Carbon capture from stationary sources and geologic storage of carbon dioxide (CO2) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO2 storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO2, consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO2 storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO2 injection will be mitigated by reservoir pressure management, estimates of the costs of CO2 storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO2 storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO2 storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the scarcity of (data from) long-term commercial-scale CO2 storage projects, decision makers may experience considerable difficulty in ascertaining the realistic potential, the likely costs, and the most beneficial pattern of deployment of CCS as an option to reduce CO2 concentrations in the atmosphere.
","language":"English","publisher":"Springer","doi":"10.1007/s11053-016-9310-7","usgsCitation":"Anderson, S.T., 2017, Cost implications of uncertainty in CO2 storage resource estimates: A review: Natural Resources Research, v. 26, no. 2, p. 137-159, https://doi.org/10.1007/s11053-016-9310-7.","productDescription":"23 p.","startPage":"137","endPage":"159","ipdsId":"IP-069500","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":470014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-016-9310-7","text":"Publisher Index Page"},{"id":337513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-30","publicationStatus":"PW","scienceBaseUri":"58c90122e4b0849ce97abca7","contributors":{"authors":[{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":683988,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185014,"text":"70185014 - 2017 - A science of integration: frameworks, processes, and products in a place-based, integrative study","interactions":[],"lastModifiedDate":"2017-03-29T11:42:20","indexId":"70185014","displayToPublicDate":"2017-03-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5318,"text":"Sustainability Science","active":true,"publicationSubtype":{"id":10}},"title":"A science of integration: frameworks, processes, and products in a place-based, integrative study","docAbstract":"Integrative research is increasingly a priority within the scientific community and is a central goal for the evolving field of sustainability science. While it is conceptually attractive, its successful implementation has been challenging and recent work suggests that the move towards interdisciplinarity and transdisciplinarity in sustainability science is being only partially realized. To address this from the perspective of social-ecological systems (SES) research, we examine the process of conducting a science of integration within the Southcentral Alaska Test Case (SCTC) of Alaska-EPSCoR as a test-bed for this approach. The SCTC is part of a large, 5 year, interdisciplinary study investigating changing environments and adaptations to those changes in Alaska. In this paper, we review progress toward a science of integration and present our efforts to confront the practical issues of applying proposed integration frameworks. We: (1) define our integration framework; (2) describe the collaborative processes, including the co-development of science through stakeholder engagement and partnerships; and (3) illustrate potential products of integrative, social-ecological systems research. The approaches we use can also be applied outside of this particular framework. We highlight challenges and propose improvements for integration in sustainability science by addressing the need for common frameworks and improved contextual understanding. These insights may be useful for capacity-building for interdisciplinary projects that address complex real-world social and environmental problems.
","language":"English","publisher":"Springer","doi":"10.1007/s11625-016-0391-3","usgsCitation":"Kliskey, A., Alessa, L., Wandersee, S., Williams, P., Trammell, J., Powell, J., Grunblatt, J., and Wipfli, M.S., 2017, A science of integration: frameworks, processes, and products in a place-based, integrative study: Sustainability Science, v. 12, no. 2, p. 293-303, https://doi.org/10.1007/s11625-016-0391-3.","productDescription":"11 p.","startPage":"293","endPage":"303","ipdsId":"IP-065205","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":337522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-03","publicationStatus":"PW","scienceBaseUri":"58c90122e4b0849ce97abcaa","contributors":{"authors":[{"text":"Kliskey, Andrew","contributorId":189256,"corporation":false,"usgs":false,"family":"Kliskey","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":684262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alessa, Lilian","contributorId":189257,"corporation":false,"usgs":false,"family":"Alessa","given":"Lilian","email":"","affiliations":[],"preferred":false,"id":684263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wandersee, Sarah","contributorId":189258,"corporation":false,"usgs":false,"family":"Wandersee","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":684264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Paula","contributorId":189259,"corporation":false,"usgs":false,"family":"Williams","given":"Paula","email":"","affiliations":[],"preferred":false,"id":684265,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trammell, Jamie","contributorId":189260,"corporation":false,"usgs":false,"family":"Trammell","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":684266,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Powell, Jim","contributorId":178178,"corporation":false,"usgs":false,"family":"Powell","given":"Jim","email":"","affiliations":[],"preferred":false,"id":684267,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grunblatt, Jess","contributorId":189261,"corporation":false,"usgs":false,"family":"Grunblatt","given":"Jess","email":"","affiliations":[],"preferred":false,"id":684268,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":683956,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70184973,"text":"70184973 - 2017 - Evaluation of a method using survey counts and tag data to estimate the number of Pacific walruses (Odobenus rosmarus divergens) using a coastal haulout in northwestern Alaska","interactions":[],"lastModifiedDate":"2018-06-16T17:44:45","indexId":"70184973","displayToPublicDate":"2017-03-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a method using survey counts and tag data to estimate the number of Pacific walruses (Odobenus rosmarus divergens) using a coastal haulout in northwestern Alaska","docAbstract":"Increased periods of sparse sea ice over the continental shelf of the Chukchi Sea in late summer have reduced offshore haulout habitat for Pacific walruses (Odobenus rosmarus divergens) and increased opportunities for human activities in the region. Knowing how many walruses could be affected by human activities would be useful to conservation decisions. Currently, there are no adequate estimates of walrus abundance in the northeastern Chukchi Sea during summer–early autumn. Estimating abundance in autumn might be possible from coastal surveys of hauled out walruses during periods when offshore sea ice is unavailable to walruses. We evaluated methods to estimate the size of the walrus population that was using a haulout on the coast of northwestern Alaska in autumn by using aerial photography to count the number of hauled out walruses (herd size) and data from 37 tagged walruses to estimate availability (proportion of population hauled out). We used two methods to estimate availability, direct proportions of hauled out tagged walruses and smoothed proportions using local polynomial regression. Point estimates of herd size (4200–38,000 walruses) and total population size (76,000–287,000 walruses) ranged widely among days and between the two methods of estimating availability. Estimates of population size were influenced most by variation in estimates of availability. Coastal surveys might be improved most by counting walruses when the greatest numbers are hauled out, thereby reducing the influence of availability on population size estimates. The chance of collecting data during peak haulout periods would be improved by conducting multiple surveys.
","language":"English","publisher":"Springer","doi":"10.1007/s00300-016-2060-5","usgsCitation":"Battaile, B., Jay, C.V., Udevitz, M.S., and Fischbach, A.S., 2017, Evaluation of a method using survey counts and tag data to estimate the number of Pacific walruses (Odobenus rosmarus divergens) using a coastal haulout in northwestern Alaska: Polar Biology, v. 40, no. 7, p. 1359-1369, https://doi.org/10.1007/s00300-016-2060-5.","productDescription":"11 p.","startPage":"1359","endPage":"1369","ipdsId":"IP-070731","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438417,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B27SB2","text":"USGS data release","linkHelpText":"Walrus Haulout Photographs Near Pt. Lay Alaska, September 2014"},{"id":337549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58c90123e4b0849ce97abcb2","contributors":{"authors":[{"text":"Battaile, Brian bbattaile@usgs.gov","contributorId":189069,"corporation":false,"usgs":true,"family":"Battaile","given":"Brian","email":"bbattaile@usgs.gov","affiliations":[],"preferred":true,"id":683780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":684324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":684325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":684326,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179983,"text":"sir20175003 - 2017 - Egg deposition by lithophilic-spawning fishes in the Detroit and Saint Clair Rivers, 2005–14","interactions":[],"lastModifiedDate":"2017-03-14T09:54:34","indexId":"sir20175003","displayToPublicDate":"2017-03-14T00:00:00","publicationYear":"2017","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":"2017-5003","title":"Egg deposition by lithophilic-spawning fishes in the Detroit and Saint Clair Rivers, 2005–14","docAbstract":"A long-term, multiseason, fish egg sampling program conducted annually on the Detroit (2005–14) and Saint Clair (2010–14) Rivers was summarized to identify where productive fish spawning habitat currently exists. Egg mats were placed on the river bottom during the spring and fall at historic spawning areas and candidate fish spawning habitat restoration sites throughout both rivers. Widespread evidence was found of lithophilic spawning by numerous native fish species, including walleye (Sander vitreus), lake whitefish (Coregonus clupeaformis), lake sturgeon (Acipenser fulvescens), suckers (Catostomidae spp.), and trout-perch (Percopsis omiscomaycus). Walleye, lake whitefish, and suckers spp. spawned in nearly every region of each river in all years on both reef and nonreef substrates. Lake sturgeon eggs were collected almost exclusively over constructed reefs. Catch-per-unit effort of walleye, lake whitefish, and sucker eggs was much greater in the Detroit River than in the Saint Clair River, while Saint Clair River sites supported the greatest collections of lake sturgeon eggs. Collections during this study of lake sturgeon eggs on man-made spawning reefs suggest that artificial reefs may be an effective tool for restoring fish populations in the Detroit and Saint Clair Rivers; however, the quick response of lake sturgeon to spawn on newly constructed reefs and the fact that walleye, lake whitefish, and sucker eggs were often collected over substrate with little interstitial space to protect eggs from siltation and predators suggests that lack of suitable spawning habitat may continue to limit reproduction of lithophilic-spawning fish species in the Saint Clair-Detroit River System.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175003","usgsCitation":"Prichard, C.G., Craig, J.M., Roseman, E.F., Fischer, J.L., Manny, B.A., and Kennedy, G.W., 2017, Egg deposition by lithophilic-spawning fishes in the Detroit and Saint Clair Rivers, 2005–14: U.S. Geological Survey Scientific Investigations Report 2017–5003, 20 p., https://doi.org/10.3133/sir20175003.","productDescription":"v, 20 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-077705","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":438421,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MMM8OT","text":"USGS data release","linkHelpText":"Fish eggs collected in the St. Clair, Detroit, and St. Marys rivers, 2005-2022"},{"id":438420,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VD6WPH","text":"USGS data release","linkHelpText":"Fish eggs collected in the St. Clair and Detroit rivers, 2005-2016"},{"id":337150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5003/sir20175003.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5003"},{"id":337147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5003/coverthb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Detroit River, Lake Erie, Lake Huron, Saint Clair River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.29833984375,\n 41.95949009892467\n ],\n [\n -82.177734375,\n 41.95949009892467\n ],\n [\n -82.177734375,\n 43.06086137134326\n ],\n [\n -83.29833984375,\n 43.06086137134326\n ],\n [\n -83.29833984375,\n 41.95949009892467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Great Lakes Science Center
U.S. Geological Survey
1451 Green Rd.
Ann Arbor, MI 48105
Natural selection as a result of plant–plant interactions can lead to local biotic adaptation. This may occur where species frequently interact and compete intensely for resources limiting growth, survival, and reproduction. Selection is demonstrated by comparing a genotype interacting with con- or hetero-specific sympatric neighbor genotypes with a shared site-level history (derived from the same source location), to the same genotype interacting with foreign neighbor genotypes (from different sources). Better genotype performance in sympatric than allopatric neighborhoods provides evidence of local biotic adaptation. This pattern might be explained by selection to avoid competition by shifting resource niches (differentiation) or by interactions benefitting one or more members (facilitation). We tested for local biotic adaptation among two riparian trees, Populus fremontii and Salix gooddingii, and the shrub Salix exigua by transplanting replicated genotypes from multiple source locations to a 17 000 tree common garden with sympatric and allopatric treatments along the Colorado River in California. Three major patterns were observed: 1) across species, 62 of 88 genotypes grew faster with sympatric neighbors than allopatric neighbors; 2) these growth rates, on an individual tree basis, were 44, 15 and 33% higher in sympatric than allopatric treatments for P. fremontii, S. exigua and S. gooddingii, respectively, and; 3) survivorship was higher in sympatric treatments for P. fremontiiand S. exigua. These results support the view that fitness of foundation species supporting diverse communities and dominating ecosystem processes is determined by adaptive interactions among multiple plant species with the outcome that performance depends on the genetic identity of plant neighbors. The occurrence of evolution in a plant-community context for trees and shrubs builds on ecological evolutionary research that has demonstrated co-evolution among herbaceous taxa, and evolution of native species during exotic plants invasion, and taken together, refutes the concept that plant communities are always random associations.
","language":"English","publisher":"Wiley","doi":"10.1111/oik.03240","usgsCitation":"Grady, K.C., Wood, T.E., Kolb, T.E., Hersch-Green, E., Shuster, S.M., Gehring, C.A., Hart, S.C., Allan, G.J., and Whitham, T.G., 2017, Local biotic adaptation of trees and shrubs to plant neighbors: Oikos, v. 126, no. 4, p. 583-593, https://doi.org/10.1111/oik.03240.","productDescription":"11 p.","startPage":"583","endPage":"593","ipdsId":"IP-060158","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470015,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/59p2b4xv","text":"External Repository"},{"id":337546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.850830078125,\n 30.95876857077987\n ],\n [\n -110.247802734375,\n 30.95876857077987\n ],\n [\n -110.247802734375,\n 35.41591492345623\n ],\n [\n -115.850830078125,\n 35.41591492345623\n ],\n [\n -115.850830078125,\n 30.95876857077987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-05","publicationStatus":"PW","scienceBaseUri":"58c90123e4b0849ce97abcb0","contributors":{"authors":[{"text":"Grady, Kevin C.","contributorId":174325,"corporation":false,"usgs":false,"family":"Grady","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":27415,"text":"School of Forestry, Northern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":683789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Troy E. 0000-0002-1533-5714 twood@usgs.gov","orcid":"https://orcid.org/0000-0002-1533-5714","contributorId":4023,"corporation":false,"usgs":true,"family":"Wood","given":"Troy","email":"twood@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":683788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolb, Thomas E.","contributorId":189073,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hersch-Green, Erika","contributorId":189077,"corporation":false,"usgs":false,"family":"Hersch-Green","given":"Erika","email":"","affiliations":[],"preferred":false,"id":683796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shuster, Stephen M.","contributorId":174326,"corporation":false,"usgs":false,"family":"Shuster","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":27416,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Nothern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":683791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gehring, Catherine A.","contributorId":189076,"corporation":false,"usgs":false,"family":"Gehring","given":"Catherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":683794,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Stephen C.","contributorId":189074,"corporation":false,"usgs":false,"family":"Hart","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":683792,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allan, Gerard J.","contributorId":189075,"corporation":false,"usgs":false,"family":"Allan","given":"Gerard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":683793,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitham, Thomas G.","contributorId":174327,"corporation":false,"usgs":false,"family":"Whitham","given":"Thomas","email":"","middleInitial":"G.","affiliations":[{"id":27416,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Nothern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":683795,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70185664,"text":"70185664 - 2017 - Molecular analyses reveal high species diversity of trematodes in a sub-Arctic lake","interactions":[],"lastModifiedDate":"2017-11-27T12:43:19","indexId":"70185664","displayToPublicDate":"2017-03-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2024,"text":"International Journal for Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Molecular analyses reveal high species diversity of trematodes in a sub-Arctic lake","docAbstract":"To identify trematode diversity and life-cycles in the sub-Arctic Lake Takvatn, Norway, we characterised 120 trematode isolates from mollusc first intermediate hosts, metacercariae from second intermediate host fishes and invertebrates, and adults from fish and invertebrate definitive hosts, using molecular techniques. Phylogenies based on nuclear and/or mtDNA revealed high species richness (24 species or species-level genetic lineages), and uncovered trematode diversity (16 putative new species) from five families typical in lake ecosystems (Allocreadiidae, Diplostomidae, Plagiorchiidae, Schistosomatidae and Strigeidae). Sampling potential invertebrate hosts allowed matching of sequence data for different stages, thus achieving molecular elucidation of trematode life-cycles and exploration of host-parasite interactions. Phylogenetic analyses also helped identify three major mollusc intermediate hosts (Radix balthica, Pisidium casertanum and Sphaerium sp.) in the lake. Our findings increase the known trematode diversity at the sub-Arctic Lake Takvatn, showing that digenean diversity is high in this otherwise depauperate sub-Arctic freshwater ecosystem, and indicating that sub-Arctic and Arctic ecosystems may be characterised by unique trematode assemblages.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijpara.2016.12.008","usgsCitation":"Soldanova, M., Georgieva, S., Rohacovaa, J., Knudsen, R., Kuhn, J.A., Henriksen, E.H., Siwertsson, A., Shaw, J.C., Kuris, A.M., Amundsen, P., Scholz, T., Lafferty, K.D., and Kostadinova, A., 2017, Molecular analyses reveal high species diversity of trematodes in a sub-Arctic lake: International Journal for Parasitology, v. 47, no. 6, p. 327-345, https://doi.org/10.1016/j.ijpara.2016.12.008.","productDescription":"19 p. 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climate variables for Puerto Rico and the US Caribbean","interactions":[],"lastModifiedDate":"2020-12-11T21:09:52.907025","indexId":"70191915","displayToPublicDate":"2017-03-13T15:02:52","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":7461,"text":"Final Project Memorandum","active":true,"publicationSubtype":{"id":9}},"seriesNumber":"557-271","title":"Developing multi-model ensemble projections of ecologically relevant climate variables for Puerto Rico and the US Caribbean","docAbstract":"The global increases in surface air temperature are the most widespread and direct consequence of anthropogenic climate change. However, while 21st century temperatures are projected to increase in the Caribbean, the low variability and high average temperatures suggest that impacts on ecosystems and water resources are more likely through changes to the availability, timing, and pattern of moisture. The lack of local-scale climate model information that can resolve the complex topography and small scale climate features hinders the development of robust adaptation strategies. The goal of this project was to develop a suite of local-scale climate projections using dynamic downscaling to aid the development of adaptation strategies in Puerto Rico and the U.S. Virgin Islands (USVI). This project began by engaging the ecologists, hydrologists, and conservation biologists in the region to determine the most valuable types of information to aid research and decision making. The final product provides projections of future climate at a 2km horizontal resolution based on three global climate models and two regional climate models for a scenario with high greenhouse gas emissions. Results from the projections suggest that for Puerto Rico, annual temperature would increase between 1°C and 1.3°C by mid-century with larger temperature increases located in the interior portion of the island. Precipitation totals decrease for much of the island with island average decline between 12% and 19%, with some potentially large localized decreases exceeding 30%. The projected changes for the USVI are dominated by the surrounding ocean environment. The resulting projections will be provided to stakeholders in the region via the USGS and the CLCC.","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Terando, A., 2017, Developing multi-model ensemble projections of ecologically relevant climate variables for Puerto Rico and the US Caribbean: Final Project Memorandum 557-271, 20 p.","productDescription":"20 p.","ipdsId":"IP-085236","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":381228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346905,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/wp-content/uploads/sites/14/2020/01/020-Final-Memo-Terando.pdf"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"US Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.181884765625,\n 18.07275691457901\n ],\n [\n -65.203857421875,\n 18.3858049312974\n ],\n [\n -66.588134765625,\n 18.646245142670608\n ],\n [\n -67.291259765625,\n 18.594188856740413\n ],\n [\n -67.39013671875,\n 18.15629140283545\n ],\n [\n -67.060546875,\n 17.78007412664325\n ],\n [\n -65.599365234375,\n 17.895114303749143\n ],\n [\n -65.181884765625,\n 18.07275691457901\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.43756103515625,\n 17.712060974461494\n ],\n [\n -64.64630126953125,\n 18.367559302479318\n ],\n [\n -64.7479248046875,\n 18.404048629104647\n ],\n [\n -64.9017333984375,\n 18.474399059267128\n ],\n [\n -65.0665283203125,\n 18.432713391700858\n ],\n [\n -65.1214599609375,\n 18.34931174429646\n ],\n [\n -65.07202148437499,\n 17.63616972425169\n ],\n [\n -64.76165771484375,\n 17.589048722297875\n ],\n [\n -64.43756103515625,\n 17.712060974461494\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terando, Adam 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":197511,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713675,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185060,"text":"70185060 - 2017 - Geochemistry of host rocks in the Howards Pass district, Yukon-Northwest Territories, Canada: implications for sedimentary environments of Zn-Pb and phosphate mineralization","interactions":[],"lastModifiedDate":"2017-03-22T14:41:40","indexId":"70185060","displayToPublicDate":"2017-03-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of host rocks in the Howards Pass district, Yukon-Northwest Territories, Canada: implications for sedimentary environments of Zn-Pb and phosphate mineralization","docAbstract":"Detailed lithogeochemical data are reported here on early Paleozoic sedimentary rocks that host the large Howards Pass stratiform Zn-Pb deposits in Yukon-Northwest Territories. Redox-sensitive trace elements (Mo, Re, V, U) and Ce anomalies in members of the Duo Lake Formation record significant environmental changes. During the deposition of lower footwall units (Pyritic siliceous and Calcareous mudstone members), bottom waters were anoxic and sulphidic, respectively; these members formed in a marginal basin that may have become increasingly restricted with time. Relative to lower members, a major environmental change is proposed for deposition of the overlying Lower cherty mudstone member, which contains phosphorite beds up to ∼0.8 m thick in the upper part, near the base of the Zn-Pb deposits. The presence of these beds, together with models for modern phosphorite formation, suggests P input from an upwelling system and phosphorite deposition in an upper slope or outer shelf setting. The overlying Active mudstone member contains stratabound to stratiform Zn-Pb deposits within black mudstone and gray calcareous mudstone. Data for unmineralized black mudstone in this member indicate deposition under diverse redox conditions from suboxic to sulphidic. Especially distinctive in this member are uniformly low ratios of light to heavy rare earth elements that are unique within the Duo Lake Formation, attributed here to the dissolution of sedimentary apatite by downward-percolating acidic metalliferous brines. Strata that overlie the Active member (Upper siliceous mudstone member) consist mainly of black mudstone with thin (0.5–1.5 cm) laminae of fine-grained apatite, recording continued deposition on an upper slope or outer shelf under predominantly suboxic bottom waters. Results of this study suggest that exploration for similar stratiform sediment-hosted Zn-Pb deposits should include the outer parts of ancient continental margins, especially at and near stratigraphic transitions from marginal basin facies to overlying slope or shelf facies.
","language":"English","publisher":"Springer","doi":"10.1007/s00126-016-0680-x","usgsCitation":"Slack, J.F., Falck, H., Kelley, K.D., and Xue, G.G., 2017, Geochemistry of host rocks in the Howards Pass district, Yukon-Northwest Territories, Canada: implications for sedimentary environments of Zn-Pb and phosphate mineralization: Mineralium Deposita, v. 52, no. 4, p. 565-593, https://doi.org/10.1007/s00126-016-0680-x.","productDescription":"29 p.","startPage":"565","endPage":"593","ipdsId":"IP-076693","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":337465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-05","publicationStatus":"PW","scienceBaseUri":"58c7af9be4b0849ce9795e72","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":684113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falck, Hendrik","contributorId":167705,"corporation":false,"usgs":false,"family":"Falck","given":"Hendrik","email":"","affiliations":[{"id":24811,"text":"NWT Geoscience Office, Yellowknife, Canada","active":true,"usgs":false}],"preferred":false,"id":684114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen D. kdkelley@usgs.gov","contributorId":431,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":684115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Gabriel G.","contributorId":189206,"corporation":false,"usgs":false,"family":"Xue","given":"Gabriel","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":684116,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185003,"text":"70185003 - 2017 - Territory occupancy and breeding success of Peregrine Falcons Falco peregrinus at various stages of population recovery","interactions":[],"lastModifiedDate":"2017-03-13T13:43:38","indexId":"70185003","displayToPublicDate":"2017-03-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Territory occupancy and breeding success of Peregrine Falcons Falco peregrinus at various stages of population recovery","docAbstract":"Organochlorine pesticides disrupted reproduction and killed many raptorial birds, and contributed to population declines during the 1940s to 1970s. We sought to discern whether and to what extent territory occupancy and breeding success changed from the pesticide era to recent years in a resident population of Peregrine Falcons Falco peregrinus in southern Scotland using long-term (1964–2015) field data and multi-state, multi-season occupancy models. Peregrine territories that were occupied with successful reproduction in one year were much more likely to be occupied and experience reproductive success in the following year, compared with those that were unoccupied or occupied by unsuccessful breeders in the previous year. Probability of territory occupancy differed between territories in the eastern and western parts of the study area, and varied over time. The probability of occupancy of territories that were unoccupied and those that were occupied with successful reproduction during the previous breeding season generally increased over time, whereas the probability of occupancy of territories that were occupied after failed reproduction decreased. The probability of reproductive success (conditional on occupancy) in territories that were occupied during the previous breeding season increased over time. Specifically, for territories that had been successful in the previous year, the probability of occupancy as well as reproductive success increased steadily over time; these probabilities were substantially higher in recent years than earlier, when the population was still exposed to direct or residual effects of organochlorine pesticides. These results are consistent with the hypothesis that progressive reduction, followed by a complete ban, in the use of organochlorine pesticides improved reproductive success of Peregrines in southern Scotland. Differences in the temporal pattern of probability of reproductive success between south-eastern and south-western Scotland suggest that the effect of organochlorine pesticides on Peregrine reproductive success and/or the recovery from pesticide effects varied geographically and was possibly affected by other factors such as persecution.
","language":"English","publisher":"Ibis Society","publisherLocation":"London","doi":"10.1111/ibi.12443","usgsCitation":"McGrady, M.J., Hines, J.E., Rollie, C., Smith, G.D., Morton, E.R., Moore, J.F., Mearns, R.M., Newton, I., Murillo-Garcia, O.E., and Oli, M.K., 2017, Territory occupancy and breeding success of Peregrine Falcons Falco peregrinus at various stages of population recovery: Ibis, v. 159, no. 2, p. 285-296, https://doi.org/10.1111/ibi.12443.","productDescription":"12 p.","startPage":"285","endPage":"296","ipdsId":"IP-077722","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470018,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ibi.12443","text":"External Repository"},{"id":337439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"159","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-02","publicationStatus":"PW","scienceBaseUri":"58c7af95e4b0849ce9795e68","contributors":{"authors":[{"text":"McGrady, Michael J.","contributorId":189117,"corporation":false,"usgs":false,"family":"McGrady","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":683934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":683895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rollie, Chris","contributorId":189118,"corporation":false,"usgs":false,"family":"Rollie","given":"Chris","email":"","affiliations":[],"preferred":false,"id":683935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, George D.","contributorId":189119,"corporation":false,"usgs":false,"family":"Smith","given":"George","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":683936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morton, Elise R.","contributorId":189121,"corporation":false,"usgs":false,"family":"Morton","given":"Elise","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":683937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":683938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mearns, Richard M.","contributorId":189123,"corporation":false,"usgs":false,"family":"Mearns","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":683939,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newton, Ian","contributorId":111901,"corporation":false,"usgs":true,"family":"Newton","given":"Ian","email":"","affiliations":[],"preferred":false,"id":683903,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murillo-Garcia, Oscar E.","contributorId":189120,"corporation":false,"usgs":false,"family":"Murillo-Garcia","given":"Oscar","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683940,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Oli, Madan K.","contributorId":86089,"corporation":false,"usgs":true,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":683904,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70184964,"text":"70184964 - 2017 - Relationships between maternal engorgement weight and the number, size, and fat content of larval Ixodes scapularis (Acari: Ixodidae)","interactions":[],"lastModifiedDate":"2017-05-31T16:29:08","indexId":"70184964","displayToPublicDate":"2017-03-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between maternal engorgement weight and the number, size, and fat content of larval Ixodes scapularis (Acari: Ixodidae)","docAbstract":"The relationship between engorgement weight of female Ixodes scapularis Say and characteristics of offspring was studied using field-collected females fed on rabbits in the laboratory. The number of eggs laid was positively related to maternal engorgement weight in one trial, and larval size (estimated by scutal area) was positively related to maternal engorgement weight in the other. These results suggest a trade-off in number of eggs produced versus average size of offspring, possibly determined during late engorgement. The adults for the two trials were collected from different sites in southern Rhode Island and in different seasons (the fall adults were newly emerged, while the spring adults had presumably lived through the winter), so it is not clear whether these results reflect genetic differences or subtle environmental differences between trials. Percent egg hatch and average fat content of larvae were not related to female engorgement weight. We present a modified method to measure lipid content of pooled larval ticks.
","language":"English","publisher":"Bernice Pauahi Bishop Museum","publisherLocation":"Honolulu, HI","doi":"10.1093/jme/tjw191","usgsCitation":"Ginsberg, H., Lee, C., Volson, B., Dyer, M.C., and LeBrun, R.A., 2017, Relationships between maternal engorgement weight and the number, size, and fat content of larval Ixodes scapularis (Acari: Ixodidae): Journal of Medical Entomology, v. 54, no. 2, p. 275-280, https://doi.org/10.1093/jme/tjw191.","productDescription":"6 p.","startPage":"275","endPage":"280","ipdsId":"IP-074914","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjw191","text":"Publisher Index Page"},{"id":337414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-27","publicationStatus":"PW","scienceBaseUri":"58c7af9be4b0849ce9795e70","contributors":{"authors":[{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":683720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Chong","contributorId":189052,"corporation":false,"usgs":false,"family":"Lee","given":"Chong","email":"","affiliations":[],"preferred":false,"id":683721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Volson, Barry","contributorId":189053,"corporation":false,"usgs":false,"family":"Volson","given":"Barry","email":"","affiliations":[],"preferred":false,"id":683722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dyer, Megan C.","contributorId":178309,"corporation":false,"usgs":false,"family":"Dyer","given":"Megan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":683723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeBrun, Roger A.","contributorId":70907,"corporation":false,"usgs":false,"family":"LeBrun","given":"Roger","email":"","middleInitial":"A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":683724,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184375,"text":"ds1041 - 2017 - Coastal single-beam bathymetry data collected in 2015 from Raccoon Point to Point Au Fer Island, Louisiana","interactions":[],"lastModifiedDate":"2017-03-10T10:36:47","indexId":"ds1041","displayToPublicDate":"2017-03-10T09:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1041","title":"Coastal single-beam bathymetry data collected in 2015 from Raccoon Point to Point Au Fer Island, Louisiana","docAbstract":"As part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the south-central coast of Louisiana, from Raccoon Point to Point Au Fer Island, in July 2015. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in this report will provide baseline bathymetric information for future research investigating island evolution, sediment transport, and recent and long-term geomorphic change, and will support modeling of future changes in response to restoration and storm impacts. The survey area encompasses more than 300 square kilometers of nearshore environment from Raccoon Point to Point Au Fer Island. This data series serves as an archive of processed single-beam bathymetry data, collected from July 22–29, 2015, under USGS Field Activity Number 2015-320-FA. Geographic information system data products include a 200-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1041","usgsCitation":"Stalk, C.A., DeWitt, N.T., Kindinger, J.L., Flocks, J.G., Reynolds, B.J., Kelso, K.W., Fredericks, J.J., and Tuten, T.M., 2017, Coastal single-beam bathymetry data collected in 2015 from Raccoon Point to Point Au Fer Island, Louisiana: U.S. Geological Survey Data Series 1041, https://doi.org/10.3133/ds1041.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076353","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1041/coverthb.jpg"},{"id":337141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1041/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1041"}],"country":"United States ","state":"Louisiana","otherGeospatial":"Point Au Fer Island, Raccoon Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.0384521484375,\n 30.90693797089463\n ],\n [\n -92.0819091796875,\n 30.888083515609047\n ],\n [\n -92.1258544921875,\n 28.85429649869795\n ],\n [\n -90.0604248046875,\n 28.849485201023\n ],\n [\n -90.0384521484375,\n 30.90693797089463\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Between 1997 and 2011, Mongolia established three specially protected areas in the north-central part of the country to protect various high-value resources. These areas are jointly referred to as the Ulaan Taiga Specially Protected Areas. In accordance with the goals of the draft general management plan, this report identifies options for initiating an inventory and monitoring program for the three protected areas. Together, the three areas comprise over 1.5 million hectares of mountainous terrain west of Lake Hovsgol and bordering the Darkhad Valley. The area supports numerous rare ungulates, endangered fish, and over 40 species of threatened plants. Illegal mining, illegal logging, and poaching pose the most immediate threats to resources. As a first step, a review of published literature would inform natural resource management at the Ulaan Taiga Specially Protected Areas because it would inform other inventories.
Vegetation classification and mapping also would inform other inventory efforts because the process incorporates geographic analysis to identify environmental gradients, fine-scale sampling that captures species composition and structure, and landscape-scale results that represent the variety and extent of habitats for various organisms. Mapping using satellite imagery reduces the cost per hectare.
Following a determination of existing knowledge, field surveys of vertebrates and vascular plants would serve to build species lists and fill in gaps in existing knowledge. For abiotic resources, a focus on monitoring air quality, evaluating and monitoring water quality, and assembling and storing weather data would provide information for correlating resource response status with changing environmental conditions.
Finally, we identify datasets that, if incorporated into a geographic information system, would inform resource management. They include political boundaries, infrastructure, topography, surficial geology, hydrology, fire history, and soils.
In terms of tracking high-value resources, vegetation monitoring at the plot scale would provide a basis for detecting change in such characteristics as plant species composition, vegetation structure, and productivity that are associated with landscape-scale factors such as climate change or biotic interactions. Continued population monitoring of rare ungulates, particularly argali or wild sheep (Ovis ammon), would provide information on how populations are responding to natural and anthropogenic stressors. Siberian taimen (Hucho taimen) also is an important monitoring target given ongoing threats of poaching and climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171025","usgsCitation":"Moore, P.E., Meyer, J.B., and Chow, L.S., 2017, Natural resource inventory and monitoring for Ulaan Taiga Specially Protected Areas—An assessment of needs and opportunities in northern Mongolia: U.S. Geological Survey Open-File Report 2017–1025, 35 p., https://doi.org/10.3133/ofr20171025.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-082861","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":337345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1025/coverthb.jpg"},{"id":337346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1025/ofr20171025.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1025"}],"country":"Mongolia","otherGeospatial":"Ulaan Taiga Specially Protected Areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 97.55859375,\n 49.89463439573421\n ],\n [\n 102.48046875,\n 49.89463439573421\n ],\n [\n 102.48046875,\n 52.24125614966341\n ],\n [\n 97.55859375,\n 52.24125614966341\n ],\n [\n 97.55859375,\n 49.89463439573421\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
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Sacramento, California 95819
http://www.werc.usgs.gov/
Drylands represent the planet’s largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness—changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.
","language":"English","publisher":"Springer Nature","doi":"10.1038/srep44188","usgsCitation":"Rutherford, W.A., Painter, T.H., Ferrenberg, S., Belnap, J., Okin, G.S., Flagg, C.B., and Reed, S.C., 2017, Albedo feedbacks to future climate via climate change impacts on dryland biocrusts: Scientific Reports, v. 7, Article 44188: 9 p., https://doi.org/10.1038/srep44188.","productDescription":"Article 44188: 9 p.","ipdsId":"IP-079895","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep44188","text":"Publisher Index Page"},{"id":342637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Castle Valley","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.393889,\n 38.617778\n ],\n [\n -109.427222,\n 38.617778\n ],\n [\n -109.427222,\n 38.651111\n ],\n [\n -109.393889,\n 38.651111\n ],\n [\n -109.393889,\n 38.617778\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-10","publicationStatus":"PW","scienceBaseUri":"5948e2a6e4b062508e354c6e","contributors":{"authors":[{"text":"Rutherford, William A. wrutherford@usgs.gov","contributorId":5724,"corporation":false,"usgs":true,"family":"Rutherford","given":"William","email":"wrutherford@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":698647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Okin, Gregory S.","contributorId":50025,"corporation":false,"usgs":true,"family":"Okin","given":"Gregory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":698650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flagg, Cody B. cflagg@usgs.gov","contributorId":4573,"corporation":false,"usgs":true,"family":"Flagg","given":"Cody","email":"cflagg@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698645,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190090,"text":"70190090 - 2017 - Creating high-resolution bare-earth digital elevation models (DEMs) from stereo imagery in an area of densely vegetated deciduous forest using combinations of procedures designed for lidar point cloud filtering","interactions":[],"lastModifiedDate":"2017-08-12T08:58:08","indexId":"70190090","displayToPublicDate":"2017-03-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Creating high-resolution bare-earth digital elevation models (DEMs) from stereo imagery in an area of densely vegetated deciduous forest using combinations of procedures designed for lidar point cloud filtering","docAbstract":"For areas of the world that do not have access to lidar, fine-scale digital elevation models (DEMs) can be photogrammetrically created using globally available high-spatial resolution stereo satellite imagery. The resultant DEM is best termed a digital surface model (DSM) because it includes heights of surface features. In densely vegetated conditions, this inclusion can limit its usefulness in applications requiring a bare-earth DEM. This study explores the use of techniques designed for filtering lidar point clouds to mitigate the elevation artifacts caused by above ground features, within the context of a case study of Prince William Forest Park, Virginia, USA. The influences of land cover and leaf-on vs. leaf-off conditions are investigated, and the accuracy of the raw photogrammetric DSM extracted from leaf-on imagery was between that of a lidar bare-earth DEM and the Shuttle Radar Topography Mission DEM. Although the filtered leaf-on photogrammetric DEM retains some artifacts of the vegetation canopy and may not be useful for some applications, filtering procedures significantly improved the accuracy of the modeled terrain. The accuracy of the DSM extracted in leaf-off conditions was comparable in most areas to the lidar bare-earth DEM and filtering procedures resulted in accuracy comparable of that to the lidar DEM.
","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/15481603.2017.1295514","usgsCitation":"DeWitt, J.D., Warner, T.A., Chirico, P.G., and Bergstresser, S.E., 2017, Creating high-resolution bare-earth digital elevation models (DEMs) from stereo imagery in an area of densely vegetated deciduous forest using combinations of procedures designed for lidar point cloud filtering: GIScience and Remote Sensing, v. 54, no. 4, p. 552-572, https://doi.org/10.1080/15481603.2017.1295514.","productDescription":"21 p.","startPage":"552","endPage":"572","ipdsId":"IP-079221","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":499872,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/584b1176a9f44398859e796820e90170","text":"External Repository"},{"id":344785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-10","publicationStatus":"PW","scienceBaseUri":"59901399e4b09fa1cb178929","contributors":{"authors":[{"text":"DeWitt, Jessica D. 0000-0002-8281-8134 jdewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-8134","contributorId":5804,"corporation":false,"usgs":true,"family":"DeWitt","given":"Jessica","email":"jdewitt@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":707426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, Timothy A. 0000-0002-0414-9748","orcid":"https://orcid.org/0000-0002-0414-9748","contributorId":195554,"corporation":false,"usgs":false,"family":"Warner","given":"Timothy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":707427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chirico, Peter G. 0000-0001-8375-5342 pchirico@usgs.gov","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":195555,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"pchirico@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":707428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergstresser, Sarah E. 0000-0003-0182-5779 sbergstresser@usgs.gov","orcid":"https://orcid.org/0000-0003-0182-5779","contributorId":195556,"corporation":false,"usgs":true,"family":"Bergstresser","given":"Sarah","email":"sbergstresser@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":707429,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207982,"text":"70207982 - 2017 - Harvest dynamics and annual survival of mallards and grey ducks","interactions":[],"lastModifiedDate":"2020-01-22T15:50:21","indexId":"70207982","displayToPublicDate":"2017-03-09T15:41:34","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Harvest dynamics and annual survival of mallards and grey ducks","docAbstract":"We examined how hunter behavior, environmental covariates, and mallard (Anas platyrhynchos) and grey duck (A. superciliosa) population indices affected per capita harvest, hunter effort (i.e., hours hunted), and hunter participation (i.e., license sales) between 1997 and 2012 in the Eastern Fish and Game Region of New Zealand. Additionally, we examined how total annual hunter effort and harvest affected annual survival and harvest rates (i.e., the proportion of the population that is harvested). Per capita harvest increased with hunter effort and bag limits; hunter effort decreased over time, but effort and participation increased with mallard population size. Juvenile harvest rates were greater than for adults and negatively associated with population size. The relationship between harvest regulations and harvest rates was inconsistent. The 44‐day seasons had greater juvenile harvest rates than the 57‐ and 72‐day seasons. Similarly, years with a 7‐bag limit had higher juvenile harvest rates than years with a 10‐bag limit. Hunter effort affected annual survival rates, especially for females. Alternatively or concordantly, hunter effort may be a surrogate for population size and thus, survival rate may have been density dependent. The relationship between harvest and density‐dependent mortality may in part be augmented by hunter behavior; fewer hunters hunted for fewer hours in years with relatively few birds. Our results suggest bag limits are more effective than season length at managing harvest; reducing bag limits to <2 birds/day from ≥7 could decrease harvest by as much as 50%. Furthermore, regulation consistency, better education, and enforcement of season regulations may improve harvest management; 58% of active hunters reported they shot mallards or grey ducks after the close of the 31‐day season, which accounted for 13% of total harvest.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21213","usgsCitation":"McDougall, M.B., and Amundson, C.L., 2017, Harvest dynamics and annual survival of mallards and grey ducks: Journal of Wildlife Management, v. 81, no. 3, p. 449-460, https://doi.org/10.1002/jwmg.21213.","productDescription":"12 p.","startPage":"449","endPage":"460","ipdsId":"IP-064825","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":461699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21213","text":"Publisher Index Page"},{"id":371467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 175.5615234375,\n -39.419220736559545\n ],\n [\n 178.57177734375,\n -39.419220736559545\n ],\n [\n 178.57177734375,\n -37.5097258429375\n ],\n [\n 175.5615234375,\n -37.5097258429375\n ],\n [\n 175.5615234375,\n -39.419220736559545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McDougall, Matthew B.","contributorId":221709,"corporation":false,"usgs":false,"family":"McDougall","given":"Matthew","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":780031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":780032,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240669,"text":"70240669 - 2017 - Organic petrology of peak oil maturity Triassic Yanchang Formation lacustrine mudrocks, Ordos Basin, China","interactions":[],"lastModifiedDate":"2023-02-13T17:46:06.357077","indexId":"70240669","displayToPublicDate":"2017-03-09T11:41:10","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology of peak oil maturity Triassic Yanchang Formation lacustrine mudrocks, Ordos Basin, China","docAbstract":"An organic petrology evaluation and a determination of solid bitumen reflectance
At least one-third of all amphibian species face the threat of extinction, and current amphibian extinction rates are four orders of magnitude greater than background rates. Preventing extirpation often requires both ex situ (i.e., conservation breeding programs) and in situ strategies (i.e., protecting natural habitats). Flatwoods salamanders (Ambystoma bishopi and A. cingulatum) are protected under the U.S. Endangered Species Act. The two species have decreased from 476 historical locations to 63 recently extant locations (86.8% loss). We suggest that recovery efforts are needed to increase populations and prevent extinction, but uncertainty regarding optimal actions in both ex situ and in situ realms hinders recovery planning. We used structured decision making (SDM) to address key uncertainties regarding both captive breeding and habitat restoration, and we developed short-, medium-, and long-term goals to achieve recovery objectives. By promoting a transparent, logical approach, SDM has proven vital to recovery plan development for flatwoods salamanders. The SDM approach has clear advantages over other previous approaches to recovery efforts, and we suggest that it should be considered for other complex decisions regarding endangered species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jnc.2017.02.011","usgsCitation":"O’Donnell, K., Messerman, A.F., Barichivich, W.J., Semlitsch, R.D., Gorman, T.A., Mitchell, H.G., Allan, N., Fenolio, D.B., Green, A., Johnson, F.A., Keever, A., Mandica, M., Martin, J., Mott, J., Peacock, T., Reinman, J., Romanach, S.S., Titus, G., McGowan, C.P., and Walls, S.C., 2017, Structured decision making as a conservation tool for recovery planning of two endangered salamanders: Journal for Nature Conservation, v. 37, p. 66-72, https://doi.org/10.1016/j.jnc.2017.02.011.","productDescription":"7 p.","startPage":"66","endPage":"72","ipdsId":"IP-075815","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jnc.2017.02.011","text":"Publisher Index 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F","contributorId":187740,"corporation":false,"usgs":false,"family":"Messerman","given":"Arianne","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":681536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichivich, William J. 0000-0003-1103-6861 wbarichivich@usgs.gov","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":3697,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","email":"wbarichivich@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semlitsch, Raymond D.","contributorId":174906,"corporation":false,"usgs":false,"family":"Semlitsch","given":"Raymond","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":681538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorman, Thomas A.","contributorId":169673,"corporation":false,"usgs":false,"family":"Gorman","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":681539,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitchell, Harold G","contributorId":187741,"corporation":false,"usgs":false,"family":"Mitchell","given":"Harold","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":681540,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allan, Nathan","contributorId":187742,"corporation":false,"usgs":false,"family":"Allan","given":"Nathan","affiliations":[],"preferred":false,"id":681541,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fenolio, Dante 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and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":681553,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":681554,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70184443,"text":"ds1038 - 2017 - Groundwater-quality data in 12 GAMA study units: Results from the 2006–10 initial sampling period and the 2008–13 trend sampling period, California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2017-03-10T13:57:25","indexId":"ds1038","displayToPublicDate":"2017-03-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1038","title":"Groundwater-quality data in 12 GAMA study units: Results from the 2006–10 initial sampling period and the 2008–13 trend sampling period, California GAMA Priority Basin Project","docAbstract":"The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey in cooperation with the California State Water Resources Control Board. From 2004 through 2012, the GAMA-PBP collected samples and assessed the quality of groundwater resources that supply public drinking water in 35 study units across the State. Selected sites in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. Twelve of the study units, initially sampled during 2006–11 (initial sampling period) and sampled a second time during 2008–13 (trend sampling period) to assess temporal trends, are the subject of this report.
The initial sampling was designed to provide a spatially unbiased assessment of the quality of untreated groundwater used for public water supplies in the 12 study units. In these study units, 550 sampling sites were selected by using a spatially distributed, randomized, grid-based method to provide spatially unbiased representation of the areas assessed (grid sites, also called “status sites”). After the initial sampling period, 76 of the previously sampled status sites (approximately 10 percent in each study unit) were randomly selected for trend sampling (“trend sites”). The 12 study units sampled both during the initial sampling and during the trend sampling period were distributed among 6 hydrogeologic provinces: Coastal (Northern and Southern), Transverse Ranges and Selected Peninsular Ranges, Klamath, Modoc Plateau and Cascades, and Sierra Nevada Hydrogeologic Provinces. For the purposes of this trend report, the six hydrogeologic provinces were grouped into two hydrogeologic regions based on location: Coastal and Mountain.
The groundwater samples were analyzed for a number of synthetic organic constituents (volatile organic compounds, pesticides, and pesticide degradates), constituents of special interest (perchlorate and 1,2,3-trichloropropane), and natural inorganic constituents (nutrients, major and minor ions, and trace elements). Isotopic tracers (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. More than 200 constituents and water-quality indicators were measured during the trend sampling period.
Quality-control samples (blanks, replicates, matrix-spikes, and surrogate compounds) were collected at about one-third of the trend sites, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. On the basis of detections in laboratory and field blank samples collected by GAMA-PBP study units, including the 12 study units presented here, reporting levels for some groundwater results were adjusted in this report. Differences between replicate samples were mostly within acceptable ranges, indicating low variability in analytical results. Matrix-spike recoveries were largely within the acceptable range (70 to 130 percent).
This study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater used for drinking water typically is treated, disinfected, and blended with other waters to achieve acceptable water quality. The comparison benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency and the State of California. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.
Most organic constituents that were detected in groundwater samples from the trend sites were found at concentrations less than health-based benchmarks. One volatile organic compound—perchloroethene—was detected at a concentration greater than the health-based benchmark in samples from one trend site during the initial and trend sampling periods. Chloroform was detected in at least 10 percent of the samples at trend sites in both sampling periods. Methyl tert-butyl ether was detected in samples from more than 10 percent of the trend sites during the initial sampling period. No pesticide or pesticide degradate was detected in greater than 10 percent of the samples from trend sites or at concentrations greater than their health-based benchmarks during either sampling period. Nutrients were not detected at concentrations greater than their health-based benchmarks during either sampling period.
Most detections of major ions and trace elements in samples from trend sites were less than health-based benchmarks during both sampling periods. Arsenic and boron each were detected at concentrations greater than the health-based benchmark in samples from four trend sites during the initial and trend sampling periods. Molybdenum was detected in samples from four trend sites at concentrations greater than the health-based benchmark during both sampling periods. Samples from two of these trend sites had similar molybdenum concentrations, and two had substantially different concentrations during the initial and trend sampling periods. Uranium was detected at a concentration greater than the health-based benchmark only at two trend sites.
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\"}}]}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
The Southeast Missouri Barite District and the Valles Mines are located in Washington, Jefferson, and St. Francois Counties, Missouri, where barite and lead ore are present together in surficial and near-surface deposits. Lead mining in the area began in the early 1700’s and extended into the early 1900’s. Hand mining of lead in the residuum resulted in widespread pits (also called shafts or diggings), and there was some underground mining of lead in bedrock. By the 1860’s barite was recovered from the residuum by hand mining, also resulting in widespread diggings, but generally not underground mines in bedrock. Mechanized open-pit mining of the residuum for barite began in the 1920’s. Barite production slowed by the 1980’s, and there has not been any barite mining since 1998. Mechanized barite mining resulted in large mined areas and tailings ponds containing waste from barite mills.
The U.S. Environmental Protection Agency (EPA) has determined that lead is present in surface soils in Washington and Jefferson Counties at concentrations exceeding health-based screening levels. Also, elevated concentrations of barium, arsenic, and cadmium have been identified in surface soils, and lead concentrations exceeding the Federal drinking-water standard of 15 micrograms per liter have been identified in private drinking-water wells. Potential sources of these contaminants are wastes associated with barite mining, wastes associated with lead mining, or unmined natural deposits of barium, lead, and other metals. As a first step in helping EPA determine the source of soil and groundwater contamination, the U.S. Geological Survey (USGS), in cooperation with the EPA, investigated the geology and mining history of the Southeast Missouri Barite District and the Valles Mines.
Ore minerals are barite (barium sulfate), galena (lead sulfide), cerussite (lead carbonate), anglesite (lead sulfate), sphalerite (zinc sulfide), smithsonite (zinc carbonate), and chalcopyrite (copper-iron sulfide). The Cambrian Potosi Dolomite is the most important formation for the ore deposits, followed by the Eminence Dolomite. Because galena, sphalerite, and barite are less soluble than dolomite, chemical weathering of the ore-bearing dolomite bedrock resulted in the concentration of ore minerals in the residuum. Most of the barite and lead mining was in the residuum, which averages 10 to 15 feet thick.
Lead mining by French explorers may have begun in 1719 along Old Mines Creek at Cabanage de Renaudiere, which was followed shortly by the discovery of lead and the development of lead mines at Mine Renault (also called Forche a Renault Mine), Old Mines, and at other places along the Big River, Mineral Fork, and Forche a Renault Creek. Lead mining began sometime between 1775 and 1780 at Mine a Breton, the name of which was later changed to Potosi. Other mining areas were developed in the early part of the 19th century, including Fourche a Courtois (Palmer Mines), the French Diggings, and the Richwoods Mines. Zinc became a valuable resource after the Civil War, and the Valles Mines was an important supplier of zinc as well as lead, with at least some production up until the 1920’s. Lead mining declined in the early part of the 20th century as mining in the Old Lead Belt, Mine La Motte, and the Tri-State District expanded.
The earliest lead mines were diggings in the residuum and were round holes (shafts) about 4 feet in diameter dug with pick and shovel about 15–20 feet deep, with drifts dug a short distance laterally from the bottom of the shafts. This mining process was repeated a short distance away until a large area was covered with pits. Some mining in bedrock began by about 1800, with shafts as deep as 170 feet and as much as several hundred feet of lateral drifts.
Smelting of the lead ore to elemental lead was first done using a log furnace, which was inefficient; estimates have been made that only about 50 percent of the lead was recovered, and the remainder was lost to the ashes (slags) and to volatilization. Starting in 1798, ash furnaces were used to smelt the ashes from the log furnaces. These two furnaces were worked in tandem for many years but were gradually replaced by other furnaces, including the Scotch hearth. Estimates of lead recovery as high as 80–90 percent have been made for the Scotch hearth. By the mid-1870’s the air furnace was being used, also with estimated lead recovery as high as 80–90 percent. Zinc furnaces were built when zinc became a valuable commodity, but much of the zinc ore was shipped out of the area, either to a smelter in St. Louis, Missouri, or to other smelters.
The total lead and zinc production from the Southeast Missouri Barite District and the Valles Mines is estimated at 180,000 tons of lead and 60,000 tons of zinc. An estimated 97,000 tons of lead and an estimated 120,000 tons of zinc were lost during smelting. The estimated losses do not include losses at the mine site during mining and preparation for smelting, such as the loss of fine-grained galena during hand cleaning or the discarding of zinc ore before its value was known, for which no estimates are available.
Hand mining for barite in the residuum was active by at least the 1860’s and peaked from 1905 to the 1930’s when several thousand people were engaged in barite mining. Hand mining (diggings) and cleaning of the ore was done in much the same way as earlier lead mining, with the additional use of a rattle box to further clean the barite. Mechanized open-pit mining of old barite diggings began in 1924 to recover barite left behind by hand mining, and washing plants were used to clean the clay from the barite. Hand mining, however, continued to thrive, and washer plants began to close temporarily in 1931; nearly all of the barite produced before 1937 was by hand mining. By the 1940’s, however, all barite mining was mechanized.
Mechanized mining used shovels powered by steam, gasoline, or electricity (and by the 1950’s draglines and front-end loaders) to mine the residuum. The ore was loaded onto rail cars (and by the 1940’s, trucks) for shipment to washer plants. Clay was removed from the barite using a log washer, and a jig was used to concentrate the barite. Overflow from the log washers was waste and went to a mud (tailings) pond. The coarse jig tailings went to tailings piles or were used as railroad ballast and, later, to create roads within the mine pit. Some barite was ground, depending on its final use, and some ground barite was bleached using a hot solution of sulfuric acid to remove impurities such as iron minerals and lead sulfide (galena). An earlier bleaching process used lead-lined tanks.
Large quantities of water were required for milling the barite; some was recirculated water and the remainder came from dammed streams or was pumped from wells. Tailings and wastewater were impounded behind dikes that were built across small valleys and were increased in height as necessary using washer waste and any overburden that had been stripped. In some cases, dikes were built across valleys that had already been mined for barite.
The total production of barite from the Southeast Missouri Barite District and the Valles Mines is estimated to have been about 13.1 million tons. Most of the barite production was from Washington County. Hand mining and processing of barite was inefficient. Estimates of barite recovery range from less than one-fourth to about one-half because pillars between the shafts in the residuum needed to be left unmined for stability. With mechanized mining, large amounts of barite were lost during the milling process. It has been estimated that about 30 percent of the barite was lost and that about two-thirds of the lost barite was fine-grained and was discharged to the tailings ponds. Some galena was lost to the tailings ponds.
A 1972 inventory of tailings ponds by the Missouri Geological Survey identified 67 ponds in the Southeast Missouri Barite District (there are more than this currently documented). Results from samples from four ponds that were drilled were used to estimate that the 67 ponds contained almost 39 million tons (or cubic yards) of tailings averaging about 5 percent barite, for a potential reserve of 1.935 million tons of barite.
It is not known how much lead was removed during barite mining, either by hand or mechanized mining and processing, how much lead was recovered, or how much lead went as fines to the tailing ponds or as coarse material to mine roads or was otherwise lost.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165173","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Mugel, D.N., 2017, Geology and mining history of the Southeast Missouri Barite District and the Valles Mines, Washington, Jefferson, and St. Francois Counties, Missouri: U.S. Geological Survey Scientific Investigations Report 2016–5173, 61 p., https://doi.org/10.3133/sir20165173.","productDescription":"vi, 61 p.","numberOfPages":"72","onlineOnly":"N","ipdsId":"IP-076644","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":337151,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5173/coverthb.jpg"},{"id":337152,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5173/sir20165173.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5173"}],"country":"United States","state":"Missouri","county":"Jefferson County, St. Francois County, Washington County","otherGeospatial":"Southeast Missouri Barite District, Valles Mines","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-90.3435,38.3872],[-90.3467,38.3829],[-90.3507,38.3774],[-90.3536,38.372],[-90.3565,38.367],[-90.3566,38.362],[-90.3579,38.357],[-90.3598,38.3516],[-90.3617,38.3471],[-90.3648,38.3422],[-90.3673,38.3372],[-90.3698,38.3319],[-90.3713,38.3274],[-90.3724,38.3224],[-90.3723,38.3179],[-90.3728,38.3116],[-90.3729,38.307],[-90.3727,38.3011],[-90.3731,38.288],[-90.373,38.278],[-90.37,38.269],[-90.3682,38.2622],[-90.3663,38.255],[-90.3645,38.2486],[-90.3624,38.2424],[-90.3603,38.2356],[-90.3564,38.2264],[-90.3524,38.2197],[-90.3498,38.2141],[-90.3453,38.208],[-90.3413,38.2031],[-90.3373,38.1989],[-90.3334,38.1949],[-90.3292,38.1904],[-90.3222,38.1846],[-90.3185,38.1823],[-90.3133,38.1805],[-90.3092,38.1787],[-90.3028,38.177],[-90.297,38.1751],[-90.2904,38.1725],[-90.2839,38.1689],[-90.2792,38.1652],[-90.2745,38.1604],[-90.2709,38.1559],[-90.2673,38.1501],[-90.2634,38.1441],[-90.256,38.1333],[-90.2504,38.1255],[-90.2493,38.1239],[-90.2512,38.123],[-90.2513,38.1198],[-90.2554,38.1195],[-90.259,38.115],[-90.2633,38.1096],[-90.2674,38.1088],[-90.2756,38.1094],[-90.2785,38.109],[-90.281,38.1045],[-90.287,38.0983],[-90.2925,38.0925],[-90.2972,38.0898],[-90.303,38.0922],[-90.31,38.0946],[-90.3163,38.0974],[-90.3227,38.0975],[-90.3315,38.0995],[-90.4137,38.0447],[-90.3254,37.9861],[-90.4574,37.8823],[-90.2396,37.6998],[-90.2203,37.6854],[-90.2027,37.6701],[-90.1535,37.7004],[-90.1114,37.6715],[-90.1489,37.6423],[-90.2204,37.6423],[-90.5349,37.6441],[-90.5907,37.6441],[-90.6483,37.6437],[-90.6454,37.7365],[-90.7687,37.7393],[-90.8159,37.7381],[-90.8747,37.7362],[-90.874,37.7403],[-90.8892,37.7378],[-90.8921,37.7369],[-91.1004,37.7431],[-91.0925,38.005],[-91.0963,38.2072],[-90.999,38.2079],[-90.9702,38.2111],[-90.9703,38.2084],[-90.7788,38.2077],[-90.7386,38.4184],[-90.7358,38.4832],[-90.7282,38.4821],[-90.7194,38.4811],[-90.7165,38.4802],[-90.7172,38.4734],[-90.7161,38.4729],[-90.7125,38.4733],[-90.7096,38.4751],[-90.7037,38.4763],[-90.6967,38.474],[-90.6898,38.4653],[-90.6875,38.4625],[-90.6888,38.4585],[-90.69,38.4567],[-90.6889,38.4557],[-90.6818,38.4574],[-90.68,38.4565],[-90.683,38.4543],[-90.6837,38.4511],[-90.6802,38.4497],[-90.6743,38.4505],[-90.6589,38.4571],[-90.6547,38.4598],[-90.6546,38.4638],[-90.6574,38.4698],[-90.6596,38.4734],[-90.6594,38.4811],[-90.6569,38.4883],[-90.6516,38.4905],[-90.6456,38.4927],[-90.6398,38.4922],[-90.6328,38.4884],[-90.6282,38.4847],[-90.623,38.481],[-90.6189,38.4787],[-90.6143,38.4773],[-90.6084,38.4785],[-90.6041,38.4839],[-90.5998,38.4902],[-90.5967,38.4951],[-90.5918,38.5032],[-90.5906,38.5064],[-90.4089,38.5039],[-90.406,38.5016],[-90.4061,38.4984],[-90.4079,38.4962],[-90.4075,38.4912],[-90.4052,38.4884],[-90.4083,38.4839],[-90.4119,38.4822],[-90.4125,38.4822],[-90.4137,38.4813],[-90.4154,38.4818],[-90.4201,38.4837],[-90.4218,38.4832],[-90.4224,38.4833],[-90.4224,38.4824],[-90.4214,38.4774],[-90.4215,38.4751],[-90.4159,38.4627],[-90.4102,38.4581],[-90.4067,38.4567],[-90.4026,38.4571],[-90.399,38.4593],[-90.3954,38.461],[-90.3919,38.4601],[-90.3903,38.4569],[-90.3868,38.455],[-90.3773,38.4562],[-90.3602,38.46],[-90.356,38.4617],[-90.3466,38.4616],[-90.3443,38.4606],[-90.3402,38.4592],[-90.3368,38.456],[-90.3375,38.4496],[-90.3442,38.4434],[-90.3474,38.4348],[-90.3473,38.4194],[-90.3467,38.4167],[-90.3488,38.4072],[-90.345,38.3972],[-90.3451,38.3935],[-90.3435,38.3872]]]},\"properties\":{\"name\":\"Jefferson\",\"state\":\"MO\"}}]}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
This paper presents a conceptual framework to operationalize flow–ecology relationships into decision-support systems of practical use to water-resource managers, who are commonly tasked with balancing multiple competing socioeconomic and environmental priorities. We illustrate this framework with a case study, whereby fish community responses to various water-management scenarios were predicted in a partially regulated river system at a local watershed scale. This case study simulates management scenarios based on interactive effects of dam operation protocols, withdrawals for municipal water supply, effluent discharges from wastewater treatment, and inter-basin water transfers. Modeled streamflow was integrated with flow–ecology relationships relating hydrologic departure from reference conditions to fish species richness, stratified by trophic, reproductive, and habitat characteristics. Adding a hypothetical new water-withdrawal site was predicted to increase the frequency of low-flow conditions with adverse effects for several fish groups. Imposition of new reservoir release requirements was predicted to enhance flow and fish species richness immediately downstream of the reservoir, but these effects were dissipated further downstream. The framework presented here can be used to translate flow–ecology relationships into evidence-based management by developing decision-support systems for conservation of riverine biodiversity while optimizing water availability for human use.
","language":"English","publisher":"MDPI","doi":"10.3390/w9030196","usgsCitation":"Cartwright, J.M., Caldwell, C., Nebiker, S., and Knight, R., 2017, Putting flow-ecology relationships into practice: A decision-support system to assess fish community response to water-management scenarios: Water, v. 9, no. 3, p. 1-18, https://doi.org/10.3390/w9030196.","productDescription":"Article 196; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-076084","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":470021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9030196","text":"Publisher Index Page"},{"id":337171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-08","publicationStatus":"PW","scienceBaseUri":"58c277d5e4b014cc3a3e76a9","contributors":{"authors":[{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Casey","contributorId":187734,"corporation":false,"usgs":false,"family":"Caldwell","given":"Casey","email":"","affiliations":[],"preferred":false,"id":681523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nebiker, Steven","contributorId":187735,"corporation":false,"usgs":false,"family":"Nebiker","given":"Steven","email":"","affiliations":[],"preferred":false,"id":681524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681525,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184315,"text":"ds1037 - 2017 - Sediment data collected in 2014 and 2015 from around Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana","interactions":[],"lastModifiedDate":"2017-03-13T09:54:04","indexId":"ds1037","displayToPublicDate":"2017-03-08T11:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1037","title":"Sediment data collected in 2014 and 2015 from around Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana","docAbstract":"Breton Island, located at the southern end of the Chandeleur Islands, supports one of Louisiana’s largest historical brown pelican (Pelecanus occidentalis) nesting colonies. Although the brown pelican was delisted as an endangered species in 2009, nesting areas are threatened by continued land loss and are extremely vulnerable to storm impacts. The U.S. Fish and Wildlife Service proposed to restore Breton Island to pre-Hurricane Katrina conditions through rebuilding the shoreface, dune, and back-barrier marsh environments. Prior to restoration, scientists from the U.S. Geological Survey’s (USGS) St. Petersburg Coastal and Marine Science Center Geologic and Morphologic Evolution of Coastal Margins project collected high-resolution geophysical (topography, bathymetry, and sub-bottom profiles) and sedimentologic data from around Breton Island to characterize the geologic framework of the island platform, nearshore, and shelf environments. These data will be used to characterize the geologic framework around Breton Island, identify potential borrow areas for restoration efforts, quantify seafloor change, and provide information for sediment transport and morphologic change models to assess island response to restoration and natural processes.
This report, along with the accompanying USGS data release, serves as an archive of sediment data from vibracores, push cores, and submerged grab samples collected from around Breton and Gosier Islands, Louisiana, during two surveys conducted in July 2014 and January 2015 (USGS Field Activity Numbers 2014–314–FA and 2014–336–FA, respectively). Sedimentologic and stratigraphic metrics (for example, sediment texture or unit thicknesses) derived from these data can be used to ground-truth the geophysical data and characterize potential sand resources or can be incorporated into sediment transport or morphologic change models. Data products, including sample location tables, descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, and geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the accompanying data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1037","usgsCitation":"Bernier, J.C., Kelso, K.W., Tuten, T.M., Stalk, C.A., and Flocks, J.G., 2017, Sediment data collected in 2014 and 2015 from around Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana: U.S. Geological Survey Data Series 1037, https://doi.org/10.3133/ds1037.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081095","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":336951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1037/coverthb.jpg"},{"id":336945,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1037","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1037"},{"id":336959,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79C6VKF","text":"USGS data release ","linkHelpText":"Archive of Sediment Data Collected in 2014 and 2015 From Around Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Islands, Breton National Wildlife Refuge, Gosier Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.241943359375,\n 29.450360671054415\n ],\n [\n -88.97140502929688,\n 29.450360671054415\n ],\n [\n -88.97140502929688,\n 29.60987920220905\n ],\n [\n -89.241943359375,\n 29.60987920220905\n ],\n [\n -89.241943359375,\n 29.450360671054415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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This scientific investigations map is a product of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project modeling and mapping team. The prediction grids depicted in this map are of continuous pH and are intended to provide an understanding of groundwater-quality conditions at the domestic and public supply drinking water zones in the groundwater of the Central Valley of California. The chemical quality of groundwater and the fate of many contaminants is often influenced by pH in all aquifers. These grids are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to pH. In this work, the median well depth categorized as domestic supply was 30 meters below land surface, and the median well depth categorized as public supply is 100 meters below land surface. Prediction grids were created using prediction modeling methods, specifically boosted regression trees (BRT) with a Gaussian error distribution within a statistical learning framework within the computing framework of R (http://www.r-project.org/). The statistical learning framework seeks to maximize the predictive performance of machine learning methods through model tuning by cross validation. The response variable was measured pH from 1,337 wells and was compiled from two sources: USGS National Water Information System (NWIS) database (all data are publicly available from the USGS: http://waterdata.usgs.gov/ca/nwis/nwis) and the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW) database (water quality data are publicly available from the SWRCB: http://www.waterboards.ca.gov/gama/geotracker_gama.shtml). Only wells with measured pH and well depth data were selected, and for wells with multiple records, only the most recent sample in the period 1993–2014 was used. A total of 1,003 wells (training dataset) were used to train the BRT model, and 334 wells (hold-out dataset) were used to validate the prediction model. The training r-squared was 0.70, and the root-mean-square error (RMSE) in standard pH units was 0.26. The hold-out r-squared was 0.43, and RMSE in standard pH units was 0.37. Predictor variables consisting of more than 60 variables from 7 sources were assembled to develop a model that incorporates regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrology. Previously developed Central Valley model outputs of textures (Central Valley Textural Model, CVTM; Faunt and others, 2010) and MODFLOW-simulated vertical water fluxes and predicted depth to water table (Central Valley Hydrologic Model, CVHM; Faunt, 2009) were used to represent aquifer textures and groundwater hydraulics, respectively. In this work, wells were attributed to predictor variable values in ArcGIS using a 500-meter buffer.
Faunt, C.C., ed., 2009, Groundwater availability in the Central Valley aquifer, California: U.S. Geological Survey Professional Paper 1776, 225 p., accessed at https://pubs.usgs.gov/pp/1766/.
Faunt, C.C., Belitz, K., and Hanson, R.T., 2010, Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA: Hydrogeology Journal, v. 18, no. 3, p. 625–649, https://doi.org/10.1007/s10040-009-0539-7.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3377","usgsCitation":"Rosecrans, C.Z., Nolan, B.T., Gronberg, J.M., 2017, Predicted pH at the domestic and public supply drinking water depths, Central Valley, California: U.S. Geological Survey Scientific Investigations Map 3377, 1 sheet, scale 1:2,400,000, https://doi.org/10.3133/sim3377.","productDescription":"Sheet: 19.00 x 21.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-079912","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":336887,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77K4","text":"USGS data release","description":"USGS data release","linkHelpText":"Ascii grids of predicted pH in depth zones used by domestic and public drinking water supply depths, Central Valley, California."},{"id":336878,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3377/coverthb.jpg"},{"id":336879,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3377/sim3377.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3377"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.22290039062499,\n 40.75557964275589\n ],\n [\n -122.958984375,\n 40.38839687388361\n ],\n [\n -122.574462890625,\n 39.32579941789298\n ],\n [\n -122.08007812499999,\n 38.07404145941957\n ],\n [\n -120.7177734375,\n 36.77409249464195\n ],\n [\n -119.83886718750001,\n 35.33529320309328\n ],\n [\n -119.267578125,\n 34.912962495216966\n ],\n [\n -118.740234375,\n 35.110921809704756\n ],\n [\n -118.740234375,\n 35.8356283888737\n ],\n [\n -118.91601562499999,\n 36.359374956015856\n ],\n [\n -119.84985351562499,\n 37.32648861334206\n ],\n [\n -120.82763671875,\n 38.24680876017446\n ],\n [\n -121.39892578125,\n 39.2492708462234\n ],\n [\n -122.1240234375,\n 40.53050177574321\n ],\n [\n -122.22290039062499,\n 40.75557964275589\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
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The Lower Colorado River provides critical riparian areas in an otherwise arid region and is an important stopover site for migrating landbirds. In order to reverse ongoing habitat degradation due to drought and human-altered hydrology, a pulse flow was released from Morelos Dam in spring of 2014, which brought surface flow to dry stretches of the Colorado River in Mexico. To assess the potential effects of habitat modification resulting from the pulse flow, we used foraging behavior of spring migrants from past and current studies to assess the relative importance of different riparian habitats. We observed foraging birds in 2000 and 2014 at five riparian sites along the Lower Colorado River in Mexico to quantify prey attack rates, prey attack maneuvers, vegetation use patterns, and degree of preference for fully leafed-out or flowering plants. Prey attack rate was highest in mesquite (Prosopis spp.) in 2000 and in willow (Salix gooddingii) in 2014; correspondingly, migrants predominantly used mesquite in 2000 and willow in 2014 and showed a preference for willows in flower or fruit in 2014. Wilson’s warbler (Cardellina pusilla) used relatively more low-energy foraging maneuvers in willow than in tamarisk (Tamarix spp.) or mesquite. Those patterns in foraging behavior suggest native riparian vegetation, and especially willow, are important resources for spring migrants along the lower Colorado River. Willow is a relatively short-lived tree dependent on spring floods for dispersal and establishment and thus spring migrants are likely to benefit from controlled pulse flows.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2016.06.001","usgsCitation":"Darrah, A., Greeney, H.F., and van Riper, C., 2017, Importance of the 2014 Colorado River Delta pulse flow for migratory songbirds: Insights from foraging behavior: Ecological Engineering, v. 106, no. B, p. 784-790, https://doi.org/10.1016/j.ecoleng.2016.06.001.","productDescription":"7 p.","startPage":"784","endPage":"790","ipdsId":"IP-071691","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470022,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2016.06.001","text":"Publisher Index Page"},{"id":337066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.1202392578125,\n 31.765537409484374\n ],\n [\n -113.70849609375,\n 31.765537409484374\n ],\n [\n -113.70849609375,\n 32.78265637602964\n ],\n [\n -115.1202392578125,\n 32.78265637602964\n ],\n [\n -115.1202392578125,\n 31.765537409484374\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c12633e4b014cc3a3d344c","contributors":{"authors":[{"text":"Darrah, Abigail J.","contributorId":187674,"corporation":false,"usgs":false,"family":"Darrah","given":"Abigail J.","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false},{"id":35720,"text":"Audubon Mississippi, Coastal Bird Stewardship ProgramMoss PointUSA","active":true,"usgs":false}],"preferred":false,"id":681275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Greeney, Harold F.","contributorId":187675,"corporation":false,"usgs":false,"family":"Greeney","given":"Harold","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":681276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":681274,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184362,"text":"70184362 - 2017 - Restoration versus invasive species: Bigheaded carps’ use of a rehabilitated backwater","interactions":[],"lastModifiedDate":"2017-06-07T10:29:07","indexId":"70184362","displayToPublicDate":"2017-03-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Restoration versus invasive species: Bigheaded carps’ use of a rehabilitated backwater","docAbstract":"Knowledge of how invasive species use invaded habitats can aid in developing management practices to exclude them. Swan Lake, a 1100-ha Illinois River (USA) backwater, was rehabilitated to restore ecosystem functions, but may provide valuable habitat for invasive bigheaded carps [bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix)]. Use (residency and passages) of Swan Lake by invasive bigheaded carps was monitored using acoustic telemetry (n = 50 individuals/species) to evaluate the use of a large, restored habitat from 2004 to 2005. Passages (entrances/exits) by bigheaded carps were highest in winter, and residency was highest in the summer. Bighead carp backwater use was associated with the differences in temperature between the main channel and backwater, and passages primarily occurred between 18:00 h and midnight. Silver carp backwater use was positively correlated with water level and main channel discharge, and fewer passages occurred between 12:00 h and 18:00 h than during any other time of day. Harvest occurring during summer or high main channel discharge could reduce backwater abundances while maintenance of low water levels could reduce overall backwater use. Conclusions from this study regarding the timing of bigheaded carps' use of backwater habitats are critical to integrated pest management plans to control invasive species.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3122","usgsCitation":"Coulter, A.A., Schultz, D., Tristano, E., Brey, M.K., and Garvey, J.E., 2017, Restoration versus invasive species: Bigheaded carps’ use of a rehabilitated backwater: River Research and Applications, v. 33, no. 5, p. 662-669, https://doi.org/10.1002/rra.3122.","productDescription":"8 p.","startPage":"662","endPage":"669","ipdsId":"IP-072124","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":438423,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J1S","text":"USGS data release","linkHelpText":"Remotely sensed variables analyzed and reported in the paper titled &amp;amp;amp;quot;Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate&amp;amp;amp;rsquo;s effects on wetland surface water, amphibians, and landscape conditions&amp;amp;amp;quot;"},{"id":438422,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1VDT","text":"USGS data release","linkHelpText":"Restoration versus invasive species: bigheaded carps use of a rehabilitated backwater: Data"},{"id":337010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-24","publicationStatus":"PW","scienceBaseUri":"58c12634e4b014cc3a3d3450","contributors":{"authors":[{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":681168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, Douglas","contributorId":187653,"corporation":false,"usgs":false,"family":"Schultz","given":"Douglas","affiliations":[],"preferred":false,"id":681169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tristano, Elizabeth","contributorId":187654,"corporation":false,"usgs":false,"family":"Tristano","given":"Elizabeth","affiliations":[],"preferred":false,"id":681170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":681171,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184365,"text":"70184365 - 2017 - Effects of carbon dioxide on juveniles of the freshwater mussel (Lampsilis siliquoidea [Unionidae])","interactions":[],"lastModifiedDate":"2017-03-08T12:23:32","indexId":"70184365","displayToPublicDate":"2017-03-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effects of carbon dioxide on juveniles of the freshwater mussel (Lampsilis siliquoidea [Unionidae])","docAbstract":"Carbon dioxide (CO2) has shown promise as a tool to control movements of invasive Asian carp, but its effects on native freshwater biota have not been well studied. The authors evaluated lethal and sublethal responses of juvenile fatmucket (Lampsilis siliquoidea) mussels to CO2 at levels (43–269 mg/L, mean concentration) that bracket concentrations effective for deterring carp movement. The 28-d lethal concentration to 50% of the mussels was 87.0 mg/L (95% confidence interval [CI] 78.4–95.9) and at 16-d postexposure, 76.0 mg/L (95% CI 62.9–90.3). A proportional hazards regression model predicted that juveniles could not survive CO2 concentrations >160 mg/L for more than 2 wk or >100 mg/L CO2 for more than 30 d. Mean shell growth was significantly lower for mussels that survived CO2 treatments. Growth during the postexposure period did not differ among treatments, indicating recovery of the mussels. Also, CO2 caused shell pitting and erosion. Behavioral effects of CO2 included movement of mussels to the substrate surface and narcotization at the highest concentrations. Mussels in the 110 mg/L mean CO2treatment had the most movements in the first 3 d of exposure. If CO2 is infused continuously as a fish deterrent, concentrations <76 mg/L are recommended to prevent juvenile mussel mortality and shell damage. Mussels may survive and recover from brief exposure to higher concentrations.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.3567","usgsCitation":"Waller, D.L., Bartsch, M.R., Fredricks, K.T., Bartsch, L., Schleis, S.M., and Lee, S., 2017, Effects of carbon dioxide on juveniles of the freshwater mussel (Lampsilis siliquoidea [Unionidae]): Environmental Toxicology and Chemistry, v. 36, no. 3, p. 671-681, https://doi.org/10.1002/etc.3567.","productDescription":"11 p.","startPage":"671","endPage":"681","ipdsId":"IP-074542","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":337067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-28","publicationStatus":"PW","scienceBaseUri":"58c12634e4b014cc3a3d344e","contributors":{"authors":[{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartsch, Michelle R. 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":149359,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":173994,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim","email":"kfredricks@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartsch, Lynn A. 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":149360,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn A.","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681185,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schleis, Susan M. 0000-0002-9396-7856 sschleis@usgs.gov","orcid":"https://orcid.org/0000-0002-9396-7856","contributorId":2858,"corporation":false,"usgs":true,"family":"Schleis","given":"Susan","email":"sschleis@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":681186,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Sheldon","contributorId":173995,"corporation":false,"usgs":false,"family":"Lee","given":"Sheldon","email":"","affiliations":[{"id":25359,"text":"Viterbo University","active":true,"usgs":false}],"preferred":false,"id":681187,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}