The Department of the Interior (DOI) is a Federal agency with over 90,000 employees across 10 bureaus and 8 agency offices. Its primary mission is to protect and manage the Nation’s natural resources and cultural heritage; provide scientific and other information about those resources; and honor its trust responsibilities or special commitments to American Indians, Alaska Natives, and affiliated island communities. Data and information are critical in day-to-day operational decision making and scientific research. DOI is committed to creating, documenting, managing, and sharing high-quality data and metadata in and across its various programs that support its mission. Documenting data through metadata is essential in realizing the value of data as an enterprise asset. The completeness, consistency, and timeliness of metadata affect users’ ability to search for and discover the most relevant data for the intended purpose; and facilitates the interoperability and usability of these data among DOI bureaus and offices. Fully documented metadata describe data usability, quality, accuracy, provenance, and meaning.
Across DOI, there are different maturity levels and phases of information and metadata management implementations. The Department has organized a committee consisting of bureau-level points-of-contacts to collaborate on the development of more consistent, standardized, and more effective metadata management practices and guidance to support this shared mission and the information needs of the Department. DOI’s metadata implementation plans establish key roles and responsibilities associated with metadata management processes, procedures, and a series of actions defined in three major metadata implementation phases including: (1) Getting started—Planning Phase, (2) Implementing and Maintaining Operational Metadata Management Phase, and (3) the Next Steps towards Improving Metadata Management Phase. DOI’s phased approach for metadata management addresses some of the major data and metadata management challenges that exist across the diverse missions of the bureaus and offices. All employees who create, modify, or use data are involved with data and metadata management. Identifying, establishing, and formalizing the roles and responsibilities associated with metadata management are key to institutionalizing a framework of best practices, methodologies, processes, and common approaches throughout all levels of the organization; these are the foundation for effective data resource management. For executives and managers, metadata management strengthens their overarching views of data assets, holdings, and data interoperability; and clarifies how metadata management can help accelerate the compliance of multiple policy mandates. For employees, data stewards, and data professionals, formalized metadata management will help with the consistency of definitions, and approaches addressing data discoverability, data quality, and data lineage. In addition to data professionals and others associated with information technology; data stewards and program subject matter experts take on important metadata management roles and responsibilities as data flow through their respective business and science-related workflows. The responsibilities of establishing, practicing, and governing the actions associated with their specific metadata management roles are critical to successful metadata implementation.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Metadata in Book 16: Data resource management","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm16A1","collaboration":"Prepared in collaboration with Department of the Interior Data Resource Management in Support of the Department of the Interior Metadata Approach","usgsCitation":"Obuch, R.C., Carlino, Jennifer, Zhang, Lin, Blythe, Jonathan, Dietrich, Chris, Hawkinson, Christine, 2018, Department of the Interior metadata implementation guide—Framework for developing the metadata component for data resource management: U.S. Geological Survey Techniques and Methods, book 16, chap. A1, 14 p., https://doi.org/10.3133/tm16A1.","productDescription":"vi, 14 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-087710","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":353340,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/16/a1/tm16a1.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 16-A1"},{"id":353339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/16/a1/coverthb.jpg"}],"publicComments":"This report is Chapter 1 of Section A: Metadata in Book 16: Data resource management.","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2018.03.019","usgsCitation":"Byrd, K.B., Ballanti, L., Thomas, N., Nguyen, D., Holmquist, J.R., Simard, M., and Windham-Myers, L., 2018, A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States: ISPRS Journal of Photogrammetry and Remote Sensing, v. 139, p. 255-271, https://doi.org/10.1016/j.isprsjprs.2018.03.019.","productDescription":"17 p.","startPage":"255","endPage":"271","ipdsId":"IP-091200","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468833,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.isprsjprs.2018.03.019","text":"Publisher Index Page"},{"id":437949,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90PG34S","text":"USGS data release","linkHelpText":"Tidal marsh biomass field plot and remote sensing datasets for six regions in the conterminous United States (ver. 2.0, June 2020)"},{"id":353396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e3e4b0da30c1bfbed8","contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":733142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballanti, Laurel 0000-0002-6478-8322 lballanti@usgs.gov","orcid":"https://orcid.org/0000-0002-6478-8322","contributorId":198603,"corporation":false,"usgs":true,"family":"Ballanti","given":"Laurel","email":"lballanti@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":733143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Nathan","contributorId":204124,"corporation":false,"usgs":false,"family":"Thomas","given":"Nathan","affiliations":[{"id":33580,"text":"NASA-JPL","active":true,"usgs":false}],"preferred":false,"id":733144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nguyen, Dung","contributorId":204125,"corporation":false,"usgs":false,"family":"Nguyen","given":"Dung","email":"","affiliations":[],"preferred":false,"id":733145,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holmquist, James R.","contributorId":173462,"corporation":false,"usgs":false,"family":"Holmquist","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733146,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simard, Marc","contributorId":19036,"corporation":false,"usgs":true,"family":"Simard","given":"Marc","email":"","affiliations":[],"preferred":false,"id":733147,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733148,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196476,"text":"70196476 - 2018 - In situ LA-ICPMS U–Pb dating of cassiterite without a known-age matrix-matched reference material: Examples from worldwide tin deposits spanning the Proterozoic to the Tertiary","interactions":[],"lastModifiedDate":"2018-04-11T14:41:38","indexId":"70196476","displayToPublicDate":"2018-04-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"In situ LA-ICPMS U–Pb dating of cassiterite without a known-age matrix-matched reference material: Examples from worldwide tin deposits spanning the Proterozoic to the Tertiary","docAbstract":"Cassiterite (SnO2), a main ore mineral in tin deposits, is suitable for U–Pb isotopic dating because of its relatively high U/Pb ratios and typically low common Pb. We report a LA-ICPMS analytical procedure for U–Pb dating of this mineral with no need for an independently dated matrix-matched cassiterite standard. LA-ICPMS U-Th-Pb data were acquired while using NIST 612 glass as a primary non-matrix-matched standard. Raw data are reduced using a combination of Iolite™ and other off-line data reduction methods. Cassiterite is extremely difficult to digest, so traditional approaches in LA-ICPMS U-Pb geochronology that utilize well-characterized matrix-matched reference materials (e.g., age values determined by ID-TIMS) cannot be easily implemented. We propose a new approach for in situ LA-ICPMS dating of cassiterite, which benefits from the unique chemistry of cassiterite with extremely low Th concentrations (Th/U ratio of 10−4 or lower) in some cassiterite samples. Accordingly, it is assumed that 208Pb measured in cassiterite is mostly of non-radiogenic origin—it was initially incorporated in cassiterite during mineral formation, and can be used as a proxy for common Pb. Using 208Pb as a common Pb proxy instead of 204Pb is preferred as 204Pb is much less abundant and is also compromised by 204Hg interference during the LA-ICPMS analyses.
Our procedure relies on 208Pb/206Pb vs 207Pb/206Pb (Pb-Pb) and Tera-Wasserburg 207Pb/206Pb vs 238U/206Pb (U-Pb) isochron dates that are calculated for a ~1.54 Ga low-Th cassiterite reference material with varying amounts of common Pb that we assume remained a closed U-Pb system. The difference between the NIST 612 glass normalized biased U-Pb date and the Pb-Pb age of the reference material is used to calculate a correction factor (F) for instrumental U-Pb fractionation. The correction factor (F) is then applied to measured U/Pb ratios and Tera-Wasserburg isochron dates are obtained for the unknown cassiterite analyzed in the same analytical session. This allows for U-Pb dating of cassiterite of any age with no need for an independently dated matrix-matched reference material, nor assumptions about the isotopic composition of common Pb.
Results for cassiterite from tin deposits in Bolivia, Brazil, China, Russia, Saudi Arabia, South Africa, Spain, and the United Kingdom, with ages ranging from ~20 Ma to ~2060 Ma, demonstrate the applicability of this approach across a broad range of geologic time. These ages are in good agreement with published geochronology of the host rocks associated with the tin deposits and with previously published U-Pb ages of some cassiterites from the same deposits. Thus, our in situ LA-ICPMS methodology verifies the use of cassiterite as a reliable U-Pb mineral-geochronometer with the advantages of fast and relatively low cost in situ analyses with moderate spatial resolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2018.03.008","usgsCitation":"Neymark, L., Holm-Denoma, C.S., and Moscati, R.J., 2018, In situ LA-ICPMS U–Pb dating of cassiterite without a known-age matrix-matched reference material: Examples from worldwide tin deposits spanning the Proterozoic to the Tertiary: Chemical Geology, v. 483, p. 410-425, https://doi.org/10.1016/j.chemgeo.2018.03.008.","productDescription":"16 p.","startPage":"410","endPage":"425","ipdsId":"IP-092649","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":460955,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2018.03.008","text":"Publisher Index Page"},{"id":437952,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BP021W","text":"USGS data release","linkHelpText":"U-Pb data for: In situ LA-ICPMS U-Pb dating of cassiterite without a known-age matrix-matched reference material: Examples from worldwide tin deposits spanning the Proterozoic to Tertiary"},{"id":353333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"483","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e4e4b0da30c1bfbee4","contributors":{"authors":[{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":733136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":733137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":733138,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196493,"text":"70196493 - 2018 - Modeled de facto reuse and contaminants of emerging concern in drinking water source waters","interactions":[],"lastModifiedDate":"2018-04-11T14:04:10","indexId":"70196493","displayToPublicDate":"2018-04-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2136,"text":"Journal - American Water Works Association","active":true,"publicationSubtype":{"id":10}},"title":"Modeled de facto reuse and contaminants of emerging concern in drinking water source waters","docAbstract":"De facto reuse is the percentage of drinking water treatment plant (DWTP) intake potentially composed of effluent discharged from upstream wastewater treatment plants (WWTPs). Results from grab samples and a De Facto Reuse in our Nation's Consumable Supply (DRINCS) geospatial watershed model were used to quantify contaminants of emerging concern (CECs) concentrations at DWTP intakes to qualitatively compare exposure risks obtained by the two approaches. Between nine and 71 CECs were detected in grab samples. The number of upstream WWTP discharges ranged from 0 to >1,000; comparative de facto reuse results from DRINCS ranged from <0.1 to 13% during average flow and >80% during lower streamflows. Correlation between chemicals detected and DRINCS modeling results were observed, particularly DWTPs withdrawing from midsize water bodies. This comparison advances the utility of DRINCS to identify locations of DWTPs for future CEC sampling and treatment technology testing.
","language":"English","publisher":"Wiley","doi":"10.1002/awwa.1052","usgsCitation":"Nguyen, T., Westerhoff, P., Furlong, E., Kolpin, D., Batt, A.L., Mash, H.E., Schenck, K.M., Boone, J.S., Rice, J., and Glassmeyer, S.T., 2018, Modeled de facto reuse and contaminants of emerging concern in drinking water source waters: Journal - American Water Works Association, v. 110, no. 4, p. E2-E18, https://doi.org/10.1002/awwa.1052.","productDescription":"17 p.","startPage":"E2","endPage":"E18","ipdsId":"IP-091952","costCenters":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":468835,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10054860","text":"External Repository"},{"id":353326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-09","publicationStatus":"PW","scienceBaseUri":"5afee6e3e4b0da30c1bfbedc","contributors":{"authors":[{"text":"Nguyen, Thuy","contributorId":204152,"corporation":false,"usgs":false,"family":"Nguyen","given":"Thuy","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":733221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westerhoff, Paul","contributorId":204153,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Paul","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":733222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Edward T. 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":204151,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":733220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batt, Angela L.","contributorId":184134,"corporation":false,"usgs":false,"family":"Batt","given":"Angela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":733224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mash, Heath E.","contributorId":184073,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":733225,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schenck, Kathleen M.","contributorId":184136,"corporation":false,"usgs":false,"family":"Schenck","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":733226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boone, J. Scott","contributorId":178697,"corporation":false,"usgs":false,"family":"Boone","given":"J.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":733227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rice, Jacelyn","contributorId":204155,"corporation":false,"usgs":false,"family":"Rice","given":"Jacelyn","email":"","affiliations":[{"id":36866,"text":"University of North Carolina Charlotte","active":true,"usgs":false}],"preferred":false,"id":733228,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":733229,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70196458,"text":"ofr20181052 - 2018 - Faunal and vegetation monitoring in response to harbor dredging in the Port of Miami","interactions":[],"lastModifiedDate":"2018-04-12T09:54:46","indexId":"ofr20181052","displayToPublicDate":"2018-04-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1052","title":"Faunal and vegetation monitoring in response to harbor dredging in the Port of Miami","docAbstract":"Seagrasses are highly productive ecosystems. A before-after-control-impact (BACI) design was used to examine effects of dredging on seagrasses and the animals that inhabit them. The control site North Biscayne Bay and the affected site Port of Miami had seagrass densities decrease during both the before, Fish and Invertebrate Assessment Network 2006-2011, and after, Faunal Monitoring in Response to Harbor Dredging 2014-2016, studies. Turbidity levels increased at North Biscayne Bay and Port of Miami basins during the Faunal Monitoring in Response to Harbor Dredging study, especially in 2016. Animal populations decreased significantly in North Biscayne Bay and Port of Miami in the Faunal Monitoring in Response to Harbor Dredging study compared to the Fish and Invertebrate Assessment Network study. Predictive modeling shows that numbers of animal populations will likely continue to decrease if the negative trends in seagrass densities continue unabated. There could be effects on several fisheries vital to the south Florida economy. Additional research could determine if animal populations and seagrass densities have rebounded or continued to decrease.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181052","usgsCitation":"Daniels, A., Stevenson, R., Smith, E., and Robblee, M., 2018, Faunal and vegetation monitoring in response to harbor dredging in the Port of Miami: U.S. Geological Survey Open-File Report 2018–1052, 38 p., https://doi.org/10.3133/ofr20181052.","productDescription":"Report: viii, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084431","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":353291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1052/ofr20181052.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1052"},{"id":353292,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3KD9","text":"USGS data release","description":"USGS Data Release ","linkHelpText":"Faunal and vegetation monitoring in response to harbor dredging in Port of Miami"},{"id":353290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1052/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"North Biscayne Bay, Port of Miami","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.20774841308594,\n 25.723209559418265\n ],\n [\n -80.11505126953125,\n 25.723209559418265\n ],\n [\n -80.11505126953125,\n 25.9117325831107\n ],\n [\n -80.20774841308594,\n 25.9117325831107\n ],\n [\n -80.20774841308594,\n 25.723209559418265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71 Street
Gainesville, FL 32653
Chaparral diversity has marked spatial and temporal variation. Evolutionary diversity at the genetic, specific, and lineage level contribute to a very diverse flora. Ecological diversity is evident in life histories that comprise a range of physiological and morphological strategies for dealing with drought, and demographic patterns centered around different seedling recruitment strategies. Community or alpha diversity varies markedly through time. Mature chaparral ranges from monotypic stands of chamise (Adenostoma fasciculatum) to mixed chaparral often with up to a dozen shrub species. The understory contributes relatively little other than a few diminutive annuals and occasional herbaceous perennial resprouts. However, after fire, diversity increases dramatically and is often dominated by annuals that arise from a dormant seedbank with significant contribution of geophytes resprouting and flowering from dormant bulbs and corms. This flora has very diverse life histories, with some present only a year or two and then existing as a dormant seedbank or bulbs until the next fire. Others may persist much longer, often in gaps in the shrub canopy. Postfire dominance-diversity patterns fit a geometric model as most communities are dominated by a few species and the bulk of the flora comprise subordinates that occupy specific microhabitats. Postfire community assembly is a result of competitive interactions and environmental filtering effects. Beta diversity plays a role in community assembly for as heterogeneity of communities in the landscape increases, the potential species pool for a community increases. Gamma diversity is particularly high because species turnover across latitudinal and elevational gradients is high. The role of diversity in conferring community resilience is complex and a function of the life history of shrub dominants and the historical patterns of fires. Under some circumstances low diversity may be more resilient than high diversity, for example under high fire frequency monotypic stands of Adenostoma fasciculatum may resist change better than diverse stands that include obligate seeding shrubs sensitive to short interval fires. Postfire annuals also are sensitive to short interval fires as these disturbances enhance the invasion by more competitive non-native grasses. Expected increases in anthropogenic ignitions due to population growth are the biggest threat to biodiversity in chaparral.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Valuing chaparral","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-68303-4_2","usgsCitation":"Keeley, J.E., 2018, Drivers of chaparral plant diversity, chap. of Valuing chaparral, p. 29-51, https://doi.org/10.1007/978-3-319-68303-4_2.","productDescription":"24 p.","startPage":"29","endPage":"51","ipdsId":"IP-077516","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","contributors":{"editors":[{"text":"Underwood, Emma C.","contributorId":204451,"corporation":false,"usgs":false,"family":"Underwood","given":"Emma C.","affiliations":[],"preferred":false,"id":758757,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Safford, Hugh D.","contributorId":112922,"corporation":false,"usgs":true,"family":"Safford","given":"Hugh","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":758758,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Molinari, Nicole A.","contributorId":204452,"corporation":false,"usgs":false,"family":"Molinari","given":"Nicole","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":758759,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":758760,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":758712,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70196479,"text":"70196479 - 2018 - Simulating selenium and nitrogen fate and transport in coupled stream-aquifer systems of irrigated regions","interactions":[],"lastModifiedDate":"2018-04-10T16:44:08","indexId":"70196479","displayToPublicDate":"2018-04-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Simulating selenium and nitrogen fate and transport in coupled stream-aquifer systems of irrigated regions","docAbstract":"Elevated levels of selenium (Se) in aqueous environments can harm aquatic life and endanger livestock and human health. Although Se occurs naturally in the rocks and soils of many alluvial aquifers, mining and agricultural activities can increase its rate of mobilization and transport to surface waters. Attention is given here to regions where nonpoint source return flows from irrigated lands carry pollutant loads to aquifers and streams, contributing to concentrations that violate regulatory and performance standards. Of particular concern is the heightened level and mobilization of Se influenced by nitrate (NO3), a harmful pollutant in its own right. We present a numerical model that simulates the reactive transport of Se and nitrogen (N) species in a coupled groundwater-surface water system. Building upon a conceptual model that incorporates the major processes affecting Se and NO3 transport in an irrigated watershed, the model links the finite-difference models MODFLOW, UZF-RT3D, and OTIS, to simulate flow and reactive transport of multiple chemical species in both the aquifer and a stream network, with mass exchange between the two. The capability of the new model is showcased by calibration, testing, and application to a 500 km2 region in Colorado’s Lower Arkansas River Valley using a rich data set gathered over a 10-yr period. Simulation of spatial and temporal distributions of Se concentration reveals conditions that exceed standards in groundwater for approximately 20% of the area. For the Arkansas River, standards are exceeded by 290%–450%. Simulation indicates that river concentrations of NO3 alone are near the current interim standard for the total of all dissolved N species. These results indicate the need for future use of the developed model to investigate the prospects for land and water best management practices to decrease pollutant levels.
The generation of runoff and the resultant flash flooding can be substantially larger following wildfire than for similar rainstorms that precede wildfire disturbance. Flash flooding after the 2011 Las Conchas Fire in New Mexico provided the motivation for this investigation to assess postwildfire effects on soil-hydraulic properties (SHPs) and soil-physical properties (SPPs) as a function of remotely sensed burn severity 4 years following the wildfire. A secondary purpose of this report is to illustrate a methodology to determine SHPs that analyzes infiltrometer data by using three different analysis methods. The SPPs and SHPs are measured as a function of remotely sensed burn severity by using the difference in the Normalized Burn Ratio (dNBR) metric for seven sites. The dNBR metric was used to guide field sample collection across a full spectrum of burn severities that covered the range of Monitoring Trends in Burn Severity (MTBS) and Burned Area Reflectance Classification (BARC) thematic classes from low to high severity. The SPPs (initial and saturated soil-water content, bulk density, soil-organic matter, and soil-particle size) and SHPs (field-saturated hydraulic conductivity and sorptivity) were measured under controlled laboratory conditions for soil cores collected in the field. The SHPs were estimated by using tension infiltrometer measurements and three different data analysis methods. These measurements showed large effects of burn severity, focused in the top
1 centimeter (cm) of soil, on some SPPs (bulk density, soil organic matter, and particle sizes). The threshold of these bulk density and soil organic matter effects was between 300 and 400 dNBR, which corresponds to a MTBS thematic class between moderate and high burn severity and a BARC4 thematic class of high severity. Gravel content and the content of fines in the top 1 cm of soil had a higher threshold value between 450 and 500 dNBR. Lesser effects on SPPs were observed at depths of 1–3 cm and 3–6 cm. In contrast, SHPs showed little effect from dNBR or from MTBS/BARC4 thematic class. Measurements suggested that 4 years of elapsed time after the wildfire may be sufficient for SHP recovery in this area. These measurements also indicated that SPP differences as a function of burn severity cannot be used as reliable indicators of SHP differences as a function of burn severity.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, NM 87113
The ongoing summit eruption at Kīlauea Volcano, Hawai‘i, began in March 2008 with the formation of the Overlook crater, within Halema‘uma‘u Crater. As of late 2016, the Overlook crater contained a large, persistently active lava lake (250 × 190 meters). The accessibility of the lake allows frequent direct observations, and a robust geophysical monitoring network closely tracks subtle changes at the summit. These conditions present one of the best opportunities worldwide for understanding persistent lava lake behavior and the geophysical signals associated with open-vent basaltic eruptions. In this report, we provide a descriptive and visual summary of lava lake activity during 2016, a year consisting of continuous lava lake activity. The lake surface was composed of large black crustal plates separated by narrow incandescent spreading zones. The dominant motion of the surface was normally from north to south, but spattering produced transient disruptions to this steady motion. Spattering in the lake was common, consisting of one or more sites on the lake margin. The Overlook crater was continuously modified by the deposition of spatter (often as a thin veneer) on the crater walls, with frequent collapses of this adhered lava into the lake. Larger collapses, involving lithic material from the crater walls, triggered several small explosive events that deposited bombs and lapilli around the Halema‘uma‘u Crater rim, but these did not threaten public areas. The lava lake level varied over several tens of meters, controlled primarily by changes in summit magma reservoir pressure (in part driven by magma supply rates) and secondarily by fluctuations in spattering and gas release from the lake (commonly involving gas pistoning). The lake emitted a persistent gas plume, normally averaging 1,000–8,000 metric tons per day (t/d) of sulfur dioxide (SO2), as well as a constant fallout of small juvenile and lithic particles, including Pele’s hair and tears. The gas emissions created volcanic air pollution (vog) that affected large areas of the Island of Hawai‘i. The summit eruption has been a major attraction for visitors in Hawai‘i Volcanoes National Park. During 2016, the rising lake levels allowed the lake and its spattering to be more consistently visible from public viewing areas, enhancing the visitor experience. The U.S. Geological Survey’s Hawaiian Volcano Observatory (HVO) closely monitors the summit eruption and keeps emergency managers and the public informed of activity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185008","usgsCitation":"Patrick, M.R., Orr, T.R., Swanson, D.A., Elias, T., and Shiro, B., 2018, Lava lake activity at the summit of Kīlauea Volcano in 2016: U.S. Geological Survey Scientific Investigations Report 2018–5008, 58 p., https://doi.org/10.3133/sir20185008.","productDescription":"vi, 58 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-087932","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5008/coverthb.jpg"},{"id":353299,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5008/sir20185008.pdf","text":"Report","size":"49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5008"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3,\n 19.39\n ],\n [\n -155.23,\n 19.39\n ],\n [\n -155.23,\n 19.44\n ],\n [\n -155.3,\n 19.44\n ],\n [\n -155.3,\n 19.39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"HVO, Volcano Science Center,
Hawaiian Volcano Observatory
U.S. Geological Survey
P.O. Box 51, 1 Crater Rim Road
Hawaiʻi Volcanoes National Park, HI 96718-0051
Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.
The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the physical stream structure, survival, growth, and movement processes ensures that simulations provide results that are relevant to the questions asked about the population under study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Plumb, J.M., Jones, E.C., Som, N.A., Hetrick, N.J., and Hardy, T.B., 2018, Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids: U.S. Geological Survey Open-File Report 2018-1056, 32 p., https://doi.org/10.3133/ofr20181056.","productDescription":"iv, 32 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-092781","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353225,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1056/coverthb.jpg"},{"id":353226,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1056/ofr20181056.pdf","text":"Report","size":"971 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1056"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Capsule: We describe ecological factors associated with movements of a globally declining raptor species, the Eastern Imperial Eagle Aquila heliaca.
Aims: To describe the movements, habitat associations and resource selection of Eastern Imperial Eagles marked in Central Asia.
Methods: We used global positioning system (GPS) data sent via satellite telemetry devices deployed on Eastern Imperial Eagles captured in Kazakhstan to calculate distances travelled and to associate habitat and weather variables with eagle locations collected throughout the annual cycle. We also used resource selection models to evaluate habitat use of tracked birds during autumn migration. Separately, we used wing-tagging recovery data to broaden our understanding of wintering locations of eagles.
Results: Eagles tagged in Kazakhstan wintered in most countries on the Arabian Peninsula, as well as Iran and India. The adult eagle we tracked travelled more efficiently than did the four pre-adults. During autumn migration, telemetered eagles used a mixture of vegetation types, but during winter and summer, they primarily used bare and sparsely vegetated areas. Finally, telemetered birds used orographic updrafts to subsidize their autumn migration flight, but they relied on thermal updrafts during spring migration.
Conclusion: Our study is the first to use GPS telemetry to describe year-round movements and habitat associations of Eastern Imperial Eagles in Central Asia. Our findings provide insight into the ecology of this vulnerable raptor species that can contribute to conservation efforts on its behalf.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00063657.2018.1447907","usgsCitation":"Poessel, S.A., Bragin, E.A., Sharpe, P.B., Garcelon, D.K., Bartoszuk, K., and Katzner, T., 2018, Movements and landscape use of Eastern Imperial Eagles Aquila heliaca in Central Asia: Bird Study, v. 65, no. 2, p. 208-218, https://doi.org/10.1080/00063657.2018.1447907.","productDescription":"11 p.","startPage":"208","endPage":"218","ipdsId":"IP-090963","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-04","publicationStatus":"PW","scienceBaseUri":"5afee6e6e4b0da30c1bfbf0a","contributors":{"authors":[{"text":"Poessel, Sharon A. 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":168465,"corporation":false,"usgs":true,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":732919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragin, Evgeny A.","contributorId":194894,"corporation":false,"usgs":false,"family":"Bragin","given":"Evgeny","email":"","middleInitial":"A.","affiliations":[{"id":35656,"text":"Science Department, Naurzum National Nature Reserve, Kostanay Oblast, Naurzumski Raijon, Karamendy, Kazakhstan","active":true,"usgs":false}],"preferred":false,"id":732920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Peter B.","contributorId":204011,"corporation":false,"usgs":false,"family":"Sharpe","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":36796,"text":"Institute for Wildlife Studies, Arcata, CA, USA","active":true,"usgs":false}],"preferred":false,"id":732921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcelon, David K.","contributorId":204012,"corporation":false,"usgs":false,"family":"Garcelon","given":"David","email":"","middleInitial":"K.","affiliations":[{"id":36796,"text":"Institute for Wildlife Studies, Arcata, CA, USA","active":true,"usgs":false}],"preferred":false,"id":732922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartoszuk, Kordian","contributorId":204013,"corporation":false,"usgs":false,"family":"Bartoszuk","given":"Kordian","email":"","affiliations":[{"id":36797,"text":"Aquila, Grzędy 2, 19-206 Rajgrod, Poland","active":true,"usgs":false}],"preferred":false,"id":732923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":732924,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196417,"text":"70196417 - 2018 - The future of fish passage science, engineering, and practice","interactions":[],"lastModifiedDate":"2018-04-06T10:40:10","indexId":"70196417","displayToPublicDate":"2018-04-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"The future of fish passage science, engineering, and practice","docAbstract":"Much effort has been devoted to developing, constructing and refining fish passage facilities to enable target species to pass barriers on fluvial systems, and yet, fishway science, engineering and practice remain imperfect. In this review, 17 experts from different fish passage research fields (i.e., biology, ecology, physiology, ecohydraulics, engineering) and from different continents (i.e., North and South America, Europe, Africa, Australia) identified knowledge gaps and provided a roadmap for research priorities and technical developments. Once dominated by an engineering‐focused approach, fishway science today involves a wide range of disciplines from fish behaviour to socioeconomics to complex modelling of passage prioritization options in river networks. River barrier impacts on fish migration and dispersal are currently better understood than historically, but basic ecological knowledge underpinning the need for effective fish passage in many regions of the world, including in biodiversity hotspots (e.g., equatorial Africa, South‐East Asia), remains largely unknown. Designing efficient fishways, with minimal passage delay and post‐passage impacts, requires adaptive management and continued innovation. While the use of fishways in river restoration demands a transition towards fish passage at the community scale, advances in selective fishways are also needed to manage invasive fish colonization. Because of the erroneous view in some literature and communities of practice that fish passage is largely a proven technology, improved international collaboration, information sharing, method standardization and multidisciplinary training are needed. Further development of regional expertise is needed in South America, Asia and Africa where hydropower dams are currently being planned and constructed.
","language":"English","publisher":"Wiley","doi":"10.1111/faf.12258","usgsCitation":"Silva, A.T., Lucas, M.C., Castro-Santos, T.R., Katopodis, C., Baumgartner, L.J., Thiem, J.D., Aarestrup, K., Pompeu, P.S., O’Brien, G.C., Braun, D.C., Burnett, N.J., Zhu, D.Z., Fjeldstad, H., Forseth, T., Rajarathnam, N., Williams, J.G., and Cooke, S., 2018, The future of fish passage science, engineering, and practice: Fish and Fisheries, v. 19, no. 2, p. 340-362, https://doi.org/10.1111/faf.12258.","productDescription":"23 p.","startPage":"340","endPage":"362","ipdsId":"IP-084784","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468845,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/faf.12258","text":"Publisher Index Page"},{"id":353213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-28","publicationStatus":"PW","scienceBaseUri":"5afee6e6e4b0da30c1bfbf0e","contributors":{"authors":[{"text":"Silva, Ana T.","contributorId":203987,"corporation":false,"usgs":false,"family":"Silva","given":"Ana","email":"","middleInitial":"T.","affiliations":[{"id":36784,"text":"Norsk Institutt for Naturforskning","active":true,"usgs":false}],"preferred":false,"id":732839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Martyn C.","contributorId":18725,"corporation":false,"usgs":true,"family":"Lucas","given":"Martyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":732838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katopodis, Christos","contributorId":203989,"corporation":false,"usgs":false,"family":"Katopodis","given":"Christos","email":"","affiliations":[{"id":36786,"text":"Katopodis Ecohydraulics Ltd","active":true,"usgs":false}],"preferred":false,"id":732841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baumgartner, Lee J.","contributorId":203990,"corporation":false,"usgs":false,"family":"Baumgartner","given":"Lee","email":"","middleInitial":"J.","affiliations":[{"id":36787,"text":"Charles Sturt University, Institute for Land, Water, and Society","active":true,"usgs":false}],"preferred":false,"id":732842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiem, Jason D.","contributorId":75421,"corporation":false,"usgs":true,"family":"Thiem","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":732843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aarestrup, Kim","contributorId":203992,"corporation":false,"usgs":false,"family":"Aarestrup","given":"Kim","email":"","affiliations":[{"id":36789,"text":"Danmarks Tekniske Universitet","active":true,"usgs":false}],"preferred":false,"id":732844,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pompeu, Paulo S.","contributorId":203993,"corporation":false,"usgs":false,"family":"Pompeu","given":"Paulo","email":"","middleInitial":"S.","affiliations":[{"id":36790,"text":"Universidad Federal de Lavras, Department de Biologia","active":true,"usgs":false}],"preferred":false,"id":732845,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Brien, Gordon C.","contributorId":203994,"corporation":false,"usgs":false,"family":"O’Brien","given":"Gordon","email":"","middleInitial":"C.","affiliations":[{"id":36791,"text":"University of KwaZulu-Natal, School of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":732846,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Braun, Douglas C.","contributorId":204003,"corporation":false,"usgs":false,"family":"Braun","given":"Douglas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732875,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Burnett, Nicholas J.","contributorId":203995,"corporation":false,"usgs":false,"family":"Burnett","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36792,"text":"University of British Columbia, Forest and Conservation Sciences","active":true,"usgs":false}],"preferred":false,"id":732847,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zhu, David Z.","contributorId":203996,"corporation":false,"usgs":false,"family":"Zhu","given":"David","email":"","middleInitial":"Z.","affiliations":[{"id":36793,"text":"Department of Civil and Environmental Engineering, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":732848,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Fjeldstad, Hans-Petter","contributorId":203997,"corporation":false,"usgs":false,"family":"Fjeldstad","given":"Hans-Petter","email":"","affiliations":[{"id":36794,"text":"SINTEF Energy AS","active":true,"usgs":false}],"preferred":false,"id":732849,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Forseth, Torbjorn","contributorId":203998,"corporation":false,"usgs":false,"family":"Forseth","given":"Torbjorn","email":"","affiliations":[{"id":36784,"text":"Norsk Institutt for Naturforskning","active":true,"usgs":false}],"preferred":false,"id":732850,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rajarathnam, Nallamuthu","contributorId":203999,"corporation":false,"usgs":false,"family":"Rajarathnam","given":"Nallamuthu","email":"","affiliations":[{"id":36793,"text":"Department of Civil and Environmental Engineering, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":732851,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Williams, John G.","contributorId":10270,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":732852,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":732853,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70196412,"text":"70196412 - 2018 - Carnivore hotspots in Peninsular Malaysia and their landscape attributes","interactions":[],"lastModifiedDate":"2018-04-06T10:44:11","indexId":"70196412","displayToPublicDate":"2018-04-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Carnivore hotspots in Peninsular Malaysia and their landscape attributes","docAbstract":"Mammalian carnivores play a vital role in ecosystem functioning. However, they are prone to extinction because of low population densities and growth rates, and high levels of persecution or exploitation. In tropical biodiversity hotspots such as Peninsular Malaysia, rapid conversion of natural habitats threatens the persistence of this vulnerable group of animals. Here, we carried out the first comprehensive literature review on 31 carnivore species reported to occur in Peninsular Malaysia and updated their probable distribution. We georeferenced 375 observations of 28 species of carnivore from 89 unique geographic locations using records spanning 1948 to 2014. Using the Getis-Ord Gi*statistic and weighted survey records by IUCN Red List status, we identified hotspots of species that were of conservation concern and built regression models to identify environmental and anthropogenic landscape factors associated with Getis-Ord Gi* z scores. Our analyses identified two carnivore hotspots that were spatially concordant with two of the peninsula’s largest and most contiguous forest complexes, associated with Taman Negara National Park and Royal Belum State Park. A cold spot overlapped with the southwestern region of the Peninsula, reflecting the disappearance of carnivores with higher conservation rankings from increasingly fragmented natural habitats. Getis-Ord Gi* z scores were negatively associated with elevation, and positively associated with the proportion of natural land cover and distance from the capital city. Malaysia contains some of the world’s most diverse carnivore assemblages, but recent rates of forest loss are some of the highest in the world. Reducing poaching and maintaining large, contiguous tracts of lowland forests will be crucial, not only for the persistence of threatened carnivores, but for many mammalian species in general.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0194217","usgsCitation":"Ratnayeke, S., van Manen, F.T., Clements, G.R., Mohd Kulaimi, N.A., and Sharp, S.P., 2018, Carnivore hotspots in Peninsular Malaysia and their landscape attributes: PLoS ONE, v. 13, no. 4, p. 1-18, https://doi.org/10.1371/journal.pone.0194217.","productDescription":"e0194217; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-092271","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468846,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0194217","text":"Publisher Index Page"},{"id":353215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malaysia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 99.931640625,\n 1.2303741774326145\n ],\n [\n 104.3701171875,\n 1.2303741774326145\n ],\n [\n 104.3701171875,\n 6.610044093207648\n ],\n [\n 99.931640625,\n 6.610044093207648\n ],\n [\n 99.931640625,\n 1.2303741774326145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-04","publicationStatus":"PW","scienceBaseUri":"5afee6e6e4b0da30c1bfbf10","contributors":{"authors":[{"text":"Ratnayeke, Shyamala","contributorId":203978,"corporation":false,"usgs":false,"family":"Ratnayeke","given":"Shyamala","email":"","affiliations":[{"id":36779,"text":"Department of Biological Sciences, Sunway University, Malaysia","active":true,"usgs":false}],"preferred":false,"id":732817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":732816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Gopalasamy Reuben","contributorId":203979,"corporation":false,"usgs":false,"family":"Clements","given":"Gopalasamy","email":"","middleInitial":"Reuben","affiliations":[{"id":36779,"text":"Department of Biological Sciences, Sunway University, Malaysia","active":true,"usgs":false}],"preferred":false,"id":732818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohd Kulaimi, Noor Azleen","contributorId":203980,"corporation":false,"usgs":false,"family":"Mohd Kulaimi","given":"Noor","email":"","middleInitial":"Azleen","affiliations":[{"id":36780,"text":"Ex-Situ Conservation Division, Department of Wildlife and National Parks, Malaysia","active":true,"usgs":false}],"preferred":false,"id":732819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharp, Stuart P.","contributorId":203981,"corporation":false,"usgs":false,"family":"Sharp","given":"Stuart","email":"","middleInitial":"P.","affiliations":[{"id":36781,"text":"Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK","active":true,"usgs":false}],"preferred":false,"id":732820,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196400,"text":"70196400 - 2018 - Biota connect aquatic habitats throughout freshwater ecosystem mosaics","interactions":[],"lastModifiedDate":"2018-04-05T11:25:03","indexId":"70196400","displayToPublicDate":"2018-04-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Biota connect aquatic habitats throughout freshwater ecosystem mosaics","docAbstract":"Freshwater ecosystems are linked at various spatial and temporal scales by movements of biota adapted to life in water. We review the literature on movements of aquatic organisms that connect different types of freshwater habitats, focusing on linkages from streams and wetlands to downstream waters. Here, streams, wetlands, rivers, lakes, ponds, and other freshwater habitats are viewed as dynamic freshwater ecosystem mosaics (FEMs) that collectively provide the resources needed to sustain aquatic life. Based on existing evidence, it is clear that biotic linkages throughout FEMs have important consequences for biological integrity and biodiversity. All aquatic organisms move within and among FEM components, but differ in the mode, frequency, distance, and timing of their movements. These movements allow biota to recolonize habitats, avoid inbreeding, escape stressors, locate mates, and acquire resources. Cumulatively, these individual movements connect populations within and among FEMs and contribute to local and regional diversity, resilience to disturbance, and persistence of aquatic species in the face of environmental change. Thus, the biological connections established by movement of biota among streams, wetlands, and downstream waters are critical to the ecological integrity of these systems. Future research will help advance our understanding of the movements that link FEMs and their cumulative effects on downstream waters.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12634","usgsCitation":"Schofield, K.A., Alexander, L.C., Ridley, C.E., Vanderhoof, M.K., Fritz, K.M., Autrey, B., DeMeester, J., Kepner, W.G., Lane, C., Leibowitz, S., and Pollard, A.I., 2018, Biota connect aquatic habitats throughout freshwater ecosystem mosaics: Journal of the American Water Resources Association, v. 54, no. 2, p. 372-399, https://doi.org/10.1111/1752-1688.12634.","productDescription":"28 p.","startPage":"372","endPage":"399","ipdsId":"IP-085914","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468847,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6621606","text":"External Repository"},{"id":353181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e7e4b0da30c1bfbf1e","contributors":{"authors":[{"text":"Schofield, Kate A.","contributorId":203969,"corporation":false,"usgs":false,"family":"Schofield","given":"Kate","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":732761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ridley, Caroline E.","contributorId":203967,"corporation":false,"usgs":false,"family":"Ridley","given":"Caroline","email":"","middleInitial":"E.","affiliations":[{"id":36774,"text":"USEPA NCEA","active":true,"usgs":false}],"preferred":false,"id":732763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":732760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":732764,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Autrey, Bradley","contributorId":203961,"corporation":false,"usgs":false,"family":"Autrey","given":"Bradley","email":"","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":732765,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeMeester, Julie","contributorId":203962,"corporation":false,"usgs":false,"family":"DeMeester","given":"Julie","email":"","affiliations":[{"id":34601,"text":"Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":732766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kepner, William G.","contributorId":174144,"corporation":false,"usgs":false,"family":"Kepner","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":732767,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":732768,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leibowitz, Scott","contributorId":192092,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","affiliations":[],"preferred":false,"id":732769,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pollard, Amina I.","contributorId":203965,"corporation":false,"usgs":false,"family":"Pollard","given":"Amina","email":"","middleInitial":"I.","affiliations":[{"id":36775,"text":"USEPA, Office of Water","active":true,"usgs":false}],"preferred":false,"id":732770,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70196394,"text":"70196394 - 2018 - Montane-breeding bird distribution and abundance across national parks of southwestern Alaska","interactions":[],"lastModifiedDate":"2018-06-04T16:07:16","indexId":"70196394","displayToPublicDate":"2018-04-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Montane-breeding bird distribution and abundance across national parks of southwestern Alaska","docAbstract":"Between 2004 and 2008, biologists conducted an inventory of breeding birds during May–June primarily in montane areas (>100 m above sea level) in Aniakchak National Monument and Preserve (Aniakchak NMP), Katmai National Park and Preserve (Katmai NPP), and Lake Clark National Park and Preserve (Lake Clark NPP) in southwestern Alaska. Observers conducted 1,021 point counts along 169 transects within 63 10-km × 10-km plots that were randomly selected and stratified by ecological subsection. We created hierarchical N-mixture models to estimate detection probability and abundance for 15 species, including 12 passerines, 2 galliforms, and 1 shorebird. We first modeled detection probability relative to observer, date within season, and proportion of dense vegetation cover around the point, then modeled abundance as a function of land cover composition (proportion of seven coarse-scale land cover types) within 300 m of the survey point. Land cover relationships varied widely among species but most showed selection for low to tall shrubs (0.2–5 m tall) and an avoidance of alpine and 2 dwarf shrub–herbaceous cover types. After adjusting for species not observed, we estimated a minimum of 107 ± 9 species bred in the areas surveyed within the three parks combined. Species richness was negatively associated with elevation and associated land cover types. At comparable levels of survey effort (n = 721 birds detected), species richness was greatest in Lake Clark NPP (75 ± 12 species), lowest in Aniakchak NMP (45 ± 6 species), and intermediate at Katmai NPP (59 ± 10 species). Species richness was similar at equivalent survey effort (n = 973 birds detected) within the Lime Hills, Alaska Range, and Alaska Peninsula ecoregions (68 ± 8; 79 ± 11; 67 ± 11, respectively). Species composition was similar across all three parks and across the three major ecoregions (Alaska Range, Alaska Peninsula, Lime Hills) that encompass them. Our results provide baseline estimates of relative abundance and models of abundance and species richness relative to land cover that can be used to assess future changes in avian distribution. Additionally, these subarctic montane parks may serve as signals of landscape change and barometers for the assessment of population and distributional changes as a result of warming temperatures and changing precipitation patterns.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/062017-JFWM-050","usgsCitation":"Amundson, C.L., Handel, C.M., Ruthrauff, D.R., Tibbitts, T.L., and Gill, R., 2018, Montane-breeding bird distribution and abundance across national parks of southwestern Alaska: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 180-207, https://doi.org/10.3996/062017-JFWM-050.","productDescription":"28 p.","startPage":"180","endPage":"207","ipdsId":"IP-085392","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":501965,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1IYXYTN","text":"USGS data release","linkHelpText":"Data Supporting the Inventory of Montane-nesting Birds in Katmai National Park and Preserve and Lake Clark National Park and Preserve, Alaska"},{"id":468850,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/062017-jfwm-050","text":"Publisher Index Page"},{"id":437960,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KW50B3","text":"USGS data release","linkHelpText":"Data from the Inventory of Montane-nesting Birds in the Aniakchak National Monument and Preserve, Alaska"},{"id":437959,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MW2GD3","text":"USGS data release","linkHelpText":"Data for Montane-breeding Bird Distribution and Abundance across National Parks of Southwestern Alaska, 2004-2008"},{"id":353183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.5,\n 56.5\n ],\n [\n -152.5,\n 56.5\n ],\n [\n -152.5,\n 61.5\n ],\n [\n -158.5,\n 61.5\n ],\n [\n -158.5,\n 56.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-22","publicationStatus":"PW","scienceBaseUri":"5afee6e7e4b0da30c1bfbf22","contributors":{"authors":[{"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":732731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruthrauff, Daniel R. 0000-0003-1355-9156 druthrauff@usgs.gov","orcid":"https://orcid.org/0000-0003-1355-9156","contributorId":4181,"corporation":false,"usgs":true,"family":"Ruthrauff","given":"Daniel","email":"druthrauff@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":140455,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":732734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732735,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196401,"text":"70196401 - 2018 - Connectivity of streams and wetlands to downstream waters: An integrated systems framework","interactions":[],"lastModifiedDate":"2018-04-05T11:29:37","indexId":"70196401","displayToPublicDate":"2018-04-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Connectivity of streams and wetlands to downstream waters: An integrated systems framework","docAbstract":"Interest in connectivity has increased in the aquatic sciences, partly because of its relevance to the Clean Water Act. This paper has two objectives: (1) provide a framework to understand hydrological, chemical, and biological connectivity, focusing on how headwater streams and wetlands connect to and contribute to rivers; and (2) briefly review methods to quantify hydrological and chemical connectivity. Streams and wetlands affect river structure and function by altering material and biological fluxes to the river; this depends on two factors: (1) functions within streams and wetlands that affect material fluxes; and (2) connectivity (or isolation) from streams and wetlands to rivers that allows (or prevents) material transport between systems. Connectivity can be described in terms of frequency, magnitude, duration, timing, and rate of change. It results from physical characteristics of a system, e.g., climate, soils, geology, topography, and the spatial distribution of aquatic components. Biological connectivity is also affected by traits and behavior of the biota. Connectivity can be altered by human impacts, often in complex ways. Because of variability in these factors, connectivity is not constant but varies over time and space. Connectivity can be quantified with field‐based methods, modeling, and remote sensing. Further studies using these methods are needed to classify and quantify connectivity of aquatic ecosystems and to understand how impacts affect connectivity.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12631","usgsCitation":"Leibowitz, S.G., Wigington, P., Schoefield, K.A., Alexander, L.C., Vanderhoof, M.K., and Golden, H.E., 2018, Connectivity of streams and wetlands to downstream waters: An integrated systems framework: Journal of the American Water Resources Association, v. 54, no. 2, p. 298-322, https://doi.org/10.1111/1752-1688.12631.","productDescription":"25 p.","startPage":"298","endPage":"322","ipdsId":"IP-082971","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6071435","text":"Publisher Index Page"},{"id":353182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e7e4b0da30c1bfbf1c","contributors":{"authors":[{"text":"Leibowitz, Scott G.","contributorId":156432,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":732772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wigington, Parker J.","contributorId":203968,"corporation":false,"usgs":false,"family":"Wigington","given":"Parker J.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":732773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoefield, Kate A.","contributorId":203970,"corporation":false,"usgs":false,"family":"Schoefield","given":"Kate","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":732774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":732775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":732771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golden, Heather E.","contributorId":202423,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":36429,"text":"USEPA ORD","active":true,"usgs":false}],"preferred":false,"id":732776,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196377,"text":"70196377 - 2018 - Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds","interactions":[],"lastModifiedDate":"2018-04-04T11:17:32","indexId":"70196377","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds","title":"Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds","docAbstract":"Lampreys have a worldwide distribution, are functionally important to ecological communities and serve significant roles in many cultures. In Pacific coast drainages of North America, lamprey populations have suffered large declines. However, lamprey population status and trends within many areas of this region are unknown and such information is needed for advancing conservation goals. We developed two quantitative PCR-based, aquatic environmental DNA (eDNA) assays for detection of Pacific Lamprey (Entosphenus tridentatus) and Lampetra spp, using locked nucleic acids (LNAs) in the probe design. We used these assays to characterize the spatial distribution of lamprey in 18 watersheds of Puget Sound, Washington, by collecting water samples in spring and fall. Pacific Lamprey and Lampetraspp were each detected in 14 watersheds and co-occurred in 10 watersheds. Lamprey eDNA detection rates were much higher in spring compared to fall. Specifically, the Pacific Lamprey eDNA detection rate was 3.5 times higher in spring and the Lampetra spp eDNA detection rate was 1.5 times higher in spring even though larval lamprey are present in streams year-round. This significant finding highlights the importance of seasonality on eDNA detection. Higher stream discharge in the fall likely contributed to reduced eDNA detection rates, although seasonal life history events may have also contributed. These eDNA assays differentiate Pacific Lamprey and Lampetra spp across much of their range along the west coast of North America. Sequence analysis indicates the Pacific Lamprey assay also targets other Entosphenus spp and indicates the Lampetra spp assay may have limited or no capability of detecting Lampetra in some locations south of the Columbia River Basin. Nevertheless, these assays will serve as a valuable tool for resource managers and have direct application to lamprey conservation efforts, such as mapping species distributions, occupancy modeling, and monitoring translocations and reintroductions.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.4496","usgsCitation":"Ostberg, C.O., Chase, D.M., Hayes, M.C., and Duda, J.J., 2018, Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds: PeerJ, v. 6, p. 1-25, https://doi.org/10.7717/peerj.4496.","productDescription":"e4496; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-090879","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468852,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.4496","text":"Publisher Index Page"},{"id":437962,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H994DT","text":"USGS data release","linkHelpText":"Distribution and seasonal differences in Pacific Lamprey and Lampetra spp eDNA across 18 Puget Sound watersheds, 2014 and 2015"},{"id":353142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.61267089843751,\n 46.882723010671945\n ],\n [\n -121.7340087890625,\n 46.882723010671945\n ],\n [\n -121.7340087890625,\n 49.05227025601607\n ],\n [\n -123.61267089843751,\n 49.05227025601607\n ],\n [\n -123.61267089843751,\n 46.882723010671945\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf2d","contributors":{"authors":[{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Dorothy M. 0000-0002-7759-2687","orcid":"https://orcid.org/0000-0002-7759-2687","contributorId":203926,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":145486,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":732670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196373,"text":"70196373 - 2018 - N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models","interactions":[],"lastModifiedDate":"2018-07-03T11:30:22","indexId":"70196373","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models","docAbstract":"Models that formulate mathematical linkages between fish use and habitat characteristics are applied for many purposes. For riverine fish, these linkages are often cast as resource selection functions with variables including depth and velocity of water and distance to nearest cover. Ecologists are now recognizing the role that detection plays in observing organisms, and failure to account for imperfect detection can lead to spurious inference. Herein, we present a flexible N-mixture model to associate habitat characteristics with the abundance of riverine salmonids that simultaneously estimates detection probability. Our formulation has the added benefits of accounting for demographics variation and can generate probabilistic statements regarding intensity of habitat use. In addition to the conceptual benefits, model application to data from the Trinity River, California, yields interesting results. Detection was estimated to vary among surveyors, but there was little spatial or temporal variation. Additionally, a weaker effect of water depth on resource selection is estimated than that reported by previous studies not accounting for detection probability. N-mixture models show great promise for applications to riverine resource selection.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0027","usgsCitation":"Som, N.A., Perry, R.W., Jones, E.C., De Juilio, K., Petros, P., Pinnix, W.D., and Rupert, D.L., 2018, N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 7, p. 1048-1058, https://doi.org/10.1139/cjfas-2017-0027.","productDescription":"11 p.","startPage":"1048","endPage":"1058","ipdsId":"IP-086618","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":501089,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/82344","text":"External Repository"},{"id":353134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf2f","contributors":{"authors":[{"text":"Som, Nicholas A.","contributorId":203773,"corporation":false,"usgs":false,"family":"Som","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":36713,"text":"Statistician, USFWS - Arcata Fisheries Program, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":732647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Edward C. 0000-0001-7255-1475 ejones@usgs.gov","orcid":"https://orcid.org/0000-0001-7255-1475","contributorId":203917,"corporation":false,"usgs":true,"family":"Jones","given":"Edward","email":"ejones@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De Juilio, Kyle","contributorId":203918,"corporation":false,"usgs":false,"family":"De Juilio","given":"Kyle","affiliations":[{"id":36756,"text":"Yurok Tribal Fisheries Program, Weaverville, CA 96093","active":true,"usgs":false}],"preferred":false,"id":732649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petros, Paul","contributorId":203920,"corporation":false,"usgs":false,"family":"Petros","given":"Paul","email":"","affiliations":[{"id":36758,"text":"Humboldt State University, Department of Fisheries Biology, Arcata, CA 95521","active":true,"usgs":false}],"preferred":false,"id":732651,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pinnix, William D.","contributorId":203925,"corporation":false,"usgs":false,"family":"Pinnix","given":"William","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":732666,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rupert, Derek L.","contributorId":203919,"corporation":false,"usgs":false,"family":"Rupert","given":"Derek","email":"","middleInitial":"L.","affiliations":[{"id":36757,"text":"U.S. Fish and Wildlife Service, Arcata FWO, Arcata, CA 95521","active":true,"usgs":false}],"preferred":false,"id":732650,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196369,"text":"70196369 - 2018 - A laboratory-calibrated model of coho salmon growth with utility for ecological analyses","interactions":[],"lastModifiedDate":"2018-04-24T14:17:03","indexId":"70196369","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A laboratory-calibrated model of coho salmon growth with utility for ecological analyses","docAbstract":"We conducted a meta-analysis of laboratory- and hatchery-based growth data to estimate broadly applicable parameters of mass- and temperature-dependent growth of juvenile coho salmon (Oncorhynchus kisutch). Following studies of other salmonid species, we incorporated the Ratkowsky growth model into an allometric model and fit this model to growth observations from eight studies spanning ten different populations. To account for changes in growth patterns with food availability, we reparameterized the Ratkowsky model to scale several of its parameters relative to ration. The resulting model was robust across a wide range of ration allocations and experimental conditions, accounting for 99% of the variation in final body mass. We fit this model to growth data from coho salmon inhabiting tributaries and constructed ponds in the Klamath Basin by estimating habitat-specific indices of food availability. The model produced evidence that constructed ponds provided higher food availability than natural tributaries. Because of their simplicity (only mass and temperature are required as inputs) and robustness, ration-varying Ratkowsky models have utility as an ecological tool for capturing growth in freshwater fish populations.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0506","usgsCitation":"Manhard, C.V., Som, N.A., Perry, R.W., and Plumb, J.M., 2018, A laboratory-calibrated model of coho salmon growth with utility for ecological analyses: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 5, p. 682-690, https://doi.org/10.1139/cjfas-2016-0506.","productDescription":"9 p.","startPage":"682","endPage":"690","ipdsId":"IP-080976","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468854,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0506","text":"External Repository"},{"id":353137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf31","contributors":{"authors":[{"text":"Manhard, Christopher V.","contributorId":203911,"corporation":false,"usgs":false,"family":"Manhard","given":"Christopher","email":"","middleInitial":"V.","affiliations":[{"id":36754,"text":"U.S. Fish and Wildlife Service, California Cooperative Fish and Wildlife Research Unit, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA","active":true,"usgs":false}],"preferred":false,"id":732636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Som, Nicholas A.","contributorId":203773,"corporation":false,"usgs":false,"family":"Som","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":36713,"text":"Statistician, USFWS - Arcata Fisheries Program, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":732637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196367,"text":"70196367 - 2018 - Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data","interactions":[],"lastModifiedDate":"2018-04-04T11:04:31","indexId":"70196367","displayToPublicDate":"2018-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data","title":"Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data","docAbstract":"The goals were to (i) determine if river discharge and water temperature during various early life history stages were predictors of age‐0 White Sturgeon, Acipenser transmontanus, recruitment, and (ii) provide an example of how over‐dispersed catch data, including data with many zero observations, can be used to better understand the effects of regulated rivers on the productivity of depressed sturgeon populations. An information theoretic approach was used to develop and select negative binomial and zero‐inflated negative binomial models that model the relation of age‐0 White Sturgeon survey data from three contiguous Columbia River reservoirs to river discharge and water temperature during spawning, egg incubation, larval, and post‐larval phases. Age‐0 White Sturgeon were collected with small mesh gill nets in The Dalles and John Day reservoirs from 1997 to 2014 and a bottom trawl in Bonneville Reservoir from 1989 to 2006. Results suggest that seasonal river discharge was positively correlated with age‐0 recruitment; notably that discharge, 16 June–31 July was positively correlated to age‐0 recruitment in all three reservoirs. The best approximating models for two of the three reservoirs also suggest that seasonal water temperature may be a determinant of age‐0 recruitment. Our research demonstrates how over‐dispersed catch data can be used to better understand the effects of environmental conditions on sturgeon populations caused by the construction and operation of dams.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.13570","usgsCitation":"Counihan, T.D., and Chapman, C.G., 2018, Relating river discharge and water temperature to the recruitment of age‐0 White Sturgeon (Acipenser transmontanus Richardson, 1836) in the Columbia River using over‐dispersed catch data: Journal of Applied Ichthyology, v. 34, no. 2, p. 279-289, https://doi.org/10.1111/jai.13570.","productDescription":"11 p.","startPage":"279","endPage":"289","ipdsId":"IP-074421","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":460965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.13570","text":"Publisher Index Page"},{"id":353138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.12353515624999,\n 45.213003555993964\n ],\n [\n -117.12524414062501,\n 45.213003555993964\n ],\n [\n -117.12524414062501,\n 46.800059446787316\n ],\n [\n -124.12353515624999,\n 46.800059446787316\n ],\n [\n -124.12353515624999,\n 45.213003555993964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf33","contributors":{"authors":[{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Colin G.","contributorId":197963,"corporation":false,"usgs":false,"family":"Chapman","given":"Colin","email":"","middleInitial":"G.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":732627,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196313,"text":"ofr20171157 - 2018 - Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy","interactions":[],"lastModifiedDate":"2025-05-13T16:22:30.827212","indexId":"ofr20171157","displayToPublicDate":"2018-04-03T10:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1157","title":"Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy","docAbstract":"The Nation’s eastern coast is fringed by beaches, dunes, barrier islands, wetlands, and bluffs. These natural coastal barriers provide critical benefits and services, and can mitigate the impact of storms, erosion, and sea-level rise on our coastal communities. Waves and storm surge resulting from Hurricane Sandy, which made landfall along the New Jersey coast on October 29, 2012, impacted the U.S. coastline from North Carolina to Massachusetts, including Assateague Island, Maryland and Virginia, and the Delmarva coastal system. The storm impacts included changes in topography, coastal morphology, geology, hydrology, environmental quality, and ecosystems.
In the immediate aftermath of the storm, light detection and ranging (lidar) surveys from North Carolina to New York documented storm impacts to coastal barriers, providing a baseline to assess vulnerability of the reconfigured coast. The focus of much of the existing coastal change assessment is along the ocean-facing coastline; however, much of the coastline affected by Hurricane Sandy includes the estuarine-facing coastlines of barrier-island systems. Specifically, the wetland and back-barrier shorelines experienced substantial change as a result of wave action and storm surge that occurred during Hurricane Sandy (see also USGS photograph, http://coastal.er.usgs.gov/hurricanes/sandy/photo-comparisons/virginia.php). Assessing physical shoreline and wetland change (land loss as well as land gains) can help to determine the resiliency of wetland systems that protect adjacent habitat, shorelines, and communities.
To address storm impacts to wetlands, a vulnerability assessment should describe both long-term (for example, several decades) and short-term (for example, Sandy’s landfall) extent and character of the interior wetlands and the back-barrier-shoreline changes. The objective of this report is to describe several new wetland vulnerability assessments based on the detailed physical changes estimated from observations. The scope includes understanding changes caused by both short- and long-term processes using both remotely sensed and in situ observations to characterize changes to the wetland in terms of accretion/expansion and erosion/contraction. Accretion may be due to net vertical and (or) horizontal deposition, including estuarine-shoreline change due to overwash. Wetland erosion may be due to elevated waves and water levels in the estuary itself. We included additional information based on wave runup and storm-surge elevations based on models and elevation data. We then developed a predictive assessment for wetland vulnerability that describes the likelihood of changes of the estuarine shoreline and the landward extent of sand overwash driven by processes occurring on the ocean-facing shoreline. This assessment is intended to be linked to the beach and dune vulnerability assessments that have been developed previously.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171157","usgsCitation":"Plant, N.G., Smith, K.E.L., Passeri, D.L., Smith, C.G., and Bernier, J.C., 2018, Barrier-island and estuarine-wetland physical-change assessment after Hurricane Sandy: U.S. Geological Survey Open-File Report 2017–1157, 36 p., https://doi.org/10.3133/ofr20171157.","productDescription":"viii, 36 p.","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073468","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1157/coverthb.jpg"},{"id":353052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1157/ofr20171157.pdf","text":"Report","size":"7.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1157"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Wild mammals are known to survive injuries that result in skeletal abnormalities. Quantifying and comparing skeletal injuries among species can provide insight into the factors that cause skeletal injuries and enable survival following an injury. We documented the prevalence and location of structural bone abnormalities in a community of 7 small mammal species inhabiting the White Mountains of New Hampshire. These species differ in locomotion type and levels of intraspecific aggression. Overall, the majority of injuries were to the ribs or caudal vertebrae. Incidence of skeletal injuries was highest in older animals, indicating that injuries accumulate over a lifetime. Compared to species with ambulatory locomotion, those with more specialized (semi-fossorial, saltatorial, and scansorial) locomotion exhibited fewer skeletal abnormalities in the arms and legs, which we hypothesize is a result of a lesser ability to survive limb injuries. Patterns of skeletal injuries in shrews (Soricidae) were consistent with intraspecific aggression, particularly in males, whereas skeletal injuries in rodents (Rodentia) were more likely accidental or resulting from interactions with predators. Our results demonstrate that both the incidence and pattern of skeletal injuries vary by species and suggest that the ability of an individual to survive a specific skeletal injury depends on its severity and location as well as the locomotor mode of the species involved.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyy020","usgsCitation":"Stephens, R.B., Burke, C.B., Woodman, N., Poland, L.B., and Rowe, R.J., 2018, Skeletal injuries in small mammals: a multispecies assessment of prevalence and location: Journal of Mammalogy, v. 99, no. 2, p. 486-497, https://doi.org/10.1093/jmammal/gyy020.","productDescription":"12 p.","startPage":"486","endPage":"497","ipdsId":"IP-094876","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468857,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyy020","text":"Publisher Index Page"},{"id":353122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5afee6e8e4b0da30c1bfbf3b","contributors":{"authors":[{"text":"Stephens, Ryan B.","contributorId":203881,"corporation":false,"usgs":false,"family":"Stephens","given":"Ryan","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Christopher B.","contributorId":203882,"corporation":false,"usgs":false,"family":"Burke","given":"Christopher","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poland, Lily B.","contributorId":203883,"corporation":false,"usgs":false,"family":"Poland","given":"Lily","email":"","middleInitial":"B.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowe, Rebecca J.","contributorId":203884,"corporation":false,"usgs":false,"family":"Rowe","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":36740,"text":"Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham NH 03824-3534, USA","active":true,"usgs":false}],"preferred":false,"id":732589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194741,"text":"sir20175155 - 2018 - Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13","interactions":[],"lastModifiedDate":"2018-04-09T15:08:19","indexId":"sir20175155","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","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":"2017-5155","title":"Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13","docAbstract":"Coal combustion byproducts (CCBs), which are composed of fly ash, bottom ash, and flue gas desulfurization material, produced at the coal-fired San Juan Generating Station (SJGS), located in San Juan County, New Mexico, have been buried in former surface-mine pits at the San Juan Mine, also referred to as the San Juan Coal Mine, since operations began in the early 1970s. This report, prepared by the U.S. Geological Survey in cooperation with the Mining and Minerals Division of the New Mexico Energy, Minerals and Natural Resources Department, describes results of a hydrogeologic assessment, including numerical groundwater modeling, to identify the timing of groundwater recovery and potential pathways for groundwater transport of metals that may be leached from stored CCBs and reach hydrologic receptors after operations cease. Data collected for the hydrologic assessment indicate that groundwater in at least one centrally located reclaimed surface-mining pit has already begun to recover.
The U.S. Geological Survey numerical modeling package MODFLOW–NWT was used with MODPATH particle-tracking software to identify advective flow paths from CCB storage areas toward potential hydrologic receptors. Results indicate that groundwater at CCB storage areas will recover to the former steady state, or in some locations, groundwater may recover to a new steady state in 6,600 to 10,600 years at variable rates depending on the proximity to a residual cone-of-groundwater depression caused by mine dewatering and regional oil and gas pumping as well as on actual, rather than estimated, groundwater recharge and evapotranspirational losses. Advective particle-track modeling indicates that the number of particles and rates of advective transport will vary depending on hydraulic properties of the mine spoil, particularly hydraulic conductivity and porosity. Modeling results from the most conservative scenario indicate that particles can migrate from CCB repositories to either the Shumway Arroyo alluvium after 1,320 years and from there to the San Juan River alluvium after 1,520 years or from southernmost CCB repositories directly to the San Juan River alluvium after 2,400 years after the cessation of mining.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175155","collaboration":"Prepared in cooperation with the Mining and Minerals Division of the State of New Mexico Energy, Minerals and Natural Resources Department","usgsCitation":"Stewart, A.M., 2018, Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13: U.S. Geological Survey Scientific Investigations Report 2017–5155, 94 p., https://doi.org/10.3133/sir20175155.","productDescription":"Report: xi, 94 p.; Data Releases","numberOfPages":"110","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080017","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":352877,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q81BJK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Chemical analyses for arsenic, calcium, chloride, sodium, sulfate, sulfide and dissolved solids, August 2011 through December 2013, from groundwater sampled at or in the vicinity of the San Juan Coal Mine, New Mexico"},{"id":353249,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75719JV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW–NWT and MODPATH5 models used to identify potential flow paths from San Juan Mine to hydrologic receptors, San Juan County, New Mexico"},{"id":352876,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5155/sir20175155.pdf","text":"Report","size":"6.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5155"},{"id":352875,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5155/coverthb.jpg"}],"country":"United States","state":"New Mexico","county":"San Juan County","otherGeospatial":"San Juan Mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 36.7167\n ],\n [\n -108.1,\n 36.72099868793134\n ],\n [\n -108.1,\n 37\n ],\n [\n -108.5,\n 37\n ],\n [\n -108.5,\n 36.7167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, NM 87113
In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017MS001209","usgsCitation":"Zhao, M., Golaz, J., Held, I.M., Guo, H., Balaji, V., Benson, R., Chen, J., Chen, X., Donner, L.J., Dunne, J.P., Dunne, K.A., Durachta, J., Fan, S., Freidenreich, S., Garner, S.T., Ginoux, P., Harris, L.M., Horowitz, L.W., Krasting, J., Langenhorst, A.R., Liang, Z., Lin, P., Lin, S., Malyshev, S., Mason, E., Milly, P., Ming, Y., Naik, V., Paulot, F., Paynter, D., Phillipps, P., Radhakrishnan, A., Ramaswamy, V., Robinson, T., Schwarzkopf, D., Seman, C., Shevliakova, E., Shen, Z., Shin, H., Silvers, L., Wilson, J.R., Winton, M., Wittenberg, A.T., Wyman, B., and Xiang, B., 2018, The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies: Journal of Advances in Modeling Earth Systems, v. 10, no. 3, p. 691-734, https://doi.org/10.1002/2017MS001209.","productDescription":"44 p.","startPage":"691","endPage":"734","ipdsId":"IP-090445","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468856,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ms001209","text":"Publisher Index Page"},{"id":353087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf49","contributors":{"authors":[{"text":"Zhao, M.","contributorId":203806,"corporation":false,"usgs":false,"family":"Zhao","given":"M.","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":732431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golaz, J.-C.","contributorId":203807,"corporation":false,"usgs":false,"family":"Golaz","given":"J.-C.","email":"","affiliations":[{"id":36725,"text":"GFDL/NOAA; Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":732432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Held, I. 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Coherence among these factors induces covariance among physical and biological processes across adjacent marine and terrestrial ecosystems. Here, we show that over the past century the degree and spatial extent of this covariance (synchrony) has substantially increased, and is coincident with rising variance in the winter NPH. Furthermore, centuries‐long blue oak (Quercus douglasii) growth chronologies sensitive to the winter NPH provide robust evidence that modern levels of synchrony are among the highest observed in the context of the last 250 years. These trends may ultimately be linked to changing impacts of the El Niño Southern Oscillation on mid‐latitude ecosystems of North America. Such a rise in synchrony may destabilize ecosystems, expose populations to higher risks of extinction, and is thus a concern given the broad biological relevance of winter climate to biological systems.
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