The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.
","language":"English","publisher":"Elsevier Science","doi":"10.1016/j.aeolia.2016.05.005","usgsCitation":"Webb, N., Herrick, J.E., Van Zee, J., Courtright, E., Hugenholtz, T.M., Zobeck, T.M., Okin, G.S., Barchyn, T.E., Billings, B., Boyd, R., Clingan, S.D., Cooper, B.F., Duniway, M.C., Derner, J.D., Fox, F.A., Havstad, K.M., Heilman, P., LaPlante, V., Ludwig, N.A., Metz, L.J., Nearing, M.A., Norfleet, M.L., Pierson, F., Sanderson, M.A., Sharrat, B.S., Steiner, J., Tatarko, J., Tedela, N., Todelo, D., Unnasch, R.S., Van Pelt, R., and Wagner, L., 2016, The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management: Aeolian Research, v. 22, p. 23-36, https://doi.org/10.1016/j.aeolia.2016.05.005.","productDescription":"14 p.","startPage":"23","endPage":"36","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074550","costCenters":[{"id":568,"text":"Southwest Biological Science 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\n2. In this study, we compare the reactivity of a new anti-passerine IgY secondary antibody with existing secondary antibodies developed for use with birds. Samples from 41 species from the following six avian orders were analysed: Anseriformes (1 family, 1 species), Columbiformes (1 family, 2 species), Galliformes (1 family, 1 species), Passeriformes (16 families, 34 species), Piciformes (1 family, 2 species) and Suliformes (1 family, 1 species). Direct ELISAs were performed to detect total IgY using goat anti-passerine IgY, goat anti-chicken IgY or goat anti-bird IgY secondary antibodies.
\n3.The anti-passerine antibody exhibited significantly higher IgY reactivity compared to the anti-chicken and/or anti-bird antibodies in 80% of the passerine families tested. Birds in the order Piciformes (woodpeckers) and order Suliformes (cormorants) were poorly detected by all three secondary antibodies. A comparison of serum and plasma IgY levels was made within the same individuals for two passerine species (house finch and white-crowned sparrow), and serum exhibited significantly more IgY than the plasma for all three secondary antibodies. This result indicates that serum may be preferred to plasma when measuring total antibody levels in blood.
\n4.This study indicates that the anti-passerine IgY secondary antibody can effectively be used in immunological assays to detect passerine IgY for species in most passerine families and is preferred over anti-chicken and anti-bird secondary antibodies for the majority of passerine species. This anti-passerine antibody will allow for more accurate detection and quantification of IgY in more wild bird species than was possible with previously available secondary antibodies.
","language":"English","publisher":"John Wiley","doi":"10.1111/2041-210X.12583","usgsCitation":"Fassbinder-Orth, C.A., Wilcoxen, T.E., Tran, T., Boughton, R.K., Fair, J.M., Hofmeister, E.K., Grindstaff, J.L., and Owen, J.C., 2016, Immunoglobulin detection in wild birds: Effectiveness of three secondary anti-avian IgY antibodies in direct ELISAs in 41 avian species: Methods in Ecology and Evolution, v. 7, no. 10, p. 1174-1181, https://doi.org/10.1111/2041-210X.12583.","productDescription":"8 p.","startPage":"1174","endPage":"1181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074662","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":470958,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5084450","text":"Publisher Index Page"},{"id":330424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"10","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-28","publicationStatus":"PW","scienceBaseUri":"5811c0f2e4b0f497e79a5a6d","contributors":{"authors":[{"text":"Fassbinder-Orth, Carol A.","contributorId":176331,"corporation":false,"usgs":false,"family":"Fassbinder-Orth","given":"Carol","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilcoxen, Travis E.","contributorId":176332,"corporation":false,"usgs":false,"family":"Wilcoxen","given":"Travis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":652230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tran, Tiffany","contributorId":176333,"corporation":false,"usgs":false,"family":"Tran","given":"Tiffany","email":"","affiliations":[],"preferred":false,"id":652231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boughton, Raoul K.","contributorId":176334,"corporation":false,"usgs":false,"family":"Boughton","given":"Raoul","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":652232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fair, Jeanne M.","contributorId":176335,"corporation":false,"usgs":false,"family":"Fair","given":"Jeanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":652228,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grindstaff, Jennifer L.","contributorId":176336,"corporation":false,"usgs":false,"family":"Grindstaff","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":652234,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Owen, Jen C.","contributorId":176337,"corporation":false,"usgs":false,"family":"Owen","given":"Jen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":652235,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70171554,"text":"70171554 - 2016 - Evaluation of Yersinia pestis transmission pathways for sylvatic plague in prairie dog populations in the western U.S.","interactions":[],"lastModifiedDate":"2018-01-04T15:42:43","indexId":"70171554","displayToPublicDate":"2016-05-27T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Yersinia pestis transmission pathways for sylvatic plague in prairie dog populations in the western U.S.","docAbstract":"Sylvatic plague, caused by the bacterium Yersinia pestis, is periodically responsible for large die-offs in rodent populations that can spillover and cause human mortalities. In the western US, prairie dog populations experience nearly 100% mortality during plague outbreaks, suggesting that multiple transmission pathways combine to amplify plague dynamics. Several alternate pathways in addition to flea vectors have been proposed, such as transmission via direct contact with bodily fluids or inhalation of infectious droplets, consumption of carcasses, and environmental sources of plague bacteria, such as contaminated soil. However, evidence supporting the ability of these proposed alternate pathways to trigger large-scale epizootics remains elusive. Here we present a short review of potential plague transmission pathways and use an ordinary differential equation model to assess the contribution of each pathway to resulting plague dynamics in black-tailed prairie dogs (Cynomys ludovicianus) and their fleas (Oropsylla hirsuta). Using our model, we found little evidence to suggest that soil contamination was capable of producing plague epizootics in prairie dogs. However, in the absence of flea transmission, direct transmission, i.e., contact with bodily fluids or inhalation of infectious droplets, could produce enzootic dynamics, and transmission via contact with or consumption of carcasses could produce epizootics. This suggests that these pathways warrant further investigation.
","language":"English","publisher":"SpringerLink","doi":"10.1007/s10393-016-1133-9","usgsCitation":"Richgels, K., Russell, R.E., Bron, G., and Rocke, T.E., 2016, Evaluation of Yersinia pestis transmission pathways for sylvatic plague in prairie dog populations in the western U.S.: EcoHealth, v. 13, no. 2, p. 415-427, https://doi.org/10.1007/s10393-016-1133-9.","productDescription":"13 p.","startPage":"415","endPage":"427","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072057","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":500062,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/evaluation-of-yersinia-pestis-transmission-pathways-for-sylvatic-","text":"External Repository"},{"id":322145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, 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D. 0000-0003-2834-9477","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":170005,"corporation":false,"usgs":false,"family":"Richgels","given":"Katherine L. D.","affiliations":[{"id":25647,"text":"University of Wisconsin - Madison, School of Veterinary Medicine, Department of 4 Pathobiological Sciences","active":true,"usgs":false}],"preferred":false,"id":631763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":631762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bron, Gebbiena","contributorId":170006,"corporation":false,"usgs":false,"family":"Bron","given":"Gebbiena","affiliations":[{"id":25647,"text":"University of Wisconsin - Madison, School of Veterinary Medicine, Department of 4 Pathobiological Sciences","active":true,"usgs":false}],"preferred":false,"id":631764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":631765,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171171,"text":"ofr20161087 - 2016 - Mortality monitoring design for utility-scale solar power facilities","interactions":[],"lastModifiedDate":"2017-11-22T15:52:36","indexId":"ofr20161087","displayToPublicDate":"2016-05-27T13:00:00","publicationYear":"2016","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":"2016-1087","title":"Mortality monitoring design for utility-scale solar power facilities","docAbstract":"Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015).
In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site.
We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161087","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Huso, Manuela, Dietsch, Thomas, and Nicolai, Chris, 2016, Mortality monitoring design for utility-scale solar power facilities: U.S. Geological Survey Open-File Report 2016-1087, 44 p., https://dx.doi.org/10.3133/ofr20161087.","productDescription":"vi, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073911","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1087/ofr20161087.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1087 Report PDF"},{"id":321632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1087/coverthb.jpg"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The California horn snail, Cerithideopsis californica, and the shore crabs, Pachygrapsus crassipesand Hemigrapsus oregonensis, compete for epibenthic microalgae, but the crabs also eat snails. Such intraguild predation is common in nature, despite models predicting instability. Using a series of manipulations and field surveys, we examined intraguild predation from several angles, including the effects of stage-dependent predation along with direct consumptive and nonconsumptive predator effects on intraguild prey. In the laboratory, we found that crabs fed on macroalgae, snail eggs, and snails, and the size of consumed snails increased with predator crab size. In field experiments, snails grew less in the presence of crabs partially because snails behaved differently and were buried in the sediment (nonconsumptive effects). Consistent with these results, crab and snail abundances were negatively correlated in three field surveys conducted at three different spatial scales in estuaries of California, Baja California, and Baja California Sur: (1) among 61 sites spanning multiple habitat types in three estuaries, (2) among the habitats of 13 estuaries, and (3) among 34 tidal creek sites in one estuary. These results indicate that shore crabs are intraguild predators on California horn snails that affect snail populations via predation and by influencing snail behavior and performance.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1262","usgsCitation":"Lorda, J., Hechinger, R.F., Cooper, S., Kuris, A., and Lafferty, K.D., 2016, Intraguild predation by shore crabs affects mortality, behavior, growth, and densities of California horn snails: Ecosphere, v. 7, no. 5, e01262; 17 p., https://doi.org/10.1002/ecs2.1262.","productDescription":"e01262; 17 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069609","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470961,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1262","text":"Publisher Index Page"},{"id":321827,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-25","publicationStatus":"PW","scienceBaseUri":"5749619ce4b07e28b6650f9e","contributors":{"authors":[{"text":"Lorda, J.","contributorId":74717,"corporation":false,"usgs":true,"family":"Lorda","given":"J.","affiliations":[],"preferred":false,"id":630603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hechinger, R. F.","contributorId":83864,"corporation":false,"usgs":false,"family":"Hechinger","given":"R.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":630604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, S. D.","contributorId":169662,"corporation":false,"usgs":false,"family":"Cooper","given":"S. D.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":630605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuris, A. M.","contributorId":101203,"corporation":false,"usgs":true,"family":"Kuris","given":"A. M.","affiliations":[],"preferred":false,"id":630606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":630602,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171267,"text":"70171267 - 2016 - Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region","interactions":[],"lastModifiedDate":"2016-06-01T16:49:25","indexId":"70171267","displayToPublicDate":"2016-05-27T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region","docAbstract":"The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological knowledge with species distribution modeling for early detection and targeted surveying of recently established invasive species.
","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ES-07988-210122","usgsCitation":"Luizza, M., Wakie, T., Evangelista, P., and Jarnevich, C.S., 2016, Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine (Cryptostegia grandiflora) in Ethiopia’s Afar region: Ecology and Society, v. 21, no. 1, Art. 22; 22 p,, https://doi.org/10.5751/ES-07988-210122.","productDescription":"Art. 22; 22 p,","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062006","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470963,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-07988-210122","text":"Publisher Index Page"},{"id":321817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ethiopia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 39.781494140625,\n 8.86336203355168\n ],\n [\n 39.781494140625,\n 10.055402736564224\n ],\n [\n 40.9185791015625,\n 10.055402736564224\n ],\n [\n 40.9185791015625,\n 8.86336203355168\n ],\n [\n 39.781494140625,\n 8.86336203355168\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5749619ce4b07e28b6650f9a","contributors":{"authors":[{"text":"Luizza, Matthew","contributorId":169629,"corporation":false,"usgs":false,"family":"Luizza","given":"Matthew","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":630371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wakie, Tewodros","contributorId":138730,"corporation":false,"usgs":false,"family":"Wakie","given":"Tewodros","email":"","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":630372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evangelista, Paul","contributorId":46371,"corporation":false,"usgs":true,"family":"Evangelista","given":"Paul","affiliations":[],"preferred":false,"id":630373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":630370,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171361,"text":"70171361 - 2016 - Cyanotoxins in inland lakes of the United States: Occurrence and potential recreational health risks in the EPA National Lakes Assessment 2007","interactions":[],"lastModifiedDate":"2018-08-07T12:33:30","indexId":"70171361","displayToPublicDate":"2016-05-26T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Cyanotoxins in inland lakes of the United States: Occurrence and potential recreational health risks in the EPA National Lakes Assessment 2007","docAbstract":"A large nation-wide survey of cyanotoxins (1161 lakes) in the United States (U.S.) was conducted during the EPA National Lakes Assessment 2007. Cyanotoxin data were compared with cyanobacteria abundance- and chlorophyll-based World Health Organization (WHO) thresholds and mouse toxicity data to evaluate potential recreational risks. Cylindrospermopsins, microcystins, and saxitoxins were detected (ELISA) in 4.0, 32, and 7.7% of samples with mean concentrations of 0.56, 3.0, and 0.061 mg/L, respectively (detections only). Co-occurrence of the three cyanotoxin classes was rare (0.32%) when at least one toxin was detected. Cyanobacteria were present and dominant in 98 and 76% of samples, respectively. Potential anatoxin-, cylindrospermopsin-, microcystin-, and saxitoxin-producing cyanobacteria occurred in 81, 67, 95, and 79% of samples, respectively. Anatoxin-a and nodularin-R were detected (LC/MS/MS) in 15 and 3.7% samples (n = 27). The WHO moderate and high risk thresholds for microcystins, cyanobacteria abundance, and total chlorophyll were exceeded in 1.1, 27, and 44% of samples, respectively. Complete agreement by all three WHO microcystin metrics occurred in 27% of samples. This suggests that WHO microcystin metrics based on total chlorophyll and cyanobacterial abundance can overestimate microcystin risk when compared to WHO microcystin thresholds. The lack of parity among the WHO thresholds was expected since chlorophyll is common amongst all phytoplankton and not all cyanobacteria produce microcystins.
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Center","active":false,"usgs":true}],"preferred":true,"id":630714,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dietze, Julie E. 0000-0002-5936-5739 juliec@usgs.gov","orcid":"https://orcid.org/0000-0002-5936-5739","contributorId":3939,"corporation":false,"usgs":true,"family":"Dietze","given":"Julie","email":"juliec@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":630715,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffith, Christopher cgriffith@usgs.gov","contributorId":169687,"corporation":false,"usgs":true,"family":"Griffith","given":"Christopher","email":"cgriffith@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":630716,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170898,"text":"sir20165058 - 2016 - Potential effects of sea-level rise on the depth to saturated sediments of the Sagamore and Monomoy flow lenses on Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2018-05-17T13:23:29","indexId":"sir20165058","displayToPublicDate":"2016-05-25T14:00:00","publicationYear":"2016","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":"2016-5058","title":"Potential effects of sea-level rise on the depth to saturated sediments of the Sagamore and Monomoy flow lenses on Cape Cod, Massachusetts","docAbstract":"In 2014, the U.S. Geological Survey, in cooperation with the Association to Preserve Cape Cod, the Cape Cod Commission, and the Massachusetts Environmental Trust, began an evaluation of the potential effects of sea-level rise on water table altitudes and depths to water on central and western Cape Cod, Massachusetts. Increases in atmospheric and oceanic temperatures arising, in part, from the release of greenhouse gases likely will result in higher sea levels globally. Increasing water table altitudes in shallow, unconfined coastal aquifer systems could adversely affect infrastructure—roads, utilities, basements, and septic systems—particularly in low-lying urbanized areas. The Sagamore and Monomoy flow lenses on Cape Cod are the largest and most populous of the six flow lenses that comprise the region’s aquifer system, the Cape Cod glacial aquifer. The potential effects of sea-level rise on water table altitude and depths to water were evaluated by use of numerical models of the region. The Sagamore and Monomoy flow lenses have a number of large surface water drainages that receive a substantial amount of groundwater discharge, 47 and 29 percent of the total, respectively. The median increase in the simulated water table altitude following a 6-foot sea-level rise across both flow lenses was 2.11 feet, or 35 percent when expressed as a percentage of the total sea-level rise. The response is nearly the same as the sea-level rise (6 feet) in some coastal areas and less than 0.1 foot near some large inland streams. Median water table responses differ substantially between the Sagamore and Monomoy flow lenses—at 29 and 49 percent, respectively—because larger surface water discharge on the Sagamore flow lens results in increased dampening of the water table response than in the Monomoy flow lens. Surface waters dampen water table altitude increases because streams are fixed-altitude boundaries that cause hydraulic gradients and streamflow to increase as sea-level rises, partially fixing the local water table altitude.
The region has a generally thick vadose zone with a mean of about 38 feet; areas with depths to water of 5 feet or less, as estimated from light detection and ranging (lidar) data from 2011 and simulated water table altitudes, currently [2011] occur over about 24.9 square miles, or about 8.4 percent of the total land area of the Sagamore and Monomoy flow lenses, generally in low-lying coastal areas and inland near ponds and streams. Excluding potentially submerged areas, an additional 4.5, 9.8, and 15.9 square miles would have shallow depths to water (5 feet or less) for projected sea-level rises of 2, 4, and 6 feet above levels in 2011. The additional areas with shallow depths to water generally occur in the same areas as the areas with current [2011] depths to water of 5 feet or less: low-lying coastal areas and near inland surface water features. Additional areas with shallow depths to water for the largest sea-level rise prediction (6 feet) account for about 5.7 percent of the total land area, excluding areas likely to be inundated by seawater. The numerous surface water drainages will dampen the response of the water table to sea-level rise. This dampening, combined with the region’s thick vadose zone, likely will mitigate the potential for groundwater inundation in most areas. The potential does exist for groundwater inundation in some areas, but the effects of sea-level rise on depths to water and infrastructure likely will not be substantial on a regional level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165058","collaboration":"Prepared in cooperation with the Association to Preserve Cape Cod, the Cape Cod Commission, and the Massachusetts Environmental Trust","usgsCitation":"Walter, D.A., McCobb, T.D., Masterson, J.P., and Fienen, M.N., 2016, Potential effects of sea-level rise on the depth to saturated sediments of the Sagamore and Monomoy flow lenses on Cape Cod, Massachusetts (ver. 1.1, October 18, 2016): U.S. Geological Survey Scientific Investigations Report 2016–5058, 55 p., https://dx.doi.org/10.3133/sir20165058.","productDescription":"vi, 55 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071028","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":321216,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5058/sir20165058.pdf","text":"Report","size":"19.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5058"},{"id":321215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5058/coverthb2.jpg"},{"id":329663,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5058/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.69427490234375,\n 41.509605687197975\n ],\n [\n -70.69427490234375,\n 42.10943017110108\n ],\n [\n -69.90463256835938,\n 42.10943017110108\n ],\n [\n -69.90463256835938,\n 41.509605687197975\n ],\n [\n -70.69427490234375,\n 41.509605687197975\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted May 25, 2016; Version 1.1: October 25,2016","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at
http://newengland.water.usgs.gov/
Efforts to improve fish passage have resulted in the replacement of six culverts in Crystal Springs Creek in Portland, Oregon. Two more culverts are scheduled to be replaced at Glenwood Street and Bybee Boulevard (Glenwood/Bybee project) in 2016. Recently acquired data have allowed for a more comprehensive understanding of the hydrology of the creek and the topography of the watershed. To evaluate the impact of the culvert replacements and recent hydrologic data, a Hydrologic Engineering Center-River Analysis System hydraulic model was developed to estimate water-surface elevations during high-flow events. Longitudinal surface-water profiles were modeled to evaluate current conditions and future conditions using the design plans for the culverts to be installed in 2016. Additional profiles were created to compare with the results from the most recent flood model approved by the Federal Emergency Management Agency for Crystal Springs Creek and to evaluate model sensitivity.
Model simulation results show that water-surface elevations during high-flow events will be lower than estimates from previous models, primarily due to lower estimates of streamflow associated with the 0.01 and 0.002 annual exceedance probability (AEP) events. Additionally, recent culvert replacements have resulted in less ponding behind crossings. Similarly, model simulation results show that the proposed replacement culverts at Glenwood Street and Bybee Boulevard will result in lower water-surface elevations during high-flow events upstream of the proposed project. Wider culverts will allow more water to pass through crossings, resulting in slightly higher water-surface elevations downstream of the project during high-flows than water-surface elevations that would occur under current conditions. For the 0.01 AEP event, the water-surface elevations downstream of the Glenwood/Bybee project will be an average of 0.05 ft and a maximum of 0.07 ft higher than current conditions. Similarly, for the 0.002 AEP event, the water-surface elevations will be an average of 0.04 ft and a maximum of 0.19 ft higher than current conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161079","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, Adam, and Hess, Glen, 2016, Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon: U.S. Geological Survey Open-File Report 2016-1079, 33 p., https://dx.doi.org/10.3133/ofr20161079.","productDescription":"Report: iv, 33 p.; Plate: 24.00 x 36.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052885","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Report PDF"},{"id":321612,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079_plate1.pdf","text":"Plate 1","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Plate 1 PDF"},{"id":321610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1079/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62,\n 45.45\n ],\n [\n -122.62,\n 45.5\n ],\n [\n -122.65,\n 45.5\n ],\n [\n -122.65,\n 45.45\n ],\n [\n -122.62,\n 45.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Managing widespread and persistent threats to birds requires knowledge of population dynamics at large spatial and temporal scales. For over 100 yrs, the Audubon Christmas Bird Count (CBC) has enlisted volunteers in bird monitoring efforts that span the Americas, especially southern Canada and the United States. We employed a Bayesian hierarchical model to control for variation in survey effort among CBC circles and, using CBC data from 1966 to 2013, generated early-winter population trend estimates for 551 species of birds. Selecting a subset of species that do not frequent bird feeders and have ≥25% range overlap with the distribution of CBC circles (228 species) we further estimated aggregate (i.e., across species) trends for the entire study region and at the level of states/provinces, Bird Conservation Regions, and Landscape Conservation Cooperatives. Moreover, we examined the relationship between ten biological traits—range size, population size, migratory strategy, habitat affiliation, body size, diet, number of eggs per clutch, age at sexual maturity, lifespan, and tolerance of urban/suburban settings—and CBC trend estimates. Our results indicate that 68% of the 551 species had increasing trends within the study area over the interval 1966–2013. When trends were examined across the subset of 228 species, the median population trend for the group was 0.9% per year at the continental level. At the regional level, aggregate trends were positive in all but a few areas. Negative population trends were evident in lower latitudes, whereas the largest increases were at higher latitudes, a pattern consistent with range shifts due to climate change. Nine of 10 biological traits were significantly associated with median population trend; however, none of the traits explained >34% of the deviance in the data, reflecting the indirect relationships between population trend estimates and species traits. Trend estimates based on the CBC are broadly congruent with estimates based on the North American Breeding Bird Survey, another large-scale monitoring program. Both of these efforts, conducted by citizen scientists, will be required going forward to ensure robust inference about population dynamics in the face of climate and land cover changes.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1351","usgsCitation":"Soykan, C.U., Sauer, J.R., Schuetz, J.G., LeBaron, G.S., Dale, K., and Langham, G.M., 2016, Population trends for North American winter birds based on hierarchical models: Ecosphere, v. 7, no. 5, Article e01351; 16 p., https://doi.org/10.1002/ecs2.1351.","productDescription":"Article e01351; 16 p.","ipdsId":"IP-068486","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1351","text":"Publisher Index Page"},{"id":331648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"58492df4e4b06d80b7b093ac","contributors":{"authors":[{"text":"Soykan, Candan U.","contributorId":177253,"corporation":false,"usgs":false,"family":"Soykan","given":"Candan","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":655134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":655133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuetz, Justin G.","contributorId":177254,"corporation":false,"usgs":false,"family":"Schuetz","given":"Justin","email":"","middleInitial":"G.","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":655135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeBaron, Geoffrey S.","contributorId":177255,"corporation":false,"usgs":false,"family":"LeBaron","given":"Geoffrey","email":"","middleInitial":"S.","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":655136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dale, Kathy","contributorId":177256,"corporation":false,"usgs":false,"family":"Dale","given":"Kathy","email":"","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":655137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langham, Gary M.","contributorId":177257,"corporation":false,"usgs":false,"family":"Langham","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":655138,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176147,"text":"70176147 - 2016 - End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology","interactions":[],"lastModifiedDate":"2016-08-30T14:18:01","indexId":"70176147","displayToPublicDate":"2016-05-23T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology","docAbstract":"The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s00338-016-1462-8","usgsCitation":"Storlazzi, C.D., Dartnell, P., Hatcher, G., and Gibbs, A.E., 2016, End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology: Coral Reefs, v. 35, no. 3, p. 889-894, https://doi.org/10.1007/s00338-016-1462-8.","productDescription":"5 p.","startPage":"889","endPage":"894","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069114","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-23","publicationStatus":"PW","scienceBaseUri":"57c6af43e4b0f2f0cebe4ae0","chorus":{"doi":"10.1007/s00338-016-1462-8","url":"http://dx.doi.org/10.1007/s00338-016-1462-8","publisher":"Springer Nature","authors":"Storlazzi Curt D., Dartnell Peter, Hatcher Gerald A., Gibbs Ann E.","journalName":"Coral Reefs","publicationDate":"5/23/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"5/23/2016"},"contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":647474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatcher, Gerry ghatcher@usgs.gov","contributorId":3556,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerry","email":"ghatcher@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174991,"text":"70174991 - 2016 - Methane and sulfate dynamics in sediments from mangrove-dominated tropical coastal lagoons, Yucatan, Mexico","interactions":[],"lastModifiedDate":"2016-07-27T12:08:16","indexId":"70174991","displayToPublicDate":"2016-05-23T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Methane and sulfate dynamics in sediments from mangrove-dominated tropical coastal lagoons, Yucatan, Mexico","docAbstract":"Porewater profiles in sediment cores from mangrove-dominated coastal lagoons (Celestún and Chelem) on the Yucatán Peninsula, Mexico, reveal the widespread coexistence of dissolved methane and sulfate. This observation is interesting since dissolved methane in porewaters is typically oxidized anaerobically by sulfate. To explain the observations we used a numerical transport-reaction model that was constrained by the field observations. The model suggests that methane in the upper sediments is produced in the sulfate reduction zone at rates ranging between 0.012 and 31 mmol m−2 d−1, concurrent with sulfate reduction rates between 1.1 and 24 mmol SO42− m−2 d−1. These processes are supported by high organic matter content in the sediment and the use of non-competitive substrates by methanogenic microorganisms. Indeed sediment slurry incubation experiments show that non-competitive substrates such as trimethylamine (TMA) and methanol can be utilized for microbial methanogenesis at the study sites. The model also indicates that a significant fraction of methane is transported to the sulfate reduction zone from deeper zones within the sedimentary column by rising bubbles and gas dissolution. The shallow depths of methane production and the fast rising methane gas bubbles reduce the likelihood for oxidation, thereby allowing a large fraction of the methane formed in the sediments to escape to the overlying water column.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-13-2981-2016","usgsCitation":"Chuang, P.C., Young, M.B., Dale, A.W., Miller, L., Herrera-Silveira, J.A., and Paytan, A., 2016, Methane and sulfate dynamics in sediments from mangrove-dominated tropical coastal lagoons, Yucatan, Mexico: Biogeosciences, v. 13, no. 10, p. 2981-3001, https://doi.org/10.5194/bg-13-2981-2016.","productDescription":"20 p.","startPage":"2981","endPage":"3001","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075714","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470968,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-13-2981-2016","text":"Publisher Index Page"},{"id":325700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Yucatan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.5390625,\n 21.524627220545295\n ],\n [\n -87.989501953125,\n 21.69826549685252\n ],\n [\n -88.363037109375,\n 21.667638606781576\n ],\n [\n -88.670654296875,\n 21.57571893245848\n ],\n [\n -89.219970703125,\n 21.442843107187667\n ],\n [\n -90.06591796875,\n 21.299610604945617\n ],\n [\n -90.5712890625,\n 20.86907773201848\n ],\n [\n -90.46142578125,\n 20.704738720055524\n ],\n [\n -90.28564453124999,\n 20.540221355754728\n ],\n [\n -90.120849609375,\n 20.396123272467616\n ],\n [\n -90.04394531249999,\n 20.437307950568957\n ],\n [\n -89.80224609374999,\n 20.107523268824004\n ],\n [\n -89.74731445312499,\n 20.128155311797183\n ],\n [\n -89.6044921875,\n 19.9010536062052\n ],\n [\n -89.395751953125,\n 19.559790136497398\n ],\n [\n -89.18701171875,\n 19.487307518564272\n ],\n [\n -88.912353515625,\n 19.72534224805787\n ],\n [\n -88.70361328125,\n 20.024967917222785\n ],\n [\n -88.35205078124999,\n 20.138470312451155\n ],\n [\n -88.033447265625,\n 20.2725032501349\n ],\n [\n -87.879638671875,\n 20.478481600090568\n ],\n [\n -87.725830078125,\n 20.601936194281016\n ],\n [\n -87.51708984375,\n 20.838277806058933\n ],\n [\n -87.462158203125,\n 21.08450008351735\n ],\n [\n -87.47314453125,\n 21.4121622297254\n ],\n [\n -87.5390625,\n 21.524627220545295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-23","publicationStatus":"PW","scienceBaseUri":"5799db5be4b0589fa1c7e94f","contributors":{"authors":[{"text":"Chuang, P. C.","contributorId":173167,"corporation":false,"usgs":false,"family":"Chuang","given":"P.","email":"","middleInitial":"C.","affiliations":[{"id":27170,"text":"Department of Earth and Planetary Sciences, University of California Santa Cruz, 1156 High St., Santa Cruz, CA 95064, United States","active":true,"usgs":false}],"preferred":false,"id":643518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Megan B. 0000-0002-0229-4108 mbyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-0229-4108","contributorId":3315,"corporation":false,"usgs":true,"family":"Young","given":"Megan","email":"mbyoung@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dale, Andrew W.","contributorId":173168,"corporation":false,"usgs":false,"family":"Dale","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":27171,"text":"GEOMAR Helmholtz Centre for Ocean Research Kiel, Wischhofstr. 1–3, 24148 Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":643522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Laurence G. 0000-0002-7807-3475 lgmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-7807-3475","contributorId":2460,"corporation":false,"usgs":true,"family":"Miller","given":"Laurence G.","email":"lgmiller@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herrera-Silveira, Jorge A.","contributorId":112572,"corporation":false,"usgs":true,"family":"Herrera-Silveira","given":"Jorge","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paytan, Adina","contributorId":75242,"corporation":false,"usgs":true,"family":"Paytan","given":"Adina","affiliations":[],"preferred":false,"id":643521,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171124,"text":"70171124 - 2016 - Observations of wave transformation over a fringing coral reef and the importance of low-frequency waves and offshore water levels to runup, overwash, and coastal flooding","interactions":[],"lastModifiedDate":"2016-06-24T11:34:56","indexId":"70171124","displayToPublicDate":"2016-05-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Observations of wave transformation over a fringing coral reef and the importance of low-frequency waves and offshore water levels to runup, overwash, and coastal flooding","docAbstract":"Many low-lying tropical islands are susceptible to sea level rise and often subjected to overwash and flooding during large wave events. To quantify wave dynamics and wave-driven water levels on fringing coral reefs, a 5 month deployment of wave gauges and a current meter was conducted across two shore-normal transects on Roi-Namur Island in the Republic of the Marshall Islands. These observations captured two large wave events that had waves with maximum heights greater than 6 m with peak periods of 16 s over the fore reef. The larger event coincided with a peak spring tide, leading to energetic, highly skewed infragravity (0.04–0.004 Hz) and very low frequency (0.004–0.001 Hz) waves at the shoreline, which reached heights of 1.0 and 0.7 m, respectively. Water surface elevations, combined with wave runup, reached 3.7 m above the reef bed at the innermost reef flat adjacent to the toe of the beach, resulting in flooding of inland areas. This overwash occurred during a 3 h time window that coincided with high tide and maximum low-frequency reef flat wave heights. The relatively low-relief characteristics of this narrow reef flat may further drive shoreline amplification of low-frequency waves due to resonance modes. These results (1) demonstrate how the coupling of high offshore water levels with low-frequency reef flat wave energetics can lead to large impacts along fringing reef-lined shorelines, such as island overwash, and (2) lend support to the hypothesis that predicted higher sea levels will lead to more frequent occurrences of these extreme events, negatively impacting coastal resources and infrastructure.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JC011231","usgsCitation":"Cheriton, O., Storlazzi, C.D., and Rosenberger, K.J., 2016, Observations of wave transformation over a fringing coral reef and the importance of low-frequency waves and offshore water levels to runup, overwash, and coastal flooding: Journal of Geophysical Research C: Oceans, v. 121, no. 5, p. 3121-3140, https://doi.org/10.1002/2015JC011231.","productDescription":"20 p.","startPage":"3121","endPage":"3140","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066923","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470970,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jc011231","text":"Publisher Index Page"},{"id":321486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"57441b9ce4b07e28b660dabc","contributors":{"authors":[{"text":"Cheriton, Olivia 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":149003,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629994,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170865,"text":"ofr20161046 - 2016 - Algorithms used in the Airborne Lidar Processing System (ALPS)","interactions":[],"lastModifiedDate":"2016-05-23T15:51:47","indexId":"ofr20161046","displayToPublicDate":"2016-05-23T10:45:00","publicationYear":"2016","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":"2016-1046","title":"Algorithms used in the Airborne Lidar Processing System (ALPS)","docAbstract":"The Airborne Lidar Processing System (ALPS) analyzes Experimental Advanced Airborne Research Lidar (EAARL) data—digitized laser-return waveforms, position, and attitude data—to derive point clouds of target surfaces. A full-waveform airborne lidar system, the EAARL seamlessly and simultaneously collects mixed environment data, including submerged, sub-aerial bare earth, and vegetation-covered topographies.
ALPS uses three waveform target-detection algorithms to determine target positions within a given waveform: centroid analysis, leading edge detection, and bottom detection using water-column backscatter modeling. The centroid analysis algorithm detects opaque hard surfaces. The leading edge algorithm detects topography beneath vegetation and shallow, submerged topography. The bottom detection algorithm uses water-column backscatter modeling for deeper submerged topography in turbid water.
The report describes slant range calculations and explains how ALPS uses laser range and orientation measurements to project measurement points into the Universal Transverse Mercator coordinate system. Parameters used for coordinate transformations in ALPS are described, as are Interactive Data Language-based methods for gridding EAARL point cloud data to derive digital elevation models. Noise reduction in point clouds through use of a random consensus filter is explained, and detailed pseudocode, mathematical equations, and Yorick source code accompany the report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161046","usgsCitation":"Nagle, David B., and Wright, C. Wayne, 2016, Algorithms used in the Airborne Lidar Processing System (ALPS):\nU.S. Geological Survey Open-File Report, 2016–1046, 45 p., https://dx.doi.org/10.3133/ofr20161046.","productDescription":"x, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063528","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321007,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1046/ofr20161046.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1046"},{"id":321006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1046/coverthb.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov/
Biocrusts exert a strong influence on hydrological processes in drylands by modifying numerous soil properties that affect water retention and movement in soils. Yet, their role in these processes is not clearly understood due to the large number of factors that act simultaneously and can mask the biocrust effect. The influence of biocrusts on soil hydrology depends on biocrust intrinsic characteristics such as cover, composition, and external morphology, which differ greatly among climate regimes, but also on external factors as soil type, topography and vegetation distribution patterns, as well as interactions among these factors. This chapter reviews the most recent literature published on the role of biocrusts in infiltration and runoff, soil moisture, evaporation and non-rainfall water inputs (fog, dew, water absorption), in an attempt to elucidate the key factors that explain how biocrusts affect land hydrology. In addition to the crust type and site characteristics, recent studies point to the crucial importance of the type of rainfall and the spatial scale at which biocrust effects are analyzed to understand their role in hydrological processes. Future studies need to consider the temporal and spatial scale investigated to obtain more accurate generalizations on the role of biocrusts in land hydrology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_17","usgsCitation":"Chamizo, S., Belnap, J., Elridge, D.J., and Issa, O., 2016, Biological soil crusts: An organizing principle in dryland ecosystems (aka: the role of biocrusts in arid land hydrology), chap. of Ecological studies, p. 321-346, https://doi.org/10.1007/978-3-319-30214-0_17.","productDescription":"26 p.","startPage":"321","endPage":"346","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070333","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8b0e4b04836416a0d2f","contributors":{"authors":[{"text":"Chamizo, Sonia 0000-0002-2980-1683","orcid":"https://orcid.org/0000-0002-2980-1683","contributorId":174264,"corporation":false,"usgs":false,"family":"Chamizo","given":"Sonia","email":"","affiliations":[{"id":27406,"text":"Department of Agronomy, University of Almeria, 04120 Almeria, Spain","active":true,"usgs":false}],"preferred":false,"id":647888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elridge, David J","contributorId":174265,"corporation":false,"usgs":false,"family":"Elridge","given":"David","email":"","middleInitial":"J","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":647889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Issa, Oumarou M","contributorId":174266,"corporation":false,"usgs":false,"family":"Issa","given":"Oumarou M","affiliations":[{"id":27408,"text":"URCA, GEGENAA EA 3795, 51100 Reims – France / UMR 242 IEES-Paris, IRD representation au Niger BP11416 Niamey, Niger","active":true,"usgs":false}],"preferred":false,"id":647890,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168430,"text":"70168430 - 2016 - Biocrusts in the context of global change","interactions":[],"lastModifiedDate":"2016-12-14T12:26:26","indexId":"70168430","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Biocrusts in the context of global change","docAbstract":"A wide range of studies show global environmental change will profoundly affect the structure, function, and dynamics of terrestrial ecosystems. The research synthesized here underscores that biocrust communities are also likely to respond significantly to global change drivers, with a large potential for modification to their abundance, composition, and function. We examine how elevated atmospheric CO2 concentrations, climate change (increased temperature and altered precipitation), and nitrogen deposition affect biocrusts and the ecosystems they inhabit. We integrate experimental and observational data, as well as physiological, community ecology, and biogeochemical perspectives. Taken together, these data highlight the potential for biocrust organisms to respond dramatically to environmental change and show how changes to biocrust community composition translate into effects on ecosystem function (e.g., carbon and nutrient cycling, soil stability, energy balance). Due to the importance of biocrusts in regulating dryland ecosystem processes and the potential for large modifications to biocrust communities, an improved understanding and predictive capacity regarding biocrust responses to environmental change are of scientific and societal relevance.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biological soil crusts: An organizing principle in drylands","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-30214-0_22","usgsCitation":"Reed, S.C., Maestre, F.T., Ochoa-Hueso, R., Kuske, C., Darrouzet-Nardi, A., Darby, B., Sinsabaugh, B., Oliver, M., Sancho, L., and Belnap, J., 2016, Biocrusts in the context of global change, chap. of Biological soil crusts: An organizing principle in drylands, p. 451-476, https://doi.org/10.1007/978-3-319-30214-0_22.","productDescription":"26 p. ","startPage":"451","endPage":"476","ipdsId":"IP-060490","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":332112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"585268e0e4b0e2663625ec84","contributors":{"authors":[{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":620065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maestre, Fernando T.","contributorId":62450,"corporation":false,"usgs":true,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":620066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ochoa-Hueso, Raul","contributorId":166773,"corporation":false,"usgs":false,"family":"Ochoa-Hueso","given":"Raul","email":"","affiliations":[{"id":24505,"text":"Hawkesbury Institute for the Environment, Penrith Australia 2751","active":true,"usgs":false}],"preferred":false,"id":620067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuske, Cheryl","contributorId":22262,"corporation":false,"usgs":true,"family":"Kuske","given":"Cheryl","affiliations":[],"preferred":false,"id":620068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Darrouzet-Nardi, Anthony N. adarrouzet-nardi@usgs.gov","contributorId":5766,"corporation":false,"usgs":true,"family":"Darrouzet-Nardi","given":"Anthony N.","email":"adarrouzet-nardi@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":620069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Darby, Brian","contributorId":166774,"corporation":false,"usgs":false,"family":"Darby","given":"Brian","email":"","affiliations":[{"id":24506,"text":"University of North Dakota, Grand Forks, ND USA 58202-9019","active":true,"usgs":false}],"preferred":false,"id":620070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sinsabaugh, Bob","contributorId":166775,"corporation":false,"usgs":false,"family":"Sinsabaugh","given":"Bob","email":"","affiliations":[{"id":24507,"text":"University of New Mexico, Albuquerque, NM USA 87131","active":true,"usgs":false}],"preferred":false,"id":620071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oliver, Mel","contributorId":166776,"corporation":false,"usgs":false,"family":"Oliver","given":"Mel","email":"","affiliations":[{"id":24508,"text":"USDA-ARS, University of Missouri, Columbia campus, Columbia, MO USA 65211","active":true,"usgs":false}],"preferred":false,"id":620072,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sancho, Leo","contributorId":166777,"corporation":false,"usgs":false,"family":"Sancho","given":"Leo","affiliations":[{"id":24509,"text":"Complutense University of Madrid, Madrid Spain","active":true,"usgs":false}],"preferred":false,"id":620073,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":620076,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70171126,"text":"ofr20161080 - 2016 - Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","interactions":[],"lastModifiedDate":"2016-06-23T16:23:54","indexId":"ofr20161080","displayToPublicDate":"2016-05-20T17:00:00","publicationYear":"2016","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":"2016-1080","title":"Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","docAbstract":"Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.
Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.
We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161080","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, California Department of Fish and Wildlife, and Idaho State University","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee B.E., Ricca, M.A., Gustafson, K.B., Sanchez-Chopitea, E., Mauch, K., Niell, L., Gardner, S., Espinosa, S., and Delehanty, D.J., 2016, Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management: U.S. Geological Survey Open-File Report 2016-1080, 160 p., https://dx.doi.org/10.3133/ofr20161080.","productDescription":"Report: viii, 160 p.; Dataset","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072897","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322138,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7CC0XRV","text":"USGS data release - Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Nevada and Northeastern California - an Updated Decision-Support Tool for Management"},{"id":321471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1080/coverthb.jpg"},{"id":321472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1080/ofr20161080.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1080 Report PDF"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.87158203125,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 37.50972584293751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068904","usgsCitation":"Brennan, S.R., Torgersen, C.E., Hollenbeck, J.P., Fernandez, D.P., Jensen, C.K., and Schindler, D.E., 2016, Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers: Geophysical Research Letters, v. 43, no. 10, p. 5043-5051, https://doi.org/10.1002/2016GL068904.","productDescription":"9 p.","startPage":"5043","endPage":"5051","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073082","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470972,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068904","text":"Publisher Index Page"},{"id":321442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"5740271be4b07e28b65dcfd4","contributors":{"authors":[{"text":"Brennan, Sean R.","contributorId":149334,"corporation":false,"usgs":false,"family":"Brennan","given":"Sean","email":"","middleInitial":"R.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":629872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":629871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollenbeck, Jeff P. 0000-0001-6481-5354 jhollenbeck@usgs.gov","orcid":"https://orcid.org/0000-0001-6481-5354","contributorId":5130,"corporation":false,"usgs":true,"family":"Hollenbeck","given":"Jeff","email":"jhollenbeck@usgs.gov","middleInitial":"P.","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":629873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Diego P.","contributorId":138701,"corporation":false,"usgs":false,"family":"Fernandez","given":"Diego","email":"","middleInitial":"P.","affiliations":[{"id":12499,"text":"Univ. of Utah","active":true,"usgs":false}],"preferred":false,"id":629874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jensen, Carrie K","contributorId":169520,"corporation":false,"usgs":false,"family":"Jensen","given":"Carrie","email":"","middleInitial":"K","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":629876,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schindler, Daniel E.","contributorId":83485,"corporation":false,"usgs":true,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":629875,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171104,"text":"70171104 - 2016 - Waterfowl endozoochory: An overlooked long-distance dispersal mode for Cuscuta (dodder)","interactions":[],"lastModifiedDate":"2016-05-20T09:25:09","indexId":"70171104","displayToPublicDate":"2016-05-20T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl endozoochory: An overlooked long-distance dispersal mode for Cuscuta (dodder)","docAbstract":"REMISE OF THE STUDY: Dispersal of parasitic Cuscuta species (dodders) worldwide has been assumed to be largely anthropomorphic because their seeds do not match any previously known dispersal syndrome and no natural dispersal vectors have been reliably documented. However, the genus has a subcosmopolitan distribution and recent phylogeographic results have indicated that at least18 historical cases of long-distance dispersal (LDD) have occurred during its evolution. The objective of this study is to report the first LDD biological vector for Cuscuta seeds.
\nMETHODS: Twelve northern pintails (Anas acuta) were collected from Suisun Marsh, California and the contents of their lowest part of the large intestine (rectum) were extracted and analyzed. Seed identification was done both morphologically and using a molecular approach. Extracted seeds were tested for germination and compared to seeds not subjected to gut passage to determine the extent of structural changes caused to the seed coat by passing through the digestive tract.
\nKEY RESULTS: Four hundred and twenty dodder seeds were found in the rectum of four northern pintails. From these, 411 seeds were identified as Cuscuta campestris and nine as most likely C. pacifica. The germination rate of C. campestris seeds after gut passage was 55%. Structural changes caused by the gut passage in both species were similar to those caused by an acid scarification.
\nCONCLUSIONS: Endozoochory by waterbirds may explain the historical LDD cases in the evolution of Cuscuta. This also suggests that current border quarantine measures may be insufficient to stopping spreading of dodder pests along migratory flyways.
\nAdvanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.04.018","usgsCitation":"Morway, E.D., Niswonger, R.G., and Triana, E., 2016, Toward improved simulation of river operations through integration with a hydrologic model: Environmental Modelling and Software, no. 82, p. 255-274, https://doi.org/10.1016/j.envsoft.2016.04.018.","productDescription":"20 p.","startPage":"255","endPage":"274","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070519","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":470977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2016.04.018","text":"Publisher Index Page"},{"id":321438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"82","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740271de4b07e28b65dcfea","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":629911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Triana, Enrique","contributorId":169532,"corporation":false,"usgs":false,"family":"Triana","given":"Enrique","email":"","affiliations":[{"id":25556,"text":"MWH Global, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":629912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170968,"text":"ofr20161075 - 2016 - Aquatic Trophic Productivity model: A decision support model for river restoration planning in the Methow River, Washington","interactions":[],"lastModifiedDate":"2017-11-22T15:48:44","indexId":"ofr20161075","displayToPublicDate":"2016-05-19T13:00:00","publicationYear":"2016","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":"2016-1075","title":"Aquatic Trophic Productivity model: A decision support model for river restoration planning in the Methow River, Washington","docAbstract":"The U.S. Geological Survey (USGS) has developed a dynamic food-web simulation model to provide decision support for Bureau of Reclamation (Reclamation) river restoration projects in the Methow River, Washington. This modeling effort was done to contribute to Reasonable and Prudent Alternative actions 56 and 57of the 2014 Federal Columbia River Power System Biological Opinion (FCRPS BO), which calls for exploration of modeling as a means to help evaluate Endangered Species Act (ESA)-listed fish response to river restoration efforts. In the Methow River, these species of concern include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha) and UCR summer steelhead (Oncorhynchus mykiss). Additionally, the Independent Scientific Advisory Board (ISAB) for the Columbia River has identified the need for modeling (Independent Scientific Advisory Board, 2011a)—including models that incorporate food-web dynamics (Independent Scientific Advisory Board, 2011b)—to better understand how restoration and management strategies might enhance salmon and steelhead populations.
\nDynamic food-web models, even relatively simple ones, can be valuable tools for exploring responses to river restoration. Although these models have rarely been applied to rivers and streams (but see Mcintire and Colby, 1978; Power and others, 1995), they are commonly used for management decisions in terrestrial and ocean ecosystems (Christensen and Pauly, 1993; Evans and others, 2013). One of the main strengths of these models is that they are rooted in the fundamental laws of thermodynamics (that is, mass balance). Moreover, these models can be easily adapted to different contexts by adding or subtracting different species from the web and by mechanistically linking the dynamics of web members to local environmental conditions, such as water temperature, stream discharge, and channel hydraulics (Power and others, 1995; Doyle, 2006). Alternative management actions can then be evaluated by changing these environmental conditions to simulate potential outcomes following restoration.
\nIn this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., and Bellmore, J.R., 2016, Aquatic trophic productivity model: A decision support model for river restoration planning in the Methow River, Washington: U.S. Geological Survey Open-File Report 2016‒1075, 85 p., https://dx.doi.org/10.3133/ofr20161075.","productDescription":"vi, 85 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1075/coverthb.jpg"},{"id":321409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1075/ofr20161075.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1075 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
During summer 2014, lake level, streamflow, and water temperature in and around Crystal Springs Lake in Portland, Oregon, were measured by the U.S. Geological Survey and the City of Portland Bureau of Environmental Services to better understand the effect of the lake on Crystal Springs Creek and Johnson Creek downstream. Johnson Creek is listed as an impaired water body for temperature by the Oregon Department of Environmental Quality (ODEQ), as required by section 303(d) of the Clean Water Act. A temperature total maximum daily load applies to all streams in the Johnson Creek watershed, including Crystal Springs Creek. Summer water temperatures downstream of Crystal Springs Lake and the Golf Pond regularly exceed the ODEQ numeric criterion of 64.4 °F (18.0 °C) for salmonid rearing and migration. To better understand temperature contributions of this system, the U.S. Geological Survey developed two-dimensional hydrodynamic water temperature models of Crystal Springs Lake and the Golf Pond. Model grids were developed to closely resemble the bathymetry of the lake and pond using data from a 2014 survey. The calibrated models simulated surface water elevations to within 0.06 foot (0.02 meter) and outflow water temperature to within 1.08 °F (0.60 °C). Streamflow, water temperature, and lake elevation data collected during summer 2014 supplied the boundary and reference conditions for the model. Measured discrepancies between outflow and inflow from the lake, assumed to be mostly from unknown and diffuse springs under the lake, accounted for about 46 percent of the total inflow to the lake.
\nModel simulations (scenarios) were run with lower water surface elevations in Crystal Springs Lake and increased shading to the lake to assess the relative effect the lake and pond characteristics have on water temperature. The Golf Pond was unaltered in all scenarios. The models estimated that lower lake elevations would result in cooler water downstream of the Golf Pond and shorter residence times in the lake. Increased shading to the lake would also provide substantial cooling. Most management scenarios resulted in a decrease in 7-day average of daily maximum values by about 2.0– 4.7 °F (1.1 –2.6 °C) for outflow from Crystal Springs Lake during the period of interest. Outflows from the Golf Pond showed a net temperature reduction of 0.5–2.7 °F (0.3–1.5 °C) compared to measured values in 2014 because of solar heating and downstream warming in the Golf Pond resulting from mixing with inflow from Reed Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161076","collaboration":"Prepared in cooperation with City of Portland Bureau of Environmental Services","usgsCitation":"Buccola, N.L., and Stonewall, A.J., 2016, Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon: U.S. Geological Survey Open-File Report 2016‒1076, 26 p.,\nhttps://dx.doi.org/10.3133/ofr20161076.","productDescription":"Report: vi, 26 p.; Tables 1-9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060388","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321392,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076_tables1-9.xlsx","text":"Tables 1-9","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1076 Tables 1-9"},{"id":321390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1076/coverthb.jpg"},{"id":321391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1076"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63982295989989,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.47522429601816\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.05.011","usgsCitation":"Jurgens, B.C., Bohlke, J.K., Kauffman, L.J., Belitz, K., and Esser, B.K., 2016, A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells: Journal of Hydrology, v. 543, no. A, p. 109-126, https://doi.org/10.1016/j.jhydrol.2016.05.011.","productDescription":"18 p.","startPage":"109","endPage":"126","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":325571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.9\n ],\n [\n -122,\n 37.2\n ],\n [\n -120.2,\n 37.2\n ],\n [\n -120.2,\n 37.9\n ],\n [\n -122,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"543","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57934440e4b0eb1ce79e8bd2","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, John Karl 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":127841,"corporation":false,"usgs":true,"family":"Bohlke","given":"John","email":"jkbohlke@usgs.gov","middleInitial":"Karl","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":643298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":643300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":643301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171088,"text":"70171088 - 2016 - Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?","interactions":[],"lastModifiedDate":"2016-05-19T09:45:34","indexId":"70171088","displayToPublicDate":"2016-05-19T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?","docAbstract":"As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.
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