescription":"114050, 10 p.","ipdsId":"IP-141537","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad04b8","text":"Publisher Index Page"},{"id":426794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160.82972953158225,\n 72.33792024202972\n ],\n [\n -160.82972953158225,\n 68.87395946820305\n ],\n [\n -140.35121390658202,\n 68.87395946820305\n ],\n [\n -140.35121390658202,\n 72.33792024202972\n ],\n [\n -160.82972953158225,\n 72.33792024202972\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2023-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Piliouras, Anastasia","contributorId":334927,"corporation":false,"usgs":false,"family":"Piliouras","given":"Anastasia","email":"","affiliations":[{"id":80287,"text":"Department of Geosciences, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":896945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M.","contributorId":305542,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":896946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clevenger, Tabatha","contributorId":334928,"corporation":false,"usgs":false,"family":"Clevenger","given":"Tabatha","email":"","affiliations":[{"id":80288,"text":"Department of Earth Science and Geography, Vassar College, Poughkeepsie, NY","active":true,"usgs":false}],"preferred":false,"id":896947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":896948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowland, Joel C.","contributorId":169046,"corporation":false,"usgs":false,"family":"Rowland","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":896949,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257232,"text":"70257232 - 2023 - Advances in wildlife abundance estimation using pedigree reconstruction","interactions":[],"lastModifiedDate":"2024-08-14T11:42:08.512608","indexId":"70257232","displayToPublicDate":"2023-10-18T06:38:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Advances in wildlife abundance estimation using pedigree reconstruction","docAbstract":"

The conservation and management of wildlife populations, particularly for threatened and endangered species are greatly aided with abundance, growth rate, and density measures. Traditional methods of estimating abundance and related metrics represent trade-offs in effort and precision of estimates. Pedigree reconstruction is an emerging, attractive alternate approach because its use of one-time, noninvasive sampling of individuals to infer the existence of unsampled individuals. However, advances in pedigree reconstruction could improve its utility, including forming a measure of precision for the method, establishing required spatial sampling effort for accurate estimates, ascertaining the spatial extent of abundance estimates derived from pedigree reconstruction, and assessing how population density affects the estimator's performance. Using established relationships for a stochastic, spatially explicit simulated moose (Alces americanus) population, pedigree reconstruction provided accurate estimates of the adult moose population size and trend. Novel bootstrapped confidence intervals performed as expected with intensive sampling but underperformed with moderate sampling efforts that could produce abundance estimates with low bias. Adult population estimates more closely reflected the total number of adults in the extant population, rather than number of adults inhabiting the area where sampling occurred. Increasing sampling effort, measured as the proportion of individuals sampled and as the proportion of a hypothetical study area, yielded similar asymptotic patterns over time. Simulations indicated a positive relationship between animal density and sampling effort required for unbiased estimates. These results indicate that pedigree reconstruction can produce accurate abundance estimates and may be particularly valuable for surveying smaller areas and low-density populations.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10650","usgsCitation":"Rosenblatt, E., Creel, S., Gieder, K., Murdoch, J., and Donovan, T.M., 2023, Advances in wildlife abundance estimation using pedigree reconstruction: Ecology and Evolution, v. 13, no. 10, e10650, 18 p., https://doi.org/10.1002/ece3.10650.","productDescription":"e10650, 18 p.","ipdsId":"IP-139722","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10650","text":"Publisher Index Page"},{"id":432645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenblatt, Elias","contributorId":342124,"corporation":false,"usgs":false,"family":"Rosenblatt","given":"Elias","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":909736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creel, Scott","contributorId":342128,"corporation":false,"usgs":false,"family":"Creel","given":"Scott","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":909738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gieder, Katherina","contributorId":342131,"corporation":false,"usgs":false,"family":"Gieder","given":"Katherina","affiliations":[{"id":27622,"text":"Vermont Fish and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":909739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murdoch, James","contributorId":342134,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":909740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":909741,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269403,"text":"70269403 - 2023 - High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems","interactions":[],"lastModifiedDate":"2025-07-22T14:48:02.96331","indexId":"70269403","displayToPublicDate":"2023-10-18T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems","docAbstract":"

We rarely consider light limitation in ecosystem productivity, yet light limitation is a major constraint on river autotrophy. Because the light that reaches benthic autotrophs must first pass through terrestrial vegetation and an overlying water column that can be loaded with sediments or colored organic material, there is strong selection for river autotrophs to have high light use efficiencies (LUEs), that is, the efficiency at which light energy is converted to biomass. In contrast to prior studies that have estimated river LUE on single days, we calculated continuous LUE over more than 6 full years for 64 free-flowing rivers across the United States. This dataset represents the largest compilation of continuous estimates of daily rates of gross primary productivity (GPP) and daily light inputs from which we calculated daily estimates of LUE. Early estimates of LUE in rivers found that clearwater springs with stable flows could achieve LUEs of 4%, much higher than LUEs reported for terrestrial plants. We found that 53% of the rivers in our dataset have LUEs that exceed 4% on at least one day of their time series. Because of the high variability in daily LUE, measurements taken on any given day may misrepresent a river ecosystem's annual LUE. Though most rivers share a high potential, the mean annual LUE of all rivers in our dataset is much lower, only 0.5%. We found that rivers with more variable flow regimes had lower annual LUEs, which indicates that LUE is constrained by hydrologic disturbances that remove, bury, or shade autotrophic biomass. Comparisons of LUE across ecosystems allow us to reframe our view of rivers, by recognizing the high efficiency with which they convert light to biomass compared with lentic, marine, and terrestrial ecosystems.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4659","usgsCitation":"Thellman, A., Savoy, P., and Bernhardt, E., 2023, High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems: Ecosphere, v. 14, no. 10, e4659, 9 p., https://doi.org/10.1002/ecs2.4659.","productDescription":"e4659, 9 p.","ipdsId":"IP-151660","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":492879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4659","text":"Publisher Index Page"},{"id":492731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n 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lakes","interactions":[],"lastModifiedDate":"2024-08-12T14:56:10.530072","indexId":"70256500","displayToPublicDate":"2023-10-17T09:48:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18328,"text":"Frontiers in Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fish life-history traits predict abundance-occupancy patterns in artificial lakes","docAbstract":"

Life-history traits of a species have been postulated as a factor in abundance and occupancy patterns. Understanding how traits contribute to the ubiquity and rarity of taxa can facilitate the development of effective conservation policy by establishing a connection between species requirements and resource. The goal was to evaluate fish assemblages in artificial lakes for evidence of the abundance-occupancy patterns reported in natural environments and, if evident, to explore if observed patterns of abundance and occupancy could be attributed to species traits. Fish abundance and occupancy were estimated over 1990–2018 in 22 artificial lakes impounded within the Tennessee River basin, USA. Consistent with reports for many other taxonomic groups in natural environments, there was a positive association amidst 114 fish species between abundance and occupancy in artificial lakes (R2 = 0.78). This result indicates that the fish assemblages that develop in these anthropized environments follow the fundamental abundance-occupancy patterns uncovered in natural environments, despite assemblages having been disfigured by the dramatic rearrangement of habitats brought by impoundment. Moreover, a redundancy analysis focusing mostly on reproductive and habitat traits adequately predicted abundance-occupancy patterns of fish assemblages in artificial lakes (R2 = 0.69). Species abundance-occupancy is influenced by the interplay between life-history traits and habitat availability, even in artificial lakes, and by extension, possibly other artificial ecosystems.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffwsc.2023.1270939","usgsCitation":"Miranda, L.E., 2023, Fish life-history traits predict abundance-occupancy patterns in artificial lakes: Frontiers in Freshwater Science, v. 1, 1270939, 9 p., https://doi.org/10.3389/ffwsc.2023.1270939.","productDescription":"1270939, 9 p.","ipdsId":"IP-155049","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/ffwsc.2023.1270939","text":"Publisher Index Page"},{"id":432486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabame, Georgia, Kentucky, Mississippi, North Carolina, Tennessee, Virginia","otherGeospatial":"Tennessee River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.71853058052089,\n 36.417865012804256\n ],\n [\n -88.01805823954074,\n 37.068175622572426\n ],\n [\n -88.5039106745598,\n 36.97105864199936\n ],\n [\n -88.16082450902296,\n 36.19663882041334\n ],\n [\n -88.32274922263527,\n 34.72002280226771\n ],\n [\n -85.82977660734407,\n 34.31592129522848\n ],\n [\n -84.85626355348249,\n 34.81392356154679\n ],\n [\n -84.3271421583876,\n 35.07256459313197\n ],\n [\n -83.4163366401158,\n 34.40943382347814\n ],\n [\n -81.57660967502278,\n 35.63205440342975\n ],\n [\n -80.94496328446938,\n 36.7865912817942\n ],\n [\n -81.34468565872093,\n 36.99713207425954\n ],\n [\n -82.10618545728924,\n 36.61910300314784\n ],\n [\n -84.22694404251676,\n 36.05281390065235\n ],\n [\n -84.53649174113569,\n 35.51939544911066\n ],\n [\n -87.71853058052089,\n 36.417865012804256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationDate":"2023-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907688,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249484,"text":"cir1513 - 2023 - Woods Hole Coastal and Marine Science Center—2022 annual report","interactions":[],"lastModifiedDate":"2023-12-14T21:00:32.188771","indexId":"cir1513","displayToPublicDate":"2023-10-17T08:40:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1513","displayTitle":"Woods Hole Coastal and Marine Science Center—2022 Annual Report","title":"Woods Hole Coastal and Marine Science Center—2022 annual report","docAbstract":"

The 2022 annual report of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center highlights accomplishments of 2022, includes a list of 2022 publications, and summarizes the work of the center, as well as the work of each of its science groups. This product allows readers to gain a general understanding of the focus areas of the center’s scientific research and learn more about specific projects and progress made throughout 2022, all while enjoying photographs taken in various environments and laboratories, and applicable maps and figures.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1513","isbn":"978-1-4113-4536-2","usgsCitation":"Ernst, S., 2023, Woods Hole Coastal and Marine Science Center—2022 annual report: U.S. Geological Survey Circular 1513, 36 p., https://doi.org/10.3133/cir1513.","productDescription":"iv, 36 p.","numberOfPages":"36","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-151468","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":421834,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1513/cir1513.XML"},{"id":421833,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1513/images/"},{"id":421832,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1513/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1513"},{"id":421831,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1513/cir1513.pdf","text":"Report","size":"8.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1513"},{"id":421830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1513/coverthb.jpg"}],"contact":"

Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-10-17","noUsgsAuthors":false,"publicationDate":"2023-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ernst, Sara 0000-0001-7825-3209","orcid":"https://orcid.org/0000-0001-7825-3209","contributorId":215923,"corporation":false,"usgs":true,"family":"Ernst","given":"Sara","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":885899,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70252187,"text":"70252187 - 2023 - Respiratory acclimation of tropical forest roots in response to in situ experimental warming and hurricane disturbance","interactions":[],"lastModifiedDate":"2024-03-19T11:44:29.944909","indexId":"70252187","displayToPublicDate":"2023-10-17T06:41:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Respiratory acclimation of tropical forest roots in response to in situ experimental warming and hurricane disturbance","docAbstract":"

Climate projections predict higher temperatures and more frequent hurricanes in the tropics. Tropical plants subjected to these stresses may respond by acclimating their physiology. We investigated tropical forest root respiration in response to in situ experimental warming and hurricane disturbance in eastern Puerto Rico. We measured mass-normalized root specific respiration, root biomass, and root traits at the Tropical Responses to Altered Climate Experiment (TRACE), where understory vegetation is warmed + 4 °C above ambient. Our measurements span 5 years, including before and after two major hurricanes, to quantify root contributions to ecosystem carbon fluxes. Experimental warming did not affect root specific respiration at a standard temperature of 25° (RSR25, mean = 3.89 nmol CO2 g−1 s−1) or the temperature sensitivity of root respiration (Q10, mean = 1.75), but did result in decreased fine-root biomass, thereby decreasing area-based estimations of ecosystem-level root respiration in warmed plots by ~ 35%. RSR25 of newer roots, which increased with increasing root nitrogen, showed greater rates 6 months after the hurricanes, but subsequently decreased after 12 months. Root specific respiration did not acclimate to higher temperatures, based on lack of adjustments in either Q10 or RSR25 in the warmed plots; however, decreased root biomass indicates the root contribution to soil carbon dioxide efflux was overall lower with warming. Lower root biomass may also limit nutrient and water uptake, having potential negative effects on carbon assimilation. Our results show that warming and hurricane disturbance have strong potential to affect tropical forest roots, as well as ecosystem carbon fluxes.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-023-00880-y","usgsCitation":"Tunison, R., Wood, T.E., Reed, S., and Cavaleri, M.A., 2023, Respiratory acclimation of tropical forest roots in response to in situ experimental warming and hurricane disturbance: Ecosystems, v. 27, p. 168-184, https://doi.org/10.1007/s10021-023-00880-y.","productDescription":"17 p.","startPage":"168","endPage":"184","ipdsId":"IP-155528","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":426764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","noUsgsAuthors":false,"publicationDate":"2023-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tunison, Rob","contributorId":334894,"corporation":false,"usgs":false,"family":"Tunison","given":"Rob","email":"","affiliations":[{"id":80283,"text":"College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, Michigan, USA","active":true,"usgs":false}],"preferred":false,"id":896867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":896868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":896869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cavaleri, Molly A.","contributorId":206282,"corporation":false,"usgs":false,"family":"Cavaleri","given":"Molly","email":"","middleInitial":"A.","affiliations":[{"id":34284,"text":"School of Forest Resources and Environmental Science, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":896870,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256170,"text":"70256170 - 2023 - The Mojave section of the San Andreas fault (California), 1: Shaping the terrace stratigraphy of Littlerock Creek through the competition between rapid strike-slip faulting and lateral stream erosion over the last 40ka.","interactions":[],"lastModifiedDate":"2024-07-26T00:13:41.320242","indexId":"70256170","displayToPublicDate":"2023-10-16T19:11:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7143,"text":"Geochemistry, Geophysics, and Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"The Mojave section of the San Andreas fault (California), 1: Shaping the terrace stratigraphy of Littlerock Creek through the competition between rapid strike-slip faulting and lateral stream erosion over the last 40ka.","docAbstract":"

To determine the post-40 ka slip-rate along the Mojave section of the San Andreas Fault (MSAF) we re-analyze the sedimentary record preserved where Little Rock (LR) Creek flows across the fault. At this location, interaction between the northeast-flowing stream and right-lateral fault has resulted in the abandonment and preservation of 11 strath terraces and one paleo-floodplain in the downstream trailing corner of the river, two of which are also preserved upstream to provide cross-fault matches. A new model of fault-induced river deflection, together with standard terrace riser restoration, yields strike-slip displacements of 1,140 ± 160 m for the older terrace and 360 ± 70 m for the younger one. When combined with new 10Be dating and reinterpretation of prior measurements the displaced terraces yield right-lateral slip-rates of 27.7+6.9/−3.5 and 26.8+3.4/−3.0 mm/yr over the last 23 k.y. and last 40 k.y., where uncertainties are at 95% credible intervals. These new rate determinations are consistent with independent late Holocene estimates, indicating that the long-term rate of strain accumulation along the MSAF is relatively fast and does not vary significantly when averaged over timescales of 15–20 k.y. Using our new model of stream deflection, we find that the fluvial sequence was emplaced in two distinct periods, each characterized by a temporally stable but markedly different deflected river geometry. Each period coincides with a distinct stage of erosive power along LR Creek determined from independent paleoclimate proxies. Importantly, application of the new river-deflection model allows strike-slip displacements to be determined in the absence of upstream piercing points.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC010869","usgsCitation":"Moulin, A., Cowgill, E., Scharer, K., McPhillips, D., and Heimsath, A., 2023, The Mojave section of the San Andreas fault (California), 1: Shaping the terrace stratigraphy of Littlerock Creek through the competition between rapid strike-slip faulting and lateral stream erosion over the last 40ka.: Geochemistry, Geophysics, and Geosystems, v. 24, no. 10, e2023GC010869, 40 p., https://doi.org/10.1029/2023GC010869.","productDescription":"e2023GC010869, 40 p.","ipdsId":"IP-154087","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":441866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc010869","text":"Publisher Index Page"},{"id":431456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.8640320695366,\n 34.6946394144248\n ],\n [\n -117.8640320695366,\n 33.13569579634151\n ],\n [\n -115.44703988203676,\n 33.13569579634151\n ],\n [\n -115.44703988203676,\n 34.6946394144248\n ],\n [\n -117.8640320695366,\n 34.6946394144248\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Moulin, Adrien","contributorId":340360,"corporation":false,"usgs":false,"family":"Moulin","given":"Adrien","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":906968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowgill, Eric","contributorId":192850,"corporation":false,"usgs":false,"family":"Cowgill","given":"Eric","affiliations":[],"preferred":false,"id":906969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":906970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McPhillips, Devin 0000-0003-1987-9249","orcid":"https://orcid.org/0000-0003-1987-9249","contributorId":217362,"corporation":false,"usgs":true,"family":"McPhillips","given":"Devin","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":906971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heimsath, Arjun","contributorId":340361,"corporation":false,"usgs":false,"family":"Heimsath","given":"Arjun","email":"","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":906972,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249501,"text":"sir20235089 - 2023 - Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, Mojave River and Morongo Areas, western Mojave Desert, southern California","interactions":[],"lastModifiedDate":"2026-03-12T21:10:49.839691","indexId":"sir20235089","displayToPublicDate":"2023-10-16T13:41:24","publicationYear":"2023","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":"2023-5089","displayTitle":"Arsenic, Chromium, Uranium, and Vanadium in Rock, Alluvium, and Groundwater, Mojave River and Morongo Areas, Western Mojave Desert, Southern California","title":"Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, Mojave River and Morongo Areas, western Mojave Desert, southern California","docAbstract":"

Trace elements within groundwater that originate from aquifer materials and pose potential public-health hazards if consumed are known as geogenic contaminants. The geogenic contaminants arsenic, chromium, and vanadium can form negatively charged ions with oxygen known as oxyanions. Uranium complexes with bicarbonate and carbonate to form negatively charged ions having aqueous chemistry similar to oxyanions. The concentrations of arsenic, chromium, uranium, and vanadium in groundwater result from the combined effects of (1) geologic abundance within aquifer materials; (2) the fraction of these elements that have weathered from and sorbed to the surfaces of mineral grains and are potentially available to groundwater; and (3) the aqueous chemistry of dissolved oxyanions in groundwater during different redox conditions and pH, both of which are affected by hydrogeology, including the length of time groundwater has been in contact with aquifer materials. Concentrations of arsenic, chromium, uranium, and vanadium were measured in samples of (1) rock, surficial alluvium, and drill cuttings using portable (handheld) X-ray fluorescence (pXRF); (2) operationally defined fractions extractable from these materials; and (3) water from wells sampled between 2000 and 2018 within the 3,500 square mile Mojave River area and Morongo area of the western Mojave Desert, southern California.

Regionally, rock and surficial alluvium in the Mojave River and Morongo areas are high in arsenic, low in chromium and uranium, and near the average bulk continental crust concentration for vanadium. Locally, high chromium concentrations are present in mafic rock within the San Gabriel Mountains; high uranium concentrations are present in felsic rock within the San Bernardino Mountains; and high arsenic, uranium, and vanadium concentrations are present in extrusive (volcanic) felsic rock within uplands surrounding groundwater basins along the Mojave River downstream from Barstow, California. Elemental assemblages identified using principal component analyses (PCA) of pXRF data were used to characterize felsic, mafic, and felsic volcanic source terranes in rock, surficial alluvium, and in geologic material penetrated by selected monitoring wells drilled between 1994 and 2018. Highly felsic alluvium associated with recent deposition from the Mojave River was identified along the 90-mile length of the floodplain aquifer along the river. The thickness of these highly felsic alluvial deposits ranged from 200 feet (ft) near Victorville and near Barstow to a thin veneer about 30 ft thick downstream from Victorville and downstream portions of the floodplain aquifer within the Mojave Valley.

Groundwater in the Mojave River and Morongo areas was generally oxic and alkaline (pH≥7.5). Maximum concentrations of arsenic, hexavalent chromium [Cr(VI)], uranium, and vanadium in water from as many as 498 wells sampled between 2000 and 2018 were 360, 140, 1,470, and 690 micrograms per liter (μg/L), respectively. Water from 22 percent of sampled wells exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for arsenic of 10 μg/L, with arsenic concentrations commonly exceeding the MCL in water from wells east of Barstow, deep wells in the Victorville fan, and in suboxic or reduced groundwater within the floodplain aquifer. Water from about 1 percent of sampled wells had Cr(VI) concentrations greater than the California MCL for total chromium of 50 μg/L, whereas 13 percent of sampled wells had Cr(VI) concentrations greater than the former California MCL of 10 μg/L. Hexavalent chromium concentrations were highest in water from wells in the Sheep Creek alluvial fan, eroded from mafic rock in the San Gabriel Mountains, although Cr(VI) concentrations greater than the former California MCL also were present elsewhere in the study area where mafic materials or older groundwater were present. Water from about 9 percent of sampled wells exceeded the EPA MCL for uranium of 30 μg/L, with concentrations exceeding the MCL commonly associated with irrigation return from agricultural land overlying the floodplain aquifer. Water from about 7 percent of sampled wells had vanadium concentrations greater than the California notification level of 50 μg/L; most of these wells were in the Victorville fan within the Mojave River area. In general, arsenic concentrations were higher in suboxic or reduced water; chromium concentrations were higher in oxic, alkaline (pH≥7.5) water; uranium concentrations were higher in circumneutral to slightly alkaline water (pH≤7.4); and vanadium concentrations were higher in highly alkaline (pH≥8.0) water, independent of redox status.

Concentrations within geologic source terranes are not the sole factor controlling the concentrations of geogenic elements in groundwater. Differences in mineral weathering, pH-dependent sorption to surface-exchange sites on mineral grains, and aqueous geochemistry (especially redox status and pH) affect geogenic element concentrations in groundwater. Consequently, the relative abundances of arsenic, Cr(VI), uranium, and vanadium in groundwater differ from their relative abundances in the average bulk continental crust and their regional abundances in rock and surficial alluvium within groundwater basins of the western Mojave Desert. Processes that control the concentrations of arsenic, chromium, uranium, and vanadium in groundwater operate at the mineral-grain and aquifer scale.

At the mineral-grain scale, sequential chemical extraction data show arsenic and uranium are more available to groundwater (under specific geochemical conditions) than chromium or vanadium, which largely are unavailable within unweathered mineral grains. Additionally, chromium and vanadium form few aqueous complexes and bind tightly with iron minerals within surface coatings on mineral grains making them less available to groundwater, whereas complexation with other dissolved ions enhances the solubility of uranium and, to a lesser extent, arsenic. Complexation also increases the valence (less negative charge) and increases the size of dissolved oxyanions and uranium complexes with bicarbonate and carbonate making them less readily sorbed to aquifer materials.

At the aquifer scale, hydrogeology (including isolation of water in aquifers from surface sources of recharge, older groundwater age, and long contact times between groundwater and aquifer materials) combined with geochemical processes (such as silicate weathering) to produce alkaline groundwater. Desorption from sorption sites on the surfaces of mineral grains with increasing pH increases arsenic, chromium, and vanadium concentrations in water from wells and increases Cr(VI) concentrations as long as water remains oxic.

Aqueous geochemistry and concentrations of geogenic contaminants also are affected by anthropogenic activities including (1) discharge of treated municipal wastewater, which may change the redox status of groundwater; (2) return from irrigated agriculture, which may alter the chemistry of groundwater and increase the solubility of trace elements such as uranium; and (3) groundwater pumping and subsequent water-level declines, which may change the source of water yielded by wells. The quality of water imported from northern California and infiltrated from ponds for groundwater recharge may be altered by naturally present trace elements, especially uranium in areas of agricultural land use or chromium within mafic alluvium.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235089","collaboration":"Prepared in cooperation with the Mojave Water Agency","programNote":"U.S. Geological Survey Cooperative Water Program","usgsCitation":"Izbicki, J.A., Groover, K.D., and Seymour, W.A., 2023, Arsenic, chromium, uranium, and vanadium in rock, alluvium, and groundwater, western Mojave Desert, southern California: U.S. Geological Survey Scientific Investigations Report 2023–5089, 96 p., https://doi.org/10.3133/sir20235089.","productDescription":"Report: xiii, 96 p., 3 Data Releases; 2 Tables","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101005","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501053,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115509.htm","linkFileType":{"id":5,"text":"html"}},{"id":421873,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table2.1.csv","text":"Table 2.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Identification and National Water Information System Record Numbers for Wells Sampled in the Mojave River and Morongo Groundwater Basins as Part of This Study July 2016 to October 2016 and for Wells Sampled as Part of the Groundwater Ambient Monitoring Assessment Program Priority Basin Project Mojave Basin Domestic-Supply Aquifer Study January to May 2018 western Mojave Desert southern California"},{"id":421877,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C7U6DW","text":"USGS Data Release","description":"Groover, K.D., Goldrath, D.A., Bennett, G.L., Johnson, T.D., and Watson, E.E., 2019, Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project: U.S. Geological Survey data release, https://doi.org/10.5066/P9C7U6DW.","linkHelpText":"Groundwater-quality data in the Mojave Basin Shallow Aquifer Study Unit, 2018—Results from the California GAMA Priority Basin Project"},{"id":421878,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://ca.water.usgs.gov/mojave/mojave-water-quality.html","text":"USGS Data Release","description":"Metzger, L.F., Landon, M.K., House, S.F., and Olsen, L.D., 2015, Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://ca.water.usgs.gov/mojave/mojave-water-quality.html.","linkHelpText":"Mapping selected trace elements and major ions, 2000–2012, Mojave River and Morongo Groundwater Basins, Southwestern Mojave Desert, San Bernardino County, California"},{"id":421923,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235089/full"},{"id":421973,"rank":10,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir_20235089.pdf","text":"Report","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5089/covrthb.jpg"},{"id":421871,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089.xml"},{"id":421872,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5089/sir20235089_table1.1.csv","text":"Table 1.1","size":"3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Boreholes having portable (handheld) X-ray fluoresence (pXRF) data from drill cuttings, Mojave River and Morongo groundwater basins, western Mojave Desert, southern California"},{"id":421874,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5089/images"},{"id":421876,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CU0EH3","text":"USGS Data Release","description":"Groover, K.D., and Izbicki, J.A., 2018, Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9CU0EH3.","linkHelpText":"Field portable X-ray fluorescence and associated quality control data for the western Mojave Desert, San Bernardino County, California"}],"country":"United States","state":"California","otherGeospatial":"Western Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.4,\n 35.2\n ],\n [\n -117.4,\n 34.00\n ],\n [\n -116.0,\n 34\n ],\n [\n -116,\n 35.2\n ],\n [\n -117.4,\n 35.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-10-16","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":885965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groover, Krishangi D. 0000-0002-5805-8913 kgroover@usgs.gov","orcid":"https://orcid.org/0000-0002-5805-8913","contributorId":5626,"corporation":false,"usgs":true,"family":"Groover","given":"Krishangi","email":"kgroover@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":885966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seymour, Whitney A. 0000-0002-5999-6573 wseymour@usgs.gov","orcid":"https://orcid.org/0000-0002-5999-6573","contributorId":4131,"corporation":false,"usgs":true,"family":"Seymour","given":"Whitney","email":"wseymour@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":885967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252802,"text":"70252802 - 2023 - The 1886 Charleston, South Carolina, Earthquake: Relic railroad offset reveals rupture","interactions":[],"lastModifiedDate":"2024-04-05T14:44:12.872874","indexId":"70252802","displayToPublicDate":"2023-10-16T09:42:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"The 1886 Charleston, South Carolina, Earthquake: Relic railroad offset reveals rupture","docAbstract":"

In the absence of documented surface rupture during the 1 September 1886 Charleston earthquake, there has been considerable speculation about the location and mechanism of the causative fault. We use an inferred coseismic offset of the South Carolina Railroad and additional numerical constraints to develop an elastic deformation model—a west‐dipping fault following strands of two previously identified faults. The constraints are consistent with a blind rupture with 6.5 ± 0.3 m of dextral slip and 2 ± 0.5 m of reverse slip below 450 m depth. We propose that repeated slip on this fault has raised the Penholoway Marine Terrace >6 m since ∼770 ka. The inferred coseismic slip on the fault in an Mw 7.3 earthquake is consistent with the distribution of damage in 1886.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230022","usgsCitation":"Bilham, R., and Hough, S.E., 2023, The 1886 Charleston, South Carolina, Earthquake: Relic railroad offset reveals rupture: The Seismic Record, v. 3, no. 4, p. 278-288, https://doi.org/10.1785/0320230022.","productDescription":"11 p.","startPage":"278","endPage":"288","ipdsId":"IP-152926","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":441868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230022","text":"Publisher Index Page"},{"id":427514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.24634165513044,\n 33.088760020667124\n ],\n [\n -80.24634165513044,\n 32.62202807250516\n ],\n [\n -79.75159258126686,\n 32.62202807250516\n ],\n [\n -79.75159258126686,\n 33.088760020667124\n ],\n [\n -80.24634165513044,\n 33.088760020667124\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":898271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":898272,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256086,"text":"70256086 - 2023 - BatTool: Projecting bat populations facing multiple stressors using a demographic model","interactions":[],"lastModifiedDate":"2024-07-19T11:57:51.992521","indexId":"70256086","displayToPublicDate":"2023-10-16T06:55:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"BatTool: Projecting bat populations facing multiple stressors using a demographic model","docAbstract":"

Bats provide ecologically and agriculturally important ecosystem services but are currently experiencing population declines caused by multiple environmental stressors, including mortality from white-nose syndrome and wind energy development. Analyses of the current and future health and viability of these species may support conservation management decision making. Demographic modeling provides a quantitative tool for decision makers and conservation managers to make more informed decisions, but widespread adoption of these tools can be limited because of the complexity of the mathematical, statistical, and computational components involved in implementing these models. In this work, we provide an exposition of the BatTool R package, detailing the primary components of the matrix projection model, a publicly accessible graphical user interface (https://rconnect.usgs.gov/battool) facilitating user-defined scenario analyses, and its intended uses and limitations (Wiens et al., US Geol Surv Data Release 2022; Wiens et al., US Geol Surv Softw Release 2022). We present a case study involving wind energy permitting, weighing the effects of potential mortality caused by a hypothetical wind energy facility on the projected abundance of four imperiled bat species in the Midwestern United States.

","language":"English","publisher":"British Ecological Society","doi":"10.1186/s12862-023-02159-1","usgsCitation":"Wiens, A.M., Schorg, A., Szymanski, J., and Thogmartin, W.E., 2023, BatTool: Projecting bat populations facing multiple stressors using a demographic model: Methods in Ecology and Evolution, v. 23, 61, 16 p., https://doi.org/10.1186/s12862-023-02159-1.","productDescription":"61, 16 p.","ipdsId":"IP-132438","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12862-023-02159-1","text":"Publisher Index Page"},{"id":431237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","noUsgsAuthors":false,"publicationDate":"2023-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":906644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schorg, Amber","contributorId":333055,"corporation":false,"usgs":false,"family":"Schorg","given":"Amber","email":"","affiliations":[{"id":68344,"text":"U.S. Fish and Wildlife Service (USFWS)","active":true,"usgs":false}],"preferred":false,"id":906645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymanski, Jennifer","contributorId":15123,"corporation":false,"usgs":false,"family":"Szymanski","given":"Jennifer","affiliations":[{"id":6969,"text":"U.S. Fish and Wildlife Service, Division of Endangered Species","active":true,"usgs":false}],"preferred":false,"id":906646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":906647,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249590,"text":"70249590 - 2023 - Snowpack relative permittivity and density derived from near-coincident lidar and ground-penetrating radar","interactions":[],"lastModifiedDate":"2023-10-18T11:59:10.643012","indexId":"70249590","displayToPublicDate":"2023-10-16T06:55:05","publicationYear":"2023","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":"Snowpack relative permittivity and density derived from near-coincident lidar and ground-penetrating radar","docAbstract":"

Depth-based and radar-based remote sensing methods (e.g., lidar, synthetic aperture radar) are promising approaches for remotely measuring snow water equivalent (SWE) at high spatial resolution. These approaches require snow density estimates, obtained from in-situ measurements or density models, to calculate SWE. However, in-situ measurements are operationally limited, and few density models have seen extensive evaluation. Here, we combine near-coincident, lidar-measured snow depths with ground-penetrating radar (GPR) two-way travel times (twt) of snowpack thickness to derive >20 km of relative permittivity estimates from nine dry and two wet snow surveys at Grand Mesa, Cameron Pass, and Ranch Creek, Colorado. We tested three equations for converting dry snow relative permittivity to snow density and found the Kovacs et al. (1995) equation to yield the best comparison with in-situ measurements (RMSE = 54 kg m−3). Variogram analyses revealed a 19 m median correlation length for relative permittivity and snow density in dry snow, which increased to >30 m in wet conditions. We compared derived densities with estimated densities from several empirical models, the Snow Data Assimilation System (SNODAS), and the physically based iSnobal model. Estimated and derived densities were combined with snow depths and twt to evaluate density model performance within SWE remote sensing methods. The Jonas et al. (2009) empirical model yielded the most accurate SWE from lidar snow depths (RMSE = 51 mm), whereas SNODAS yielded the most accurate SWE from GPR twt (RMSE = 41 mm). Densities from both models generated SWE estimates within ±10% of derived SWE when SWE averaged >400 mm, however, model uncertainty increased to >20% when SWE averaged <300 mm. The development and refinement of density models, particularly in lower SWE conditions, is a high priority to fully realize the potential of SWE remote sensing methods.

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R.","contributorId":306269,"corporation":false,"usgs":false,"family":"Fassnacht","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":886349,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Webb, Ryan","contributorId":330966,"corporation":false,"usgs":false,"family":"Webb","given":"Ryan","email":"","affiliations":[{"id":79081,"text":"Department of Civil and Architectural Engineering and Construction Management, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":886350,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hale, Katherine","contributorId":330967,"corporation":false,"usgs":false,"family":"Hale","given":"Katherine","email":"","affiliations":[{"id":79082,"text":"Department of Civil and Environmental Engineering, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":886351,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70268355,"text":"70268355 - 2023 - Cultivating resilience in dryland soils: An assisted migration approach to biological soil crust restoration","interactions":[],"lastModifiedDate":"2025-06-23T14:49:01.362317","indexId":"70268355","displayToPublicDate":"2023-10-15T09:47:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5020,"text":"Microorganisms","active":true,"publicationSubtype":{"id":10}},"title":"Cultivating resilience in dryland soils: An assisted migration approach to biological soil crust restoration","docAbstract":"

Land use practices and climate change have driven substantial soil degradation across global drylands, impacting ecosystem functions and human livelihoods. Biological soil crusts, a common feature of dryland ecosystems, are under extensive exploration for their potential to restore the stability and fertility of degraded soils through the development of inoculants. However, stressful abiotic conditions often result in the failure of inoculation-based restoration in the field and may hinder the long-term success of biocrust restoration efforts. Taking an assisted migration approach, we cultivated biocrust inocula sourced from multiple hot-adapted sites (Mojave and Sonoran Deserts) in an outdoor facility at a cool desert site (Colorado Plateau). In addition to cultivating inoculum from each site, we created an inoculum mixture of biocrust from the Mojave Desert, Sonoran Desert, and Colorado Plateau. We then applied two habitat amelioration treatments to the cultivation site (growth substrate and shading) to enhance soil stability and water availability and reduce UV stress. Using marker gene sequencing, we found that the cultivated mixed inoculum comprised both local- and hot-adapted cyanobacteria at the end of cultivation but had similar cyanobacterial richness as each unmixed inoculum. All cultivated inocula had more cyanobacterial 16S rRNA gene copies and higher cyanobacterial richness when cultivated with a growth substrate and shade. Our work shows that it is possible to field cultivate biocrust inocula sourced from different deserts, but that community composition shifts toward that of the cultivation site unless habitat amelioration is employed. Future assessments of the function of a mixed inoculum in restoration and its resilience in the face of abiotic stressors are needed to determine the relative benefit of assisted migration compared to the challenges and risks of this approach.

","language":"English","publisher":"MDPI","doi":"10.3390/microorganisms11102570","usgsCitation":"Jech, S., Day, N.K., Barger, N., Antoninka, A., Bowker, M., Reed, S., and Tucker, C.L., 2023, Cultivating resilience in dryland soils: An assisted migration approach to biological soil crust restoration: Microorganisms, v. 11, no. 10, 2570, 18 p., https://doi.org/10.3390/microorganisms11102570.","productDescription":"2570, 18 p.","ipdsId":"IP-158175","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/microorganisms11102570","text":"Publisher Index Page"},{"id":491103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.34802973632918,\n 35.587070771119116\n ],\n [\n -116.01065534573146,\n 33.040451734318665\n ],\n [\n -113.56337647791864,\n 32.106918121662446\n ],\n [\n -109.03550909420508,\n 38.80883012106955\n ],\n [\n -108.98810398779125,\n 39.80828416894897\n ],\n [\n -110.68898438844218,\n 39.2840311835302\n ],\n [\n -113.98561161383276,\n 36.06454545435385\n ],\n [\n -117.34802973632918,\n 35.587070771119116\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Jech, Sierra","contributorId":292726,"corporation":false,"usgs":false,"family":"Jech","given":"Sierra","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":941062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":941063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barger, Nichole 0000-0002-8765-7974","orcid":"https://orcid.org/0000-0002-8765-7974","contributorId":245370,"corporation":false,"usgs":false,"family":"Barger","given":"Nichole","email":"","affiliations":[{"id":49167,"text":"University of Colorado Boulder, Department of Ecology and Evolutionary Biology,","active":true,"usgs":false}],"preferred":false,"id":941064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Antoninka, Anita","contributorId":166769,"corporation":false,"usgs":false,"family":"Antoninka","given":"Anita","affiliations":[{"id":24503,"text":"Northern Arizona University, School of Forestry, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":941065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowker, Matthew A.","contributorId":240683,"corporation":false,"usgs":false,"family":"Bowker","given":"Matthew A.","affiliations":[],"preferred":false,"id":941066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":941067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tucker, Colin L","contributorId":270737,"corporation":false,"usgs":false,"family":"Tucker","given":"Colin","email":"","middleInitial":"L","affiliations":[{"id":56205,"text":"U.S. National Forest Service, Northern Research Station, Houghton, MI 49931","active":true,"usgs":false}],"preferred":false,"id":941068,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70257389,"text":"70257389 - 2023 - Seven dam challenges for migratory fish: Insights from the Penobscot River","interactions":[],"lastModifiedDate":"2024-09-05T16:35:50.264408","indexId":"70257389","displayToPublicDate":"2023-10-15T09:16:26","publicationYear":"2023","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":"Seven dam challenges for migratory fish: Insights from the Penobscot River","docAbstract":"

More than a century of impoundments in the Penobscot River, Maine, USA, has contributed to population declines in migratory fish in the system. A decade of change, research, and monitoring has revealed direct and indirect ways that dams have influenced the river habitat, connectivity for migratory fish, and the food web. The removal of two main-stem dams (in 2012 and 2013) and bolstering of fish passage have been part of coordinated restoration efforts in the watershed. Integral to this undertaking was support for short- and long-term monitoring and research that included physical habitat, fish passage, and broad scale ecological assessments. Herein we discuss the seven interconnected and complex ways that dams have affected the Penobscot River ecosystem, particularly for migratory fish. These include familiar influences ascribed to dams: i) impaired access to habitat, ii) injury and mortality, and iii) delays of migration. Other ecological influences are less studied and more subtle: iv) facilitation of predation, v) community shifts, and vi) demographic shifts. Lastly, dams result in vii) a loss of ecosystem services that would otherwise be intact in an unimpounded system. We draw on both direct examples from the Penobscot River and broader information to characterize how impoundments have transformed this ecosystem for more than a century. Recent dam removals and mitigation efforts have reestablished some of these ecological functions.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1253657","usgsCitation":"Zydlewski, J.D., Coghlan, S., Dillingham, C., Figueroa-Munoz, G., Merriam, C., Smith, S., Smith, R., Stich, D.S., Vogel, S.K., Wilson, K., and Zydlewski, G., 2023, Seven dam challenges for migratory fish: Insights from the Penobscot River: Frontiers in Ecology and Evolution, v. 11, 1253657, 19 p., https://doi.org/10.3389/fevo.2023.1253657.","productDescription":"1253657, 19 p.","ipdsId":"IP-155048","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441877,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1253657","text":"Publisher Index Page"},{"id":432855,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": 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S.","contributorId":280276,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":33660,"text":"SUNY Oneonta","active":true,"usgs":false}],"preferred":false,"id":910214,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vogel, Sarah K.","contributorId":275755,"corporation":false,"usgs":false,"family":"Vogel","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":910215,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilson, Karen","contributorId":275235,"corporation":false,"usgs":false,"family":"Wilson","given":"Karen","affiliations":[{"id":34930,"text":"University of Southern Maine","active":true,"usgs":false}],"preferred":false,"id":910216,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zydlewski, Gayle B.","contributorId":139211,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle B.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":910217,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70249575,"text":"70249575 - 2023 - Evaluation of breeding distribution and chronology of North American scoters","interactions":[],"lastModifiedDate":"2024-01-08T17:21:40.311151","indexId":"70249575","displayToPublicDate":"2023-10-14T07:01:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of breeding distribution and chronology of North American scoters","docAbstract":"

North America's scoter species are poorly monitored relative to other waterfowl. Black Melanitta americana, surf M. perspicillata, and white-winged M. deglandi scoter abundance and trend estimates are thus uncertain in many parts of these species' ranges. The most extensive source of waterfowl abundance and distribution data in North America is the Waterfowl breeding population and habitat survey (WBPHS). Although the WBPHS effectively monitors most species, both its timing and geographic coverage may preclude accurate scoter monitoring. Therefore, our goal was to better define when and where scoters breed to help interpret survey results and optimize potential supplemental survey efforts for scoters. We integrated satellite telemetry tracking data from scoters marked at multiple molting, staging, breeding, and wintering areas along the Atlantic and Pacific coasts to quantify continent-wide breeding chronology and distribution. We also examined possible drivers of variation in timing of arrival, length of stay, and departure at nesting locations. We documented a northwest to southeast distribution of estimated breeding sites across Alaska and Canada. On average, scoters arrived at nest sites on 1 June. Surf scoters and Pacific black scoters arrived earliest and departed earliest. Pacific-wintering black and white-winged scoters began breeding earlier than Atlantic-wintering birds. Additionally, birds arrived at nesting locations earlier in years with earlier snowmelt, and later snowmelt reduced lengths of stay for males. Breeding chronology also varied by age group, with adults arriving earlier than subadults. Our study is the first to comprehensively describe spatial variation in timing of breeding of both Atlantic and Pacific populations of all three scoter species across North America. Our results increase our understanding of how current surveys enumerate scoters and will inform possible supplemental efforts to improve continental monitoring of scoter populations.

","language":"English","publisher":"Wiley","doi":"10.1002/wlb3.01099","usgsCitation":"Bianchini, K., Gilliland, S.G., Berlin, A., Bowman, T.D., Boyd, W., De La Cruz, S.E., Esler, D., Evenson, J.R., Flint, P.L., Lepage, C., McWilliams, S.R., Meattey, D.E., Osenkowski, J.E., Perry, M., Poulin, J., Reed, E.T., Roy, C., Savard, J.L., Savoy, L., Schamber, J.L., Spiegel, C.S., Takekawa, J., Ward, D.H., and Mallory, M.L., 2023, Evaluation of breeding distribution and chronology of North American scoters: Wildlife Biology, v. 2023, e01099, 19 p., https://doi.org/10.1002/wlb3.01099.","productDescription":"e01099, 19 p.","ipdsId":"IP-140908","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441881,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index 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Management and conservation efforts that support the recovery and protection of large rivers are daunting, reflecting the complexity of the challenge and extent of effort (in terms of policy, economic investment, and spatial extent) needed to afford measurable change. These large systems have generally experienced intensive development and regulation, compromising their capacity to respond to disturbances such as climate change or wildfire. Functionally, large river and basin management require insights gained from social, ecological, geophysical, and hydrological sciences. This multi-disciplinary perspective can unveil the integrated relationship between a river network's biotic community and seasonally variable environmental conditions that are often influenced by human activities. Large rivers and their basins are constantly changing due to anthropogenic influences and as climate modifies patterns of temperature and precipitation. Because of these factors, the state of knowledge must advance to address changing conditions. The Willamette River, in western Oregon, USA, is a prime example of a basin that has experienced significant degradation and investment in rehabilitation in recent decades. Innovative science has facilitated development of fine-scale, spatially extensive datasets and models that can generate targeted conservation and rehabilitation actions that are prioritized across the entire river network. This prioritization allows investment decisions to be driven by site-specific conditions while simultaneously considering potentials for ecological improvement. Here, we review hydrologic, geomorphic, ecologic, and social conditions in the Willamette River basin through time—including pre-settlement, river development, and contemporary periods—and offer a future vision for consideration. Currently, detailed information about fish populations and habitat, hydrologic conditions, geomorphology, water quality, and land use can be leveraged to make informed decisions about protection, rehabilitation, and development. The time is ripe for strategic management and goal development for the entire Willamette River, and these efforts can be informed by comprehensive science realized through established institutions (e.g., public agencies, non-profit watershed groups, Tribes, and universities) focused on conservation and management. The approaches to science and social-network creation that were pioneered in the Willamette River basin offer insights into the development of comprehensive conservation-based planning that could be implemented in other large river systems globally.

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