Aim: Smallmouth Bass (Micropterus dolomieu; SMB) are globally popular among anglers and have been widely introduced (i.e. stocked) for population management and sportfishing. Importantly, stocking was prevalent before cryptic diversity within the SMB complex was known, which now includes three newly elevated species: Neosho Bass (M. velox; NB), Little River Bass (M. sp. cf. dolomieu Little River; LRB) and Ouachita Bass (M. sp. cf. dolomieu Ouachita River; OB). We sought to quantify population structure and hybridisation and introgression in these three recently described species.
Location: Species-level diversity, particularly in the basin-restricted LRB and OB in the Ouachita Mountains within the Central Interior Highlands (CIH), North America, suggests the presence of distinct genetic variation that could be eroded by introgression.
Methods: We estimated interspecific introgression and intraspecific population differentiation in the Smallmouth Bass species complex (SMB-C) using 472 specimens comprising SMB, NB, LRB and OB, including the naturally sympatric Spotted Bass (M. punctulatus; SPB). Genomic samples were genotyped on a SNP panel of 192 loci designed to detect allele-sharing on multiple hierarchical levels.
Results: We found low range-wide hybridisation between species in the SMB-C and SPB (mostly SMB-C backcrosses), and interspecific heterozygosity varied, indicating differential introgression. Range-wide hybridisation between species in the CIH and SMB was similar overall (but mostly F2 and CIH backcrosses) and was observed in streams with known SMB stocking in connected reservoirs. Interspecific heterozygosity in SMB hybrids was also generally lower, indicating later-generation backcrosses. We found strong population structure in the Ouachita Mountains (LRB and OB).
Main conclusions: Despite isolated incidences of natural (SPB) and human-mediated (SMB) introgression, genomic identity appears intact in endemic LRB and OB, suggesting potential ecological or behavioural isolating mechanisms preventing cross-species reproduction. Our findings reveal that genetic variation remains in cryptic, basin-restricted species in the Ouachita Mountains ecoregion that may be managed for long-term conservation.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13759","usgsCitation":"Gunn, J.C., Taylor, A.T., Buckingham, J.J., Kern, A.I., and Long, J.M., 2023, Limited hybridisation and introgression despite stocking among endemic Interior Highlands black basses (Centrarchidae: Micropterus): Diversity and Distributions, v. 29, no. 10, p. 1299-1314, https://doi.org/10.1111/ddi.13759.","productDescription":"16 p.","startPage":"1299","endPage":"1314","ipdsId":"IP-151349","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441983,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13759","text":"Publisher Index Page"},{"id":432885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.2590286084522,\n 36.7225498069222\n ],\n [\n -95.2590286084522,\n 34.76999907364004\n ],\n [\n -93.07274931157696,\n 34.76999907364004\n ],\n [\n -93.07274931157696,\n 36.7225498069222\n ],\n [\n -95.2590286084522,\n 36.7225498069222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Gunn, Joe C.","contributorId":275348,"corporation":false,"usgs":false,"family":"Gunn","given":"Joe","email":"","middleInitial":"C.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Andrew T.","contributorId":274252,"corporation":false,"usgs":false,"family":"Taylor","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":907861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckingham, Jeff J.","contributorId":341055,"corporation":false,"usgs":false,"family":"Buckingham","given":"Jeff","email":"","middleInitial":"J.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":907862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kern, Aaron I.","contributorId":341056,"corporation":false,"usgs":false,"family":"Kern","given":"Aaron","email":"","middleInitial":"I.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":907863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":907864,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249363,"text":"70249363 - 2023 - Microgravity as a tool for eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-04T20:16:28.295246","indexId":"70249363","displayToPublicDate":"2023-10-01T13:00:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Microgravity as a tool for eruption forecasting","docAbstract":"Detection of gravity change over time has been used to better understand magmatic activity at volcanoes for decades, but the technique is not commonly applied to forecasting eruptions. In contrast, other tools, notably seismic, deformation, and gas monitoring have made exceptional strides in the past several decades and form the foundation for eruption forecasting, especially during the final buildup to an eruption. Reasons for this gap include the high cost and fragile nature of gravity instruments, and the ambiguous nature of many results. But this is changing. Instrumentation is becoming more robust and accurate, expenses may soon diminish thanks to technological advances, and the record of success in tracking subsurface mass change (either from magma or hydrothermal fluids) in volcanic areas is growing. Here we review how gravity change can be applied to forecasting volcanic eruptions across a variety of spatial and temporal scales. We argue that microgravity has untapped potential as a forecasting tool in three specific ways: constraining probabilistic assessments, detecting long-term mass change that may occur prior to the onset of vigorous seismicity and deformation, and identifying transient activity that indicates magma ascent or other changes that immediately precede new eruptions or changes in ongoing eruptions. As with any volcano-monitoring method, microgravity has strengths and weaknesses, but the varied forms of data collection—for instance, campaign versus continuous, and relative versus absolute—offer the potential to record a broad range of signals at volcanoes with a diversity of magmatic systems. The technique is currently underutilized; additional attention, investment, and application at more volcanoes could help to realize its promise.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107910","usgsCitation":"de Zeeuw-van Dalfsen, E., and Poland, M.P., 2023, Microgravity as a tool for eruption forecasting: Journal of Volcanology and Geothermal Research, v. 442, 107910, 14 p., https://doi.org/10.1016/j.jvolgeores.2023.107910.","productDescription":"107910, 14 p.","ipdsId":"IP-152507","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":421616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.28629797636563,\n 19.401938981737857\n ],\n [\n -155.28523227780258,\n 19.401603921708983\n ],\n [\n -155.2829232642494,\n 19.40171560846254\n ],\n [\n -155.27984457951175,\n 19.403390900554683\n ],\n [\n -155.27800920976435,\n 19.406183015701615\n ],\n [\n -155.27818682619153,\n 19.408472514355836\n ],\n [\n -155.2790157028517,\n 19.410091896380962\n ],\n [\n -155.28126551092907,\n 19.411599582390465\n ],\n [\n -155.28617956541413,\n 19.411376222382003\n ],\n [\n -155.28689003112277,\n 19.41065030023701\n ],\n [\n -155.28712685302565,\n 19.40970101254156\n ],\n [\n -155.28925825015176,\n 19.406294699311132\n ],\n [\n -155.28931745562747,\n 19.404898648686896\n ],\n [\n -155.28896222277308,\n 19.404451909956876\n ],\n [\n -155.2884293734916,\n 19.403446743327578\n ],\n [\n -155.28629797636563,\n 19.401938981737857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"442","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":885329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885330,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252750,"text":"70252750 - 2023 - Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA)","interactions":[],"lastModifiedDate":"2024-04-04T16:55:59.02534","indexId":"70252750","displayToPublicDate":"2023-10-01T11:47:31","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA)","docAbstract":"J.N. “Ding” Darling National Wildlife Refuge (DDNWR) is located on Sanibel Island along the southwestern coast of Florida, USA. Sanibel Island is heavily developed, but DDNWR provides protection for a large mangrove area that supports biodiversity and recreational opportunity. However, nitrogen (N) and phosphorus (P) eutrophication attributed to agriculture discharge along the Caloosahatchee River has affected the area’s aquatic habitat with algal blooms and may be causing untimely degradation of Sanibel’s mangrove forests. We launched a series of studies to understand how additional nutrient loading to the levels expected in the future might affect DDNWR’s mangrove resource. We experimentally fertilized selected mangrove forest areas with N fertilizer (+N; NH4) and P fertilizer (+P; P2O5) for three years, and monitored soil surface elevation change, soil and pneumatophore CO2 fluxes from respiration, mangrove tree sap flow from two species (Avicennia germinans, Rhizophora mangle), and individual tree and stand water use, from which we developed carbon (C) budgets for +N and +P vs. control simulations as applied to DDNWR’s 1112 ha mangrove area. Many of the measured response variables provided hints of subtle changes in response to +P rather than +N, which were compounded when scaled. From this, we found that additional P loading is expected to stimulate CO2 uptake via net ecosystem exchange of C, likely pressing the system beyond metabolic capacity and leading to a projected 41% increase in lateral C export to the estuary. Additional lateral C export is concomitant to a reduction in vertical soil surface elevation with +P. Furthermore, an inability of DDNWR’s mangroves to bury additional P and a release of P-bound ions to lateral export may exacerbate estuarine eutrophication. We also modelled the effect of sea-level rise influences on DDNWR’s mangroves through 2100 using a soil cohort model (WARMER-Mangroves) and found that the mangroves may be resilient to current rates of sea-level rise into the future but may also be susceptible to moderate accelerations. Greater eutrophication could create additional vulnerabilities to mangrove submergence, especially to basin mangroves where P concentrations are high and already reducing soil surface elevations in some mangroves. Our results suggest that amelioration of current P concentrations and avoidance of additional P loading to Sanibel Island’s mangroves are management options to consider.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Krauss, K., Conrad, J.R., Duberstein, J., Ward, E., Drexler, J.Z., Buffington, K., Thorne, K., Benscoter, B.W., Miller, H., Faron, N.T., Merino, S., From, A., Peneva-Reed, E., and Zhu, Z., 2023, Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA), 46 p.","productDescription":"46 p.","ipdsId":"IP-156801","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":427403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427371,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/mangrove-ecosystem-services/"}],"country":"United States","state":"Florida","otherGeospatial":"Ding Darling National Wildlife Refuge, Sanibel Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.09257743948284,\n 26.43591715803987\n ],\n [\n -82.04970400948879,\n 26.44673081335216\n ],\n [\n -82.05393096737532,\n 26.472138907162602\n ],\n [\n -82.08170811920239,\n 26.469976734538434\n ],\n [\n -82.09016203497596,\n 26.461327637778552\n ],\n [\n -82.1227699958168,\n 26.475922611484222\n ],\n [\n -82.15718951003726,\n 26.494839266177138\n ],\n [\n -82.17107808595081,\n 26.49916263597524\n ],\n [\n -82.17590889496402,\n 26.515914157596868\n ],\n [\n -82.18315510848416,\n 26.521857658684468\n ],\n [\n -82.18557051299105,\n 26.487272977733056\n ],\n [\n -82.14330093412373,\n 26.455381006749434\n ],\n [\n -82.10163520638315,\n 26.43916136120143\n ],\n [\n -82.09257743948284,\n 26.43591715803987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, Jeremy R.","contributorId":149347,"corporation":false,"usgs":false,"family":"Conrad","given":"Jeremy","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":898086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":898087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":217389,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":898089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":898090,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":898091,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benscoter, Brian W.","contributorId":335331,"corporation":false,"usgs":false,"family":"Benscoter","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":40277,"text":"U.S. Department of Energy","active":true,"usgs":false}],"preferred":false,"id":898092,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Haley 0000-0002-1745-9526","orcid":"https://orcid.org/0000-0002-1745-9526","contributorId":304983,"corporation":false,"usgs":false,"family":"Miller","given":"Haley","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":898093,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Faron, Natalie T.","contributorId":312468,"corporation":false,"usgs":false,"family":"Faron","given":"Natalie","email":"","middleInitial":"T.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":898094,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Merino, Sergio 0000-0002-2834-2243 merinos@usgs.gov","orcid":"https://orcid.org/0000-0002-2834-2243","contributorId":3653,"corporation":false,"usgs":true,"family":"Merino","given":"Sergio","email":"merinos@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898095,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"From, Andrew 0000-0002-6543-2627","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":223021,"corporation":false,"usgs":true,"family":"From","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898096,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peneva-Reed, Elitsa I. 0000-0002-4570-4701","orcid":"https://orcid.org/0000-0002-4570-4701","contributorId":294531,"corporation":false,"usgs":false,"family":"Peneva-Reed","given":"Elitsa I.","affiliations":[],"preferred":false,"id":898097,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":898098,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70251016,"text":"70251016 - 2023 - Grizzly bear lean body mass, but not fat gain, is inversely correlated with bear density in a changing Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-02-01T17:42:54.621751","indexId":"70251016","displayToPublicDate":"2023-10-01T11:39:24","publicationYear":"2023","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":10772,"text":"International Bear News","active":true,"publicationSubtype":{"id":30}},"title":"Grizzly bear lean body mass, but not fat gain, is inversely correlated with bear density in a changing Greater Yellowstone Ecosystem","docAbstract":"No abstract available.
","language":"English","publisher":"International Association for Bear Research and Management","usgsCitation":"Corradini, A., Haroldson, M.A., and van Manen, F.T., 2023, Grizzly bear lean body mass, but not fat gain, is inversely correlated with bear density in a changing Greater Yellowstone Ecosystem: International Bear News, v. 32, no. 3, p. 36-38.","productDescription":"3 p.","startPage":"36","endPage":"38","ipdsId":"IP-158498","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":424570,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.bearbiology.org"},{"id":425229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.258811441601,\n 45.10546497824018\n ],\n [\n -111.258811441601,\n 44.08333533276516\n ],\n [\n -109.80882252027241,\n 44.08333533276516\n ],\n [\n -109.80882252027241,\n 45.10546497824018\n ],\n [\n -111.258811441601,\n 45.10546497824018\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Corradini, Andrea","contributorId":304284,"corporation":false,"usgs":false,"family":"Corradini","given":"Andrea","affiliations":[{"id":66017,"text":"Department of Civil, Environmental and Mechanical Engineering, University of Trento","active":true,"usgs":false}],"preferred":false,"id":892778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":892779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":892780,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249606,"text":"70249606 - 2023 - Lake Ontario April prey fish survey results and Alewife assessment, 2023","interactions":[],"lastModifiedDate":"2025-08-26T14:29:06.466685","indexId":"70249606","displayToPublicDate":"2023-10-01T10:08:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lake Ontario April prey fish survey results and Alewife assessment, 2023","docAbstract":"The April bottom trawl survey and Alewife Alosa pseudoharengus population assessment provides science to inform Lake Ontario fisheries management. The 2023 survey included 215 trawls in the main lake and embayments, and sampled depths from 6.5 to 252 m (21-833 ft). The survey captured 1,012,178 fish from 32 species with a total weight of 12,136 kg (26,700 lbs.). Alewife were 92% of the catch by number while Rainbow Smelt, Osmerus mordax, Deepwater Sculpin, Myoxocephalus thompsonii, and Round Goby, Neogobius melanostomus, comprised 3%, 3%, and 1% of the catch, respectively. To improve the accuracy of prey fish biomass and density estimates we reanalyzed trawl sensor data from each of three participating survey vessels and created vessel-specific relationships predicting how bottom trawl bottom contact time, wing width, and area-swept varies with depth.
Total Alewife biomass increased in 2023 due to growth and survival of the abundant 2020 year class (now age-3) and an abundant 2022 year class (age-1). The 2023 mean Alewife biomass (81.1 kg·ha-1) was the largest since whole lake sampling began in 2016 and was the ninth largest value observed in the modern time series (1997-2023, maximum value in 2000 = 91.8 kg·ha-1). The 2023 Alewife density (6795 n·ha-1) was the greatest density observed in the modern time series. These high biomass and density values are due to above average Alewife reproductive success in 2020 and 2022. Simulation modeling suggests the 2024 and 2025 Alewife biomass index may be substantially higher than the 2023 observations.
In 2023, the Rainbow Smelt biomass index increased relative to the 2022 index, as did the biomass index for Cisco, Coregonus artedi. In contrast, Emerald Shiner Notropis atherinoides and Threespine Stickleback Gasterosteus aculeatus, biomass values continue to be low (< 0.01 kg·ha-1). Three Bloater Coregonus hoyi, were captured during the 2023 survey. Hydroacoustic sampling conducted during the bottom trawl survey estimated prey fish densities in pelagic habitats not sampled by the bottom trawl (3 m below the surface to 3 m above the lake bottom) and these densities were hundreds to thousands of times lower than bottom trawl-based densities. These results support the idea that, in April, when the warmest water is on the lake bottom, Alewife and most other pelagic prey fish are near the lake bottom and can be effectively sampled with bottom trawling.
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Jeremy","contributorId":168905,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":886438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchinson, Olivia Margaret 0009-0002-7999-1160","orcid":"https://orcid.org/0009-0002-7999-1160","contributorId":339869,"corporation":false,"usgs":true,"family":"Mitchinson","given":"Olivia","email":"","middleInitial":"Margaret","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minihkeim, Scott P. 0000-0003-4958-2462","orcid":"https://orcid.org/0000-0003-4958-2462","contributorId":265808,"corporation":false,"usgs":true,"family":"Minihkeim","given":"Scott","email":"","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886440,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250110,"text":"70250110 - 2023 - Stable isotope constraints on the source of ore fluids for the Hicks Dome REE+Y-HFSE-fluorspar deposit","interactions":[],"lastModifiedDate":"2023-11-20T16:11:18.374145","indexId":"70250110","displayToPublicDate":"2023-10-01T10:04:32","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Stable isotope constraints on the source of ore fluids for the Hicks Dome REE+Y-HFSE-fluorspar deposit","docAbstract":"Hicks Dome is comprised of coarse crystalline Mississippi Valley Type deposits at shallow levels and an enigmatic, fine-grained fluorite, rare earth elements, Y, high field strength elements, Be, and Ba rich deposit at deeper levels. Phyllosilicates from a lamprophyre dike and a breccia from two Hicks Dome drill cores were sampled to resolve the fluid history of the entire deposit using light stable isotopes. Silicate fluorination coupled with isotope ratio mass spectrometry give δ18O values from +6.9 to +16.0 ‰ (Vienna Standard Mean Ocean Water). Temperature conversion elemental analyzer and gas chromatography-isotope ratio mass spectrometry give δ2H values from -54 to -33 ‰ (Vienna Standard Mean Ocean Water). Muscovite from metasomatized dikes and breccias are relatively enriched in 18O compared to phlogopite from lamprophyre. Calculated isotopic compositions of the fluids from which the phyllosilicates precipitated indicate that phlogopite retained a magmatic composition while muscovite likely formed from magmatic fluids that exchanged with carbonate host rocks or from magmatic fluids that mixed with basinal brines. Enrichment of deuterium in fluids calculated from muscovite suggest that fluids were derived from hypothesized carbonatites or were acidic. 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carpenter, Kurt D. 0000-0002-6231-8335 kdcar@usgs.gov","orcid":"https://orcid.org/0000-0002-6231-8335","contributorId":127442,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt","email":"kdcar@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sobota, Daniel","contributorId":333712,"corporation":false,"usgs":false,"family":"Sobota","given":"Daniel","email":"","affiliations":[{"id":27064,"text":"Oregon Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":893660,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257401,"text":"70257401 - 2023 - Genetic structure across isolated Virginia populations of the endangered candy darter (Etheostoma osburni)","interactions":[],"lastModifiedDate":"2024-08-30T15:37:45.528998","indexId":"70257401","displayToPublicDate":"2023-10-01T08:27:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure across isolated Virginia populations of the endangered candy darter (Etheostoma osburni)","docAbstract":"Candy darter Etheostoma osburni, a federally endangered non-game fish, has been extirpated from most of its historic range in Virginia and now occurs in four isolated populations in the New River drainage. Understanding of population genetic structure will provide insights into the recent natural history of the species and can inform conservation management. Our objectives were to: characterize population genetic structure, estimate and compare effective population sizes (Ne), and use this information to infer recent population history. Variation at mitochondrial cytochrome b sequences among 150 individuals showed 10 haplotypes separated by 1–14 mutational steps, some shared and some unique to particular populations. Variation at 12 microsatellite loci among 171 individuals showed lower variation in Dismal Creek than in other populations. All populations showed evidence of having experienced a genetic bottleneck and were highly differentiated from one another based on both types of DNA markers. Population genetic structure was related to stream position in regard to the New River, suggesting that populations were once connected. Ne estimates for all populations were less than the 500 recommended to maintain evolutionary potential, but most estimates were greater than the 100 needed for use as source populations. Our findings indicate that habitat management to allow expansion of populations, and translocations to exchange genetic material among populations, may be effective tactics to promote conservation of candy darter in Virginia.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes8100490","usgsCitation":"McBaine, K., Angermeier, P., and Hallerman, E., 2023, Genetic structure across isolated Virginia populations of the endangered candy darter (Etheostoma osburni): Fishes, v. 8, no. 10, 490, 18 p., https://doi.org/10.3390/fishes8100490.","productDescription":"490, 18 p.","ipdsId":"IP-142203","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8100490","text":"Publisher Index Page"},{"id":433375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia, West Virginia","otherGeospatial":"New River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.18942982675185,\n 38.787279180550485\n ],\n [\n -81.18942982675185,\n 36.10166764914369\n ],\n [\n -79.93920046919138,\n 36.10166764914369\n ],\n [\n -79.93920046919138,\n 38.787279180550485\n ],\n [\n -81.18942982675185,\n 38.787279180550485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"McBaine, Kathyrn E.","contributorId":342648,"corporation":false,"usgs":false,"family":"McBaine","given":"Kathyrn E.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":910256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallerman, Eric M.","contributorId":279474,"corporation":false,"usgs":false,"family":"Hallerman","given":"Eric M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":910258,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274788,"text":"70274788 - 2023 - Water-soluble organic carbon release from mineral soils and sediments in an irrigated agricultural system","interactions":[],"lastModifiedDate":"2026-04-09T15:28:27.07613","indexId":"70274788","displayToPublicDate":"2023-10-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Water-soluble organic carbon release from mineral soils and sediments in an irrigated agricultural system","docAbstract":"Water interactions with soil and vegetation are greatly altered in agricultural watersheds compared to natural landscapes, which impacts sources and fates of organic carbon (OC). While mineral soil horizons in natural ecosystems primarily act as filters for dissolved organic carbon (DOC) leached from organic surface horizons, tilled soils largely lack an organic horizon and their mineral horizons therefore act as a source for both DOC and sediment to surface waters. Irrigated watersheds highlight this difference, as DOC and total suspended sediment (TSS) concentrations simultaneously increase during the low-discharge irrigation season, suggesting that sediment-associated OC may constitute a significant source of DOC. While water-soluble OC (WSOC) from sediments and soils has been found to be compositionally similar to stream DOC, these contributions remain poorly quantified in agricultural streams. To address this, we conducted abiotic solubilization experiments using sediments (suspended and bed) and soils from an irrigated agricultural watershed in northern California, USA. Sediments (R2 > 0.99) and soils (0.74 < R2 < 0.89) displayed linear solubilization behaviors over the range of concentrations tested. Suspended sediment from the irrigation season exhibited the largest solubilization efficiency (10.9 ± 1.6% TOCsediment solubilized) and potential (1.79 ± 0.26 mg WSOC g−1 dry sediment), followed by suspended sediment from a winter storm, then bed sediment and soils. Successive solubilization experiments increased the total release of WSOC by ∼50%, but most (88–97%) of the solid-phase OC remained insoluble in water. Using these solubilization potential estimates and measured TSS concentrations, we estimated that WSOC from suspended sediment in streams represented 4–7% of the annual DOC export from the watershed. However, field sediment export is much higher than what is represented by suspended sediment in the water column, therefore field-scale contributions from sediments could be much higher than estimated.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.118184","usgsCitation":"Matiasek, S.J., Pellerin, B.A., Spencer, R.G., Bergamaschi, B.A., and Hernes, P.J., 2023, Water-soluble organic carbon release from mineral soils and sediments in an irrigated agricultural system: Journal of Environmental Management, no. 343, 118184, 12 p., https://doi.org/10.1016/j.jenvman.2023.118184.","productDescription":"118184, 12 p.","ipdsId":"IP-118437","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":502495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2023.118184","text":"Publisher Index Page"},{"id":502356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Valley, Willow Slough watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.15914701306207,\n 38.620199839913425\n ],\n [\n -122.15914701306207,\n 38.21487986460099\n ],\n [\n -121.40033409994635,\n 38.21487986460099\n ],\n [\n -121.40033409994635,\n 38.620199839913425\n ],\n [\n -122.15914701306207,\n 38.620199839913425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"343","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matiasek, Sandrine J. 0000-0003-0272-0354","orcid":"https://orcid.org/0000-0003-0272-0354","contributorId":210031,"corporation":false,"usgs":false,"family":"Matiasek","given":"Sandrine","middleInitial":"J.","affiliations":[{"id":38054,"text":"Department of Geological and Environmental Sciences, California State University Chico, 400 W 1st St, Chico, CA 95929, USA","active":true,"usgs":false}],"preferred":false,"id":959143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pellerin, Brian A. 0000-0003-3712-7884 bpeller@usgs.gov","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":147077,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":959144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spencer, Robert G.","contributorId":369574,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert","middleInitial":"G.","affiliations":[{"id":87849,"text":"U.Calif. at Davis","active":true,"usgs":false}],"preferred":false,"id":959145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hernes, Peter J. 0000-0001-7908-0936","orcid":"https://orcid.org/0000-0001-7908-0936","contributorId":329589,"corporation":false,"usgs":false,"family":"Hernes","given":"Peter","middleInitial":"J.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":959147,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266470,"text":"70266470 - 2023 - Spatially and temporally variable production pathways support the Lake Erie central basin food web","interactions":[],"lastModifiedDate":"2025-05-07T18:47:53.830989","indexId":"70266470","displayToPublicDate":"2023-09-30T13:43:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatially and temporally variable production pathways support the Lake Erie central basin food web","docAbstract":"In large freshwater systems, the dominant production pathways supporting food webs are often spatiotemporally variable. We used stable isotope analysis and analysis of covariance (ANCOVA) models to investigate spatial and interannual variation in the dominant production pathways supporting fish consumers within the central basin of Lake Erie. We examined C and N stable isotope ratios of zooplankton, benthic invertebrates, and four species of fish common to nearshore areas of the central basin (yellow perch, Perca flavescens; white perch, Morone americana; rainbow smelt, Osmerus mordax; and round goby, Neogobius melanostomus) using tissue samples collected in 2017 and 2019. δ 13C values varied by location consistent with expected baseline differences in nutrient loading (13C was more enriched in the southern region) in two of six ANCOVA models. Furthermore, δ 15N values varied with individual fish size and by location in a manner consistent with spatial patterns of nutrient loading from surrounding agricultural landscapes (15N was more enriched in the northern region) and a longitudinal gradient of eutrophication, decreasing from west to east. These patterns were not exhibited by all species and did not necessarily persist across years, suggesting that additional factors (e.g., regional diet differences, river plume dynamics) also contributed to observed δ 13C and δ 15N variation. We suggest that spatiotemporal variation of stable isotope ratios should be accounted for in studies of trophic basis of production and food web structure in Lake Erie.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.07.006","usgsCitation":"Tellier, J., Höök, T., Kraus, R., and Collingsworth, P., 2023, Spatially and temporally variable production pathways support the Lake Erie central basin food web: Journal of Great Lakes Research, v. 49, no. 5, p. 1137-1149, https://doi.org/10.1016/j.jglr.2023.07.006.","productDescription":"13 p.","startPage":"1137","endPage":"1149","ipdsId":"IP-144710","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.jglr.2023.07.006","text":"Publisher Index Page"},{"id":485518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"central Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.89113891431519,\n 42.642087429833964\n ],\n [\n -81.54918796649198,\n 42.5518853383298\n ],\n [\n -82.00732338256428,\n 42.28154650023495\n ],\n [\n -82.41825696788968,\n 42.08990823363946\n ],\n [\n -82.65704269990312,\n 41.35456309813142\n ],\n [\n -81.71855924152474,\n 41.51441245425303\n ],\n [\n -80.95777679301685,\n 41.82391066009919\n ],\n [\n -80.89113891431519,\n 42.642087429833964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Tellier, Joshua M.","contributorId":354641,"corporation":false,"usgs":false,"family":"Tellier","given":"Joshua M.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":936058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Höök, Tomas O.","contributorId":354642,"corporation":false,"usgs":false,"family":"Höök","given":"Tomas O.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":936059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collingsworth, Paris D.","contributorId":354643,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris D.","affiliations":[{"id":84645,"text":"Illinois-Indiana SeaGrant","active":true,"usgs":false}],"preferred":false,"id":936061,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242724,"text":"70242724 - 2023 - Evaluate propagation efforts and determine dispersal patterns for Quadrula fragosa from tagged, artificially infested host fish (Ictalurus punctatus) in the St. Croix National Scenic Riverway (SACN)","interactions":[],"lastModifiedDate":"2024-03-28T17:02:20.259859","indexId":"70242724","displayToPublicDate":"2023-09-30T11:57:43","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"displayTitle":"Evaluate propagation efforts and determine dispersal patterns for Quadrula fragosa from tagged, artificially infested host fish (Ictalurus punctatus) in the St. Croix National Scenic Riverway (SACN)","title":"Evaluate propagation efforts and determine dispersal patterns for Quadrula fragosa from tagged, artificially infested host fish (Ictalurus punctatus) in the St. Croix National Scenic Riverway (SACN)","docAbstract":"The St. Croix National Scenic Riverway (SACN) has been the site of propagation and restoration efforts for two federally endangered unionid mussels: Higgins’ Eye, Lampsilis higginsii and Winged Mapleleaf (WML), Quadrula fragosa. Since about 2000, government agencies have collaboratively developed techniques to successfully propagate Higgins’ Eye and reintroduce the captive-reared subadult mussels into rehabilitated habitats in the upper Mississippi River Basin and several tributaries, including the SACN. However, propagation efforts for the WML have had limited success from 2003 to present. The population of WML in the SACN has high value because it is physically isolated and genetically distinct from four southern populations, and it is the only known self-sustaining population within the upper Mississippi River. Unionids have a complex reproductive cycle that includes a parasitic larval stage (glochidia) that requires species-specific fish hosts. WML are one of the few species that are fall, short-term (~6 weeks) brooders—brooding begins at end of August. In the SACN, Channel Catfish (Ictalurus punctatus) are the only known host for WML and glochidia are assumed to overwinter on their host fish and detach the following spring. Research has shown that holding hatchery reared channel catfish that are infested with WML glochidia in cages, either in situ or in a hatchery, over winter has been a challenge due to high fish mortality; rearing juveniles after transformation has also resulted in high mortality rates and juvenile loss (Wege et al. 2007). The importance of the overwintering parasitic period and the overall health of the host fish for successful transformation of juvenile WML is unknown, but these key criteria could play an important role in successful propagation efforts. This research has three objectives: (1) compile historic data from >14 years of Q. fragosa propagation efforts into a searchable database to identify potential knowledge gaps that could be limiting its success, (2) explore in situ and ex situ propagation techniques to optimize production of Q. fragosa juveniles, and (3) characterize the movement pattern of Channel Catfish that are artificially inoculated with the SACN strain of Q. fragosa to identify potential juvenile release survey locations in future years.
","language":"English","publisher":"National Park Service (NPS)","usgsCitation":"Bartsch, M., 2023, Evaluate propagation efforts and determine dispersal patterns for Quadrula fragosa from tagged, artificially infested host fish (Ictalurus punctatus) in the St. Croix National Scenic Riverway (SACN): Final Report, 5 p.","productDescription":"5 p.","ipdsId":"IP-150971","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":415767,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573106"},{"id":427222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St. Croix National Scenic Riverway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.71000906231872,\n 45.49867074154517\n ],\n [\n -92.71859207511878,\n 45.528691637663\n ],\n [\n -92.71712134113274,\n 45.54423659649845\n ],\n [\n -92.78307297267946,\n 45.57666706679137\n ],\n [\n -92.87175016016285,\n 45.57560062474545\n ],\n [\n -92.8823158739112,\n 45.64115838394207\n ],\n [\n -92.90800656678626,\n 45.63869230668081\n ],\n [\n -92.90093848202504,\n 45.56997586232177\n ],\n [\n -92.84201504830612,\n 45.552332618987634\n ],\n [\n -92.77301111121999,\n 45.55480983613549\n ],\n [\n -92.75042056502501,\n 45.50408264384447\n ],\n [\n -92.72673985861034,\n 45.496650138913\n ],\n [\n -92.71000906231872,\n 45.49867074154517\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartsch, Michelle 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":3165,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":869504,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70249602,"text":"70249602 - 2023 - Field and laboratory validation of new sampling gear to quantify coregonine egg deposition and larval emergence across spawning habitat gradients","interactions":[],"lastModifiedDate":"2023-10-23T10:48:58.36646","indexId":"70249602","displayToPublicDate":"2023-09-30T09:52:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Field and laboratory validation of new sampling gear to quantify coregonine egg deposition and larval emergence across spawning habitat gradients","docAbstract":"The influence of habitat and environmental conditions on Great Lakes coregonine reproduction is not well described, in part, because we lack sampling gears for early life stages that are effective across habitats. We designed new egg and larval emergence traps to quantify coregonine reproductive success across variable depths and substrates and tested them in laboratory and field settings. In the laboratory, our new metal ring egg traps had greater egg retention (94–100%) and faster post-catch processing (5–7 min) relative to a commonly employed fiber mat trap (30–67% and 30–60 min). In Lake Ontario’s Chaumont Bay, egg densities for lake whitefish Coregonus clupeaformis (0–5,832 eggs m−2) and cisco Coregonus artedi (0–426,501 eggs m−2) measured with metal ring traps (n = 112) varied across habitats but were greatest between 2–5 m on rock and dreissenid mussel substrates. Emergence traps used an inverted cone, fine mesh, and a clear collection chamber to capture positively phototactic emerging larvae. In the laboratory, traps captured 69–80% of emerged larvae. In Chaumont Bay, emergence traps deployed for 21 days after ice out caught only cisco larvae. Emergence rates varied across habitats (0–118 larvae m−2 day−1, n = 85) but were highest on dreissenid mussel reef substrate. Our samplers improved processing efficiency and facilitated large sample sizes to quantify variability in egg deposition densities and emergence rates across habitats. These methods can advance coregonine conservation by determining how anthropogenic changes to habitat and environmental conditions influence incubation success.
The opossum shrimp, Mysis diluviana, is an important member of the offshore food webs of the Laurentian Great Lakes, but its response to ecosystem changes that have occurred over the past several decades is not well understood. We combined the data of four long-term sampling programs, adding several years of data (post and prior) to previously published analyses to offer a longer-term, cross-basin analysis of M. diluviana populations in the Great Lakes from 1997 to 2019. Densities were high in lakes Superior and Ontario (summer values 100–300/m2), high and variable but declining (from 200–300/m2 in 1997–2004 to less than 100/m2 in 2017–2019) in Lake Michigan, low (∼20–50/m2 since 2005) in Lake Huron, and very low in shallower eastern Lake Erie (<1/m2). Biomass showed similar trends. Life history parameters (mortality, fecundity, and growth) were consistently highest in eastern Lake Erie, followed by lakes Ontario, Michigan, Huron, and Superior. Generation time was 1 year in Lake Erie and 2 years in the other lakes. Cross-basin relationships between annual M. diluviana areal densities and food indices (chlorophyll-a concentration and zooplankton biomass) were non-linear, increasing with food levels up to about 250 mysids/m2 and about 650 mg dry wt/m2. Annual growth rates were also positively correlated to both food indices in the four deep lakes, but fecundity and mortality rates were not. Our results suggest food availability is a primary factor predicting M. diluviana density and biomass. Density-dependent mortality and fish predation could explain some of the inter-lake differences, but these relationships could benefit from further investigations.
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Center","active":true,"usgs":true}],"preferred":true,"id":896687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowen, Kelly L.","contributorId":38382,"corporation":false,"usgs":false,"family":"Bowen","given":"Kelly","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":896688,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Currie, Warren J.S.","contributorId":334845,"corporation":false,"usgs":false,"family":"Currie","given":"Warren","email":"","middleInitial":"J.S.","affiliations":[{"id":34798,"text":"DFO Canada","active":true,"usgs":false}],"preferred":false,"id":896689,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jude, David J.","contributorId":334847,"corporation":false,"usgs":false,"family":"Jude","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":896690,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boynton, Patrick","contributorId":334848,"corporation":false,"usgs":false,"family":"Boynton","given":"Patrick","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":896691,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rudstam, Lars G. 0000-0002-3732-6368","orcid":"https://orcid.org/0000-0002-3732-6368","contributorId":213508,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":896692,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70260095,"text":"70260095 - 2023 - Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","interactions":[],"lastModifiedDate":"2024-10-28T12:02:39.587199","indexId":"70260095","displayToPublicDate":"2023-09-30T07:00:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","docAbstract":"Cretaceous through Eocene plutonic rocks in northeastern Washington, USA, document a 60 m.y. history of crustal thickening and subsequent collapse and extension in response to two terrane-accretion events. Rocks emplaced 113–53 Ma have increasing La/Yb ratios reflecting orogenic plateau development after arrival of the Insular terrane by 100 Ma. Plutons emplaced 52–45 Ma (the Challis episode) document collapse of this plateau and define a SW-younging age progression attributed to breakoff and rollback of the Farallon slab following accretion of the Siletzia terrane at ca. 50 Ma. All of the rocks have chemical traits of arc magmas, likely inherited from their lower-crustal sources, but low B/Be ratios and the lack of evidence for amphibole fractionation indicate the Eocene magmas formed under drier conditions than are typical of active subduction settings. These magmas also originated at greater depth (eclogitic vs. gabbroic source) and were emplaced more shallowly than the earlier ones. All rocks have overlapping Sr-Nd and O isotopic data, indicating significant contributions from older continental crust, and depleted mantle Nd model ages become older toward the east, defining three regions that correspond with previously inferred lower-crustal domains. Farallon slab rollback also drove extension (core complex formation, dike swarms) and crustal uplift, which, along with voluminous magmatism, define the Challis episode. This tectonic model is further supported by seismic tomography, which has identified remnants of a detached slab in the upper mantle beneath the region.
Streamflow monitoring networks provide information for a wide range of public interests in river and streams. A general approach to evaluate monitoring for different interests is developed to support network planning and design. The approach defines three theoretically distinct information metrics (coverage, resolution, and representation) based on the spatial distribution of a variable of interest. Coverage is the fraction of information that a network can provide about a variable when some areas are not monitored. Resolution is the information available from the network relative to the maximum information possible given the number of sites in the network. Representation is the information that a network provides about a benchmark distribution of a variable. Information is defined using Shannon entropy where the spatial discretization of a variable among spatial elements of a landscape or sites in a network indicates the uncertainty in the spatial distribution of the variable. This approach supports the design of networks for monitoring of variables with heterogeneous spatial distributions (“hot spots” and patches) that might otherwise be unmonitored because they occupy insignificant portions of the landscape. Areas where monitoring will maintain or improve the metrics serve as objective priorities for public interests in network design. The approach is demonstrated for the streamflow monitoring network operated by the United States Geological Survey during water year 2020 indicating gaps in the coverage of coastal rivers and the resolution of low flows.
The lack of contemporary data on contaminants in resident fish prevents an analysis of temporal trends in contaminant concentrations and the present-day status of the “Restrictions on Fish and Wildlife Consumption” Beneficial Use Impairment (BUI) in the Niagara River Area of Concern (AOC). During 2018, concentrations of 260 contaminants in four groups of fish species from five areas in or near the upper Niagara River AOC were analyzed to determine the potential risks from fish consumption, responses to remediation in an adjacent AOC, and whether additional remedial actions were warranted in this AOC. The concentrations of most contaminants were generally undetectable or did not exceed established Federal, State, or European Union fish-consumption limits. Several contaminants without State or Federal limits exceeded European Union fish-consumption guidelines in some species and areas. High PCB residues in many bullhead from Scajaquada Creek, some bass from Hoyt Lake, and most common carp from all areas surpassed certain New York and Federal fish-consumption limits and indicate PCBs continue to restrict fish consumption at most study areas. High concentrations of several contaminants in resident fish, especially dioxins and furans in carp, from Cayuga Creek indicate that additional scrutiny of consumption advisories is warranted in this area. Because this study provides a snapshot in time of fish-contaminant data from five areas, additional data from other areas and times, and more detailed information on present-day pollutant sources may be needed before determining the status of the fish-consumption BUI in this AOC.
Current methods for determining the 1-percent annual exceedance probability (AEP) for a streamflow assume stationarity (the assumption that the statistical distribution of data from past observations does not contain trends and will continue unchanged in the future). This assumption allows the 1-percent AEP to be determined based on historical streamflow records. However, the assumption of stationarity is challenged by observed trends in streamflow records.
In response, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, studied potential changes to the 1-percent AEP streamflows at streamgages in the Housatonic River watershed in Massachusetts, Connecticut, and New York. The study used the Precipitation-Runoff Modeling System—a deterministic hydrologic model. Climate inputs to the model of temperature and precipitation were scaled to anticipated changes based on global climate models that could occur in 2030, 2050, and 2100. The model outputs were used to characterize the 1-percent AEP streamflows for 2030, 2050, and 2100 and compare the results to baseline conditions for 1950 to 2015. Results indicated that the 1-percent AEP streamflow for unregulated streams and rivers may increase from the 1950–2015 baseline period by 7.4, 11.7, and 17.3 percent in 2030, 2050, and 2100, respectively, because of climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235090","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2023, Characterizing changes in the 1-percent annual exceedance probability streamflows for climate-change scenarios in the Housatonic River watershed of Massachusetts, Connecticut, and New York: U.S. Geological Survey Scientific Investigations Report 2023–5090, 16 p., https://doi.org/10.3133/sir20235090.","productDescription":"Report: iv, 16 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149676","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501055,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115441.htm","linkFileType":{"id":5,"text":"html"}},{"id":421394,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CSH0P","text":"USGS data release","linkHelpText":"Data for characterizing changes in the 1-percent annual exceedance probability streamflows for climate change scenarios in the Housatonic River watershed—Massachusetts, Connecticut, and New York"},{"id":421390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5090/coverthb.jpg"},{"id":421391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.pdf","text":"Report","size":"8.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5090"},{"id":421392,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.XML"},{"id":421393,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5090/images"},{"id":421395,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235090/full"}],"country":"United States","state":"Connecticut, Massachusetts, New York","otherGeospatial":"Housatonic River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.73443369971218,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 41.34286607604693\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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Northborough, MA 01532
The San Francisco Bay supports thousands of breeding waterbirds annually and hosts large populations of American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Forster’s terns (Sterna forsteri). These three species have relied largely on former commercial salt ponds in South San Francisco Bay, which provide wetland foraging habitat and island nesting habitat. The South Bay Salt Pond Restoration Project is in the process of restoring 50–90 percent of 15,100 acres of these former salt ponds to tidal marsh and tidal mudflats. Although this restoration is expected to have numerous benefits, including providing habitat for tidal wetland-dependent species, improving water quality, buffering against storm surge, and protecting inland areas from sea level rise, the reduction in former salt pond habitat and nesting islands may negatively affect breeding waterbirds. To address the reduction in former salt pond habitat available to waterbirds, the South Bay Salt Pond Restoration Project also includes enhancements to remaining pond habitat, such as the construction of new islands for nesting. Moreover, the South Bay Salt Pond Restoration Project follows an adaptive management plan in which waterbird response to the changing landscape is monitored over time to ensure that existing breeding waterbird populations are maintained. In this report, we provide results of waterbird nest monitoring in South San Francisco Bay during the 2022 breeding season and present these results in the context of annual nest monitoring in South San Francisco Bay since 2005. Overall, nest abundance in 2022 remained at or near 18-year lows for American avocets (176 nests) and black-necked stilts (97 nests), but Forster’s tern nest abundance (1,727 nests) was at an 18-year high, reversing historically low abundance observed during 2015–2017. In 2022, there were only 6 American avocet, 4 black-necked stilt, and 4 Forster’s tern major colony nesting sites, which is down from annual averages of 12.4, 6.6, and 6.6 observed during 2005–2009. Nest success (30 percent for American avocets, 29 percent for black-necked stilt, and 53 percent for Forster’s terns) was below the 2005–2007 baseline values established for the South Bay Salt Pond Restoration Project. Average egg-hatching success (98 percent, 100 percent, and 90 percent), and clutch sizes (3.68, 3.70, and 2.63 eggs) of American avocets, black-necked stilts, and Forster’s terns, respectively, were similar to values observed during 2005–2010. All three species displayed notable shifts in nest initiation dates in 2022, with American avocets and Forster’s terns nesting 10–11 days earlier and black-necked stilts nesting 10 days later than during 2005–2010. Finally, the enhanced, managed ponds with newly constructed islands (Ponds A16 and SF2) supported 86 percent of all the Forster’s tern nests recorded in South San Francisco Bay in 2022, which is the first time these managed ponds have hosted such a substantial number of tern nests.
","language":"English","publisher":"U.S. Geological Center","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231067","collaboration":"Prepared in cooperation with California State Coastal Conservancy, California Wildlife Foundation, California Department of Fish and Wildlife, U.S. Fish and Wildlife Service, and South Bay Salt Pond Restoration Project","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Ackerman, J.T., Hartman, C.A., and Herzog, M., 2023, Monitoring nesting waterbirds for the South Bay Salt Pond Restoration Project—2022 breeding season: U.S. Geological Survey Open-File Report 2023–1067, 25 p., https://doi.org/10.3133/ofr20231067.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-151077","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":421402,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231067/full"},{"id":421401,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1067/images"},{"id":421400,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.xml"},{"id":421398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1067/covrthb.jpg"},{"id":421399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1067/ofr20231067.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"South Bay Salt Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11258522212694,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.361346093418206\n ],\n [\n -121.87569252193163,\n 37.585319000832044\n ],\n [\n -122.11258522212694,\n 37.585319000832044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
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Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey is creating a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate the integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here to frame the presentation. Centrocercus minimus (Gunnison sage-grouse; hereafter GUSG) has been a focus of scientific investigation since the early 2000s. The U.S. Fish and Wildlife Service listed GUSG as threatened under the Endangered Species Act in 2014 because of declining populations and increasing habitat loss. The U.S. Fish and Wildlife Service, Bureau of Land Management, and Colorado Parks and Wildlife have sought to increase the conservation of this species by adapting management and recovery plans to reduce threats and increase population resiliency. GUSG are studied less than the closely related Centrocercus urophasianus (greater sage-grouse); however, research efforts have recently increased to understand the life history, genetics, and habitat suitability of this sagebrush-obligate species. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and U.S. Geological Survey Open-File Reports) on GUSG, published between January 2005 and September 2022. We first systematically searched three reference databases and three government databases using the following search phrases: “Gunnison sage-grouse” or “lesser sage-grouse” or “Gunnison grouse” or “Gunnison sage grouse” or “lesser sage grouse” or “Centrocercus minimus.” We refined the initial list of products by removing (1) duplicates, (2) publications that were not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products that did not have GUSG as a research focus or products that did not present new data or findings about GUSG. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified the management topics (for example, population estimates or targets, habitat, and management efforts) addressed by each product. We also noted which publications included new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and a formal peer review. Our initial searches resulted in 80 total products, of which 63 met our criteria for inclusion of which 53 were products that had not been summarized before. Across products summarized in the annotated bibliography, broad-scale habitat characteristics; population estimates or targets; behavior or demographics; and genetics were the most commonly addressed management topics. The bibliographies are available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers) and are searchable by topic, location, and year, and the search tool includes links to each original publication. The studies compiled and summarized in this annotated bibliography may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GUSG populations across the GUSG range.
","publisher":"U S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231079","usgsCitation":"Maxwell, L.M., Teige, E.C., Jordan, S.E., Rutherford, T.K., Samuel, E.M., Selby, L.B., Foster, A.C., Kleist, N.J., and Carter, S.K., 2023, Annotated bibliography of scientific research on Gunnison sage-grouse published from January 2005 to September 2022: U.S. Geological Survey Open-File Report 2023–1079, 52 p., https://doi.org/10.3133/ofr20231079.","productDescription":"vii, 52 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":421428,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1079"},{"id":421397,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.xml"},{"id":421355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1079"},{"id":421396,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1079/images"},{"id":421354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1079/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.12083328575649,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 39.47396881795231\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2922","usgsCitation":"Bertuol-Garcia, D., Ladouceur, E., Brudvig, L.A., Laughlin, D.C., Munson, S.M., Curran, M.F., Davies, K.W., Svejcar, L.N., and Shackelford, N., 2023, Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity: Ecological Applications, v. 33, e2922, 21 p., https://doi.org/10.1002/eap.2922.","productDescription":"e2922, 21 p.","ipdsId":"IP-153040","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":441997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2922","text":"Publisher Index Page"},{"id":427818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Continental United States","geographicExtents":"{\n \"type\": 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Canada","active":true,"usgs":false}],"preferred":false,"id":898925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ladouceur, Emma","contributorId":270938,"corporation":false,"usgs":false,"family":"Ladouceur","given":"Emma","email":"","affiliations":[{"id":56222,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Biodiversity Synthesis & Physiological Diversity","active":true,"usgs":false}],"preferred":false,"id":898926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brudvig, Lars A.","contributorId":335644,"corporation":false,"usgs":false,"family":"Brudvig","given":"Lars","email":"","middleInitial":"A.","affiliations":[{"id":80453,"text":"Department of Plant Biology and Program in Ecology, Evolution, and Behavior, Michigan State University, Lansing, MI, USA","active":true,"usgs":false}],"preferred":false,"id":898927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laughlin, Daniel C.","contributorId":200543,"corporation":false,"usgs":false,"family":"Laughlin","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":898928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Curran, Michael F.","contributorId":261573,"corporation":false,"usgs":false,"family":"Curran","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":52887,"text":"Program in Ecology, University of Wyoming, 1000 E. University Avenue, Laramie, WY, USA 82071","active":true,"usgs":false}],"preferred":false,"id":898930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":898931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Svejcar, Lauren N.","contributorId":127492,"corporation":false,"usgs":false,"family":"Svejcar","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":898932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shackelford, Nancy","contributorId":261567,"corporation":false,"usgs":false,"family":"Shackelford","given":"Nancy","email":"","affiliations":[{"id":52880,"text":"Ecology and Evolutionary Biology, University of Colorado Boulder, 1900 Pleasant St, Boulder, Colorado 80309, USA","active":true,"usgs":false}],"preferred":false,"id":898933,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70249184,"text":"sir20235107 - 2023 - Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","interactions":[],"lastModifiedDate":"2025-07-28T13:13:06.240353","indexId":"sir20235107","displayToPublicDate":"2023-09-29T09:18:15","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":"2023-5107","displayTitle":"Assessing the Effects of Chloride Deicer Applications on Groundwater near the Siskiyou Pass, Southwestern Oregon, July 2018–February 2021","title":"Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","docAbstract":"The U.S. Geological Survey, in cooperation with the Oregon Department of Transportation (ODOT), evaluated the effects of cold-weather chloride deicers (road deicing chemicals) on groundwater quality, with a focus on chloride, near the Siskiyou Pass in southwestern Oregon. The study covered the period during July 2018 through February 2021. Between the years 2016 and 2020 ODOT applied up to 16,000 gallons per mile of chloride deicer and 143,000 pounds per mile of road salt along an 11-mile stretch of Interstate 5 (I-5) through the Siskiyou Pass. Despite the benefit of safer driving conditions, there are potentially negative environmental effects associated with the use of chloride-based deicers (such as magnesium chloride and sodium chloride). The results from this study are intended to help ODOT assess the water-quality effects from the application of chloride deicers at the Siskiyou Pass and inform decisions on how those chemicals are used.
Dissolved chloride concentrations tended to be greater in groundwater downgradient from I-5 compared to groundwater upgradient from the interstate. Specific conductance was a good predictor of dissolved chloride concentration (R2 = 0.905). Continuous monitoring showed that specific conductance measurements were greater at four downgradient spring-fed sites at the end of the study period compared with measurements at the beginning of the study. The study results indicate that chloride levels in shallow groundwater downgradient from I-5 are increasing, but dissolved chloride concentrations in domestic wells are not above the U.S. Environmental Protection Agency drinking water recommendations. The approach and methods used in this study, with modifications as site conditions warrant, can be applied in other areas of chloride deicer application to determine if groundwater is affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235107","collaboration":"Prepared in cooperation with Oregon Department of Transportation","usgsCitation":"Gingerich, S.B., Wise, D.R., and Stonewall, A.J., 2023, Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021 (ver. 1.1, July 2025): U.S. Geological Survey Scientific Investigations Report 2023–5107, 39 p., https://doi.org/10.3133/sir20235107.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140151","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":492943,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5107/versionHistory.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":421408,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6XDIJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Specific conductance and other groundwater quality data, Siskiyou Pass area, southwestern Oregon, 2018 to 2021"},{"id":421403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5107/coverthb2.jpg"},{"id":421404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5107"},{"id":421405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235107/full","text":"Report","description":"SIR 2023-5107"},{"id":421406,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5107/images"},{"id":421407,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.XML"},{"id":421409,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107_appendix1.xlsx","text":"Appendix 1","size":"45 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2023-5107 Appendix 1"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.79414603940278,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 42.22368397834566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 29, 2023; Version 1.1: July 25, 2025","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
Introduction: Large dam removals provide a restoration opportunity for shrinking coastal wetland habitats. Dam removal can increase sediment delivery to sediment-starved river deltas and estuaries by restoring natural sediment transport and mobilizing reservoir-impounded sediment. However, rapid mobilization of massive quantities of sediment stored behind large dams also constitutes a major ecological perturbation. Information is lacking on coastal habitat responses to sediment pulses of this magnitude.
Methods: Removal of two large dams along the Elwha River (Washington, USA) in 2011–2014 released ~20.5 Mt of impounded sediment, ~5.4 Mt of which were deposited in the delta and estuary (hereafter, delta). We used time series of aerial imagery, digital elevation models, and vegetation field sampling to examine plant community responses to this sediment pulse across seven years during and after dam removal.
Results: Between 2011 and 2018, the Elwha River delta increased by ~26.8 ha. Vegetation colonized ~16.4 ha of new surfaces, with mixed pioneer vegetation on supratidal beach, river bars, and river mouth bars and emergent marsh vegetation in intertidal aquatic habitats. Colonization occurred on surfaces that were higher and more stable in elevation and farther from the shoreline. Compared to established delta plant communities, vegetation on new surfaces had lower cover of dominant species and functional groups, with very low woody cover, and lower graminoid cover than dunegrass and emergent marsh communities. Over time following surface stabilization, however, vegetation on new surfaces increased in species richness, cover, and similarity to established communities. By 2018, ~1.0 ha of vegetation on new surfaces had developed into dunegrass or willow–alder communities and ~5.9 ha had developed into emergent marsh. At the same time, dam removal had few discernible effects on established delta plant communities.
Discussion: Together, these results suggest that rapid sediment mobilization during large dam removal has potential to expand coastal wetland habitat without negatively affecting established plant communities. However, as sediment loads declined in 2016–2018, new delta surfaces decreased by ~4.5 ha, and ~1.6 ha of new vegetation reverted to no vegetation. Long-term persistence of the expanded coastal habitat will depend on ongoing erosional and depositional processes under the restored natural sediment regime.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1233903","usgsCitation":"Perry, L.G., Shafroth, P., Alfieri, S.J., and Miller, I.M., 2023, Coastal vegetation responses to large dam removal on the Elwha River: Frontiers in Ecology and Evolution, v. 11, 1233903, 21 p., https://doi.org/10.3389/fevo.2023.1233903.","productDescription":"1233903, 21 p.","ipdsId":"IP-153758","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442000,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1233903","text":"Publisher Index Page"},{"id":435165,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O6NML1","text":"USGS data release","linkHelpText":"Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys"},{"id":422399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.8042115532547,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 48.18296274689851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G.","contributorId":220048,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":887673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alfieri, Samuel J.","contributorId":329742,"corporation":false,"usgs":false,"family":"Alfieri","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":78705,"text":"self","active":true,"usgs":false}],"preferred":false,"id":887675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887676,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249968,"text":"70249968 - 2023 - Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","interactions":[],"lastModifiedDate":"2024-07-17T21:34:54.964345","indexId":"70249968","displayToPublicDate":"2023-09-29T07:00:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","docAbstract":"Biocrusts are sensitive to changes in livestock grazing intensity in arid rangelands and may be useful indicators of ecosystem functions, particularly soil properties like soil stability, which may suggest the potential for soil erosion. We compared biocrust community composition and surface soil stability in a big sagebrush (Artemisia tridentata) steppe rangeland in the northwestern Great Basin in several paired sites, with or without long-term cattle grazing exclusion, and similar soils (mostly sandy loams), climate, and vegetation composition. We found that livestock grazing was associated with both lower surface soil stability and cover of several biocrust morphogroups, especially lichens, compared with sites with long-term livestock exclusion. Surface soil stability did not modify the effects of grazing on most biocrust components via interactive effects. Livestock grazing effects on total biocrust cover were partially mediated by changes in surface soil stability. Though lichens were more sensitive to grazing disturbance, our results suggest that moss (mostly Tortula ruralis in this site) might be a more readily observable indicator of grazing-related soil stability change in this area due to their relatively higher abundance compared with lichens (moss: mean, 8.5% cover, maximum, 96.1%, lichens: mean, 1.0% cover, maximum, 14.1%). These results highlight the potential for biocrust components as sensitive indicators of change in soil-related ecosystem functions in sagebrush steppe rangelands. However, further research is needed to identify relevant indicator groups across the wide range of biocrust community composition associated with site environmental characteristics, variable grazing systems, other rangeland health metrics, and other disturbance types such as wildfire.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2023.09.001","usgsCitation":"Copeland, S., Condon, L.A., Rosentreter, R., Miller, J., and Kahn-Abrams, M., 2023, Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin: Rangeland Ecology & Management, v. 91, p. 82-86, https://doi.org/10.1016/j.rama.2023.09.001.","productDescription":"5 p.","startPage":"82","endPage":"86","ipdsId":"IP-147342","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442004,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2023.09.001","text":"Publisher Index Page"},{"id":422476,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","volume":"91","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":887850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosentreter, Roger","contributorId":257441,"corporation":false,"usgs":false,"family":"Rosentreter","given":"Roger","affiliations":[{"id":52018,"text":"Biology Department, Boise State University, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":887852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Jesse","contributorId":147734,"corporation":false,"usgs":false,"family":"Miller","given":"Jesse","email":"","affiliations":[{"id":16916,"text":"Dept. of Zoology, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":887853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kahn-Abrams, Maya","contributorId":331492,"corporation":false,"usgs":false,"family":"Kahn-Abrams","given":"Maya","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":887854,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251891,"text":"70251891 - 2023 - Benchmarking satellite-derived shoreline mapping algorithms","interactions":[],"lastModifiedDate":"2024-03-05T13:03:29.556435","indexId":"70251891","displayToPublicDate":"2023-09-29T06:59:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Benchmarking satellite-derived shoreline mapping algorithms","docAbstract":"Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.