DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear (Ursus americanus) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (pA and pB, respectively, or p, collectively), the proportion of each mixture (π), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI = 114–272) and 100 (95% CI = 74–167), respectively (pooled N = 261, 95% CI = 192–419), and the average weekly p was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation ≤20%) of estimates using logistic regression. The capture probability for the larger of 2 mixture proportions of the population (i.e., pA or pB, depending on the value of π) was most important for predicting accuracy and precision, whereas capture probabilities of both mixture proportions (pA and pB) were important to explain variation in coverage. Based on sampling conditions similar to parameter estimates from the empirical dataset (pA = 0.30, pB = 0.05, N = 250, π = 0.15, and k = 10), predicted accuracy and precision were low (60% and 53%, respectively), whereas coverage was high (94%). Increasing pB, the capture probability for the predominate but most difficult to capture proportion of the population, was most effective to improve accuracy under those conditions. However, manipulation of other parameters may be more effective under different conditions. In general, the probabilities of obtaining accurate and precise estimates were best when p≥ 0.2. Our regression models can be used by managers to evaluate specific sampling scenarios and guide development of sampling frameworks or to assess reliability of DNA-based capture-mark-recapture studies.
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processes","docAbstract":"In the late nineteenth century and twentieth century, there was considerable interest and activity to develop the United States for agricultural, mining, and many other purposes to improve the quality of human life standards and prosperity. Most of the work to support this development was focused along disciplinary lines with little attention focused on ecosystem service trade-offs or synergisms, especially those that transcended boundaries of scientific disciplines and specific interest groups. Concurrently, human population size has increased substantially and its use of ecosystem services has increased more than five-fold over just the past century. Consequently, the contemporary landscape has been highly modified for human use, leaving behind a fragmented landscape where basic ecosystem functions and processes have been broadly altered. Over this period, climate change also interacted with other anthropogenic effects, resulting in modern environmental problems having a complexity that is without historical precedent. The challenge before the scientific community is to develop new science paradigms that integrate relevant scientific disciplines to properly frame and evaluate modern environmental problems in a systems-type approach to better inform the decision-making process. Wetland science is a relatively new discipline that grew out of the conservation movement of the early twentieth century. In the United States, most of the conservation attention in the earlier days was on wildlife, but a growing human awareness of the importance of the environment led to the passage of the National Environmental Policy Act in 1969. Concurrently, there was a broadening interest in conservation science, and the scientific study of wetlands gradually gained acceptance as a scientific discipline. Pioneering wetland scientists became formally organized when they formed The Society of Wetland Scientists in 1980 and established a publication outlet to share wetland research findings. In comparison to older and more traditional scientific disciplines, the wetland sciences may be better equipped to tackle today’s complex problems. Since its emergence as a scientific discipline, the study of wetlands has frequently required interdisciplinary and integrated approaches. This interdisciplinary/integrated approach is largely the result of the fact that wetlands cannot be studied in isolation of upland areas that contribute surface and subsurface water, solutes, sediments, and nutrients into wetland basins. However, challenges still remain in thoroughly integrating the wetland sciences with scientific disciplines involved in upland studies, especially those involved with agriculture, development, and other land-conversion activities that influence wetland hydrology, chemistry, and sedimentation. One way to facilitate this integration is to develop an understanding of how human activities affect wetland ecosystem services, especially the trade-offs and synergisms that occur when land-use changes are made. Used in this context, an understanding of the real costs of managing for a particular ecosystem service or groups of services can be determined and quantified in terms of reduced delivery of other services and in overall sustainability of the wetland and the landscapes that support them. In this chapter, we discuss some of the more salient aspects of a few common wetland types to give the reader some background on the diversity of functions that wetlands perform and the specific ecosystem services they provide to society. Wetlands are among the most complex ecosystems on the planet, and it is often difficult to communicate to a diverse public all of the positive services wetlands provide to mankind. Our goal is to help the reader develop an understanding that management options can be approached as societal choices where decisions can be made within a spatial and temporal context to identify trade-offs, synergies, and effects on long-term sustainability of wetland ecosystems. This will be especially relevant as we move into alternate climate futures where our portfolio of management options for mitigating damage to ecosystem function or detrimental cascading effects must be diverse and effective.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland Techniques","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York","doi":"10.1007/978-94-007-6907-6_5","isbn":"9789400769069","usgsCitation":"Euliss, N.H., Mushet, D.M., Smith, L., Conner, W.H., Burkett, V.R., Wilcox, D.A., Hester, M.W., and Zheng, H., 2013, Ecosystem services: developing sustainable management paradigms based on wetland functions and processes, chap. of Wetland Techniques, v. 3, p. 181-227, https://doi.org/10.1007/978-94-007-6907-6_5.","productDescription":"47 p.","startPage":"181","endPage":"227","ipdsId":"IP-035387","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":278853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278852,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/978-94-007-6907-6_5"}],"country":"United States","volume":"3","noUsgsAuthors":false,"publicationDate":"2013-08-03","publicationStatus":"PW","scienceBaseUri":"527a2181e4b051792d019509","contributors":{"authors":[{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":485137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Loren M.","contributorId":88876,"corporation":false,"usgs":true,"family":"Smith","given":"Loren M.","affiliations":[],"preferred":false,"id":485143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, William H.","contributorId":79376,"corporation":false,"usgs":false,"family":"Conner","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":485141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burkett, Virginia R. 0000-0003-4746-2862","orcid":"https://orcid.org/0000-0003-4746-2862","contributorId":80229,"corporation":false,"usgs":true,"family":"Burkett","given":"Virginia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilcox, Douglas A.","contributorId":36880,"corporation":false,"usgs":true,"family":"Wilcox","given":"Douglas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485139,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hester, Mark W.","contributorId":9566,"corporation":false,"usgs":true,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":485138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zheng, Haochi","contributorId":61333,"corporation":false,"usgs":true,"family":"Zheng","given":"Haochi","affiliations":[],"preferred":false,"id":485140,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70048501,"text":"70048501 - 2013 - A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i","interactions":[],"lastModifiedDate":"2014-06-20T14:10:14","indexId":"70048501","displayToPublicDate":"2013-07-01T13:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"HCSU-041","title":"A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i","docAbstract":"Using acoustic recordings of the vocalizations of the endangered Hawaiian hoary bat (Lasiurus \ncinereus semotus) collected over a five-year period (2007–2011) from 25 survey areas across \nthe island of Hawai`i, we modeled the relationship between habitat attributes and bat \noccurrence. Our data support the conclusion that hoary bats concentrate in the coastal lowlands \nof Hawai`i during the breeding season, May through October, and migrate to interior highlands \nduring the winter non-breeding season. Highest occupancy peaked on the Julian date 15 \nSeptember across the five-year average and during the season of fledging by the young of the \nyear. Although the Hawaiian hoary bat is a habitat generalist species and occurs from sea level \nto the highest volcanic peaks on Hawai`i, there was a significant association between\noccupancy and the prevalence of mature forest cover. Trends in occupancy were stable to\nslightly increasing during the breeding season over the five years of our surveys.","language":"English","publisher":"University of Hawai‘i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Gorressen, M.P., Bonaccorso, F., Pinzari, C., Todd, C.M., Montoya-Aiona, K., and Brinck, K., 2013, A five-year study of Hawaiian hoary bat (Lasiurus cinereus semotus) occupancy on the island of Hawai`i, iv, 48 p.","productDescription":"iv, 48 p.","numberOfPages":"54","ipdsId":"IP-046159","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":279187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278237,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"projection":"Universal Transverse Mercator 5 North projection","datum":"North American Datum of 1983","country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.2729,18.8676 ], [ -156.2729,20.2894 ], [ -154.6488,20.2894 ], [ -154.6488,18.8676 ], [ -156.2729,18.8676 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528c96a9e4b0c629af44dd8f","contributors":{"authors":[{"text":"Gorressen, Marcos P.","contributorId":40887,"corporation":false,"usgs":true,"family":"Gorressen","given":"Marcos","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonaccorso, Frank J.","contributorId":73089,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank J.","affiliations":[],"preferred":false,"id":484857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinzari, Corinna A.","contributorId":57359,"corporation":false,"usgs":true,"family":"Pinzari","given":"Corinna A.","affiliations":[],"preferred":false,"id":484855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Christopher M.","contributorId":64548,"corporation":false,"usgs":true,"family":"Todd","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":484853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":484852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70102818,"text":"70102818 - 2013 - Uncertainty in simulated groundwater-quality trends in transient flow","interactions":[],"lastModifiedDate":"2014-04-24T13:35:00","indexId":"70102818","displayToPublicDate":"2013-07-01T13:33:13","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in simulated groundwater-quality trends in transient flow","docAbstract":"In numerical modeling of groundwater flow, the result of a given solution method is affected by the way in which transient flow conditions and geologic heterogeneity are simulated. An algorithm is demonstrated that simulates breakthrough curves at a pumping well by convolution-based particle tracking in a transient flow field for several synthetic basin-scale aquifers. In comparison to grid-based (Eulerian) methods, the particle (Lagrangian) method is better able to capture multimodal breakthrough caused by changes in pumping at the well, although the particle method may be apparently nonlinear because of the discrete nature of particle arrival times. Trial-and-error choice of number of particles and release times can perhaps overcome the apparent nonlinearity. Heterogeneous aquifer properties tend to smooth the effects of transient pumping, making it difficult to separate their effects in parameter estimation. Porosity, a new parameter added for advective transport, can be accurately estimated using both grid-based and particle-based methods, but predictions can be highly uncertain, even in the simple, nonreactive case.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrogeology Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer-Verlag","doi":"10.1007/s10040-013-0967-2","usgsCitation":"Starn, J.J., Bagtzoglou, A., and Robbins, G.A., 2013, Uncertainty in simulated groundwater-quality trends in transient flow: Hydrogeology Journal, v. 21, no. 4, p. 813-827, https://doi.org/10.1007/s10040-013-0967-2.","productDescription":"15 p.","startPage":"813","endPage":"827","numberOfPages":"15","ipdsId":"IP-037984","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":286534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286533,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10040-013-0967-2"}],"volume":"21","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-03-13","publicationStatus":"PW","scienceBaseUri":"535a3272e4b0d0864496275d","contributors":{"authors":[{"text":"Starn, J. Jeffrey","contributorId":101617,"corporation":false,"usgs":true,"family":"Starn","given":"J.","email":"","middleInitial":"Jeffrey","affiliations":[],"preferred":false,"id":493019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagtzoglou, Amvrossios","contributorId":90641,"corporation":false,"usgs":true,"family":"Bagtzoglou","given":"Amvrossios","affiliations":[],"preferred":false,"id":493018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robbins, Gary A.","contributorId":41743,"corporation":false,"usgs":true,"family":"Robbins","given":"Gary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493017,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048597,"text":"70048597 - 2013 - Preventing the trade of conflict diamonds and supporting artisanal mining","interactions":[],"lastModifiedDate":"2018-03-23T14:27:40","indexId":"70048597","displayToPublicDate":"2013-07-01T13:00:56","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":822,"text":"Apogeo Spatial","active":true,"publicationSubtype":{"id":10}},"title":"Preventing the trade of conflict diamonds and supporting artisanal mining","docAbstract":"Because of this association between the richness of a deposit and its geomorphology, high-resolution DEMs are a critical dataset in developing alluvial geomorphic models of the deposit zones.","language":"English","usgsCitation":"Chirico, P., and Malpeli, K., 2013, Preventing the trade of conflict diamonds and supporting artisanal mining: Apogeo Spatial, v. 28, no. 3, p. 28-32.","productDescription":"5 p.","startPage":"28","endPage":"32","ipdsId":"IP-045101","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":278884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527b7320e4b0a7295d9b863e","contributors":{"authors":[{"text":"Chirico, Peter G. pchirico@usgs.gov","contributorId":2659,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","email":"pchirico@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":485179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":485180,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70057585,"text":"70057585 - 2013 - Rivermouth alteration of agricultural impacts on consumer tissue δ15N","interactions":[],"lastModifiedDate":"2013-11-26T12:13:43","indexId":"70057585","displayToPublicDate":"2013-07-01T12:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Rivermouth alteration of agricultural impacts on consumer tissue δ15N","docAbstract":"Terrestrial agricultural activities strongly influence riverine nitrogen (N) dynamics, which is reflected in the δ15N of riverine consumer tissues. However, processes within aquatic ecosystems also influence consumer tissue δ15N. As aquatic processes become more important terrestrial inputs may become a weaker predictor of consumer tissue δ15N. In a previous study, this terrestrial-consumer tissue δ15N connection was very strong at river sites, but was disrupted by processes occurring in rivermouths (the ‘rivermouth effect’). This suggested that watershed indicators of N loading might be accurate in riverine settings, but could be inaccurate when considering N loading to the nearshore of large lakes and oceans. In this study, the rivermouth effect was examined on twenty-five sites spread across the Laurentian Great Lakes. Relationships between agriculture and consumer tissue δ15N occurred in both upstream rivers and at the outlets where rivermouths connect to the nearshore zone, but agriculture explained less variation and had a weaker effect at the outlet. These results suggest that rivermouths may sometimes be significant sources or sinks of N, which would cause N loading estimates to the nearshore zone that are typically made at discharge gages further upstream to be inaccurate. Identifying definitively the controls over the rivermouth effect on N loading (and other nutrients) will require integration of biogeochemical and hydrologic models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0069313","usgsCitation":"Larson, J.H., Richardson, W.B., Vallazza, J.M., and Nelson, J., 2013, Rivermouth alteration of agricultural impacts on consumer tissue δ15N: PLoS ONE, v. 8, no. 7, 8 p., https://doi.org/10.1371/journal.pone.0069313.","productDescription":"8 p.","numberOfPages":"8","ipdsId":"IP-042888","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":473709,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0069313","text":"Publisher Index Page"},{"id":279800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279645,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0069313"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.38 ], [ -92.11,48.85 ], [ -76.3,48.85 ], [ -76.3,41.38 ], [ -92.11,41.38 ] ] ] } } ] }","volume":"8","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-07-31","publicationStatus":"PW","scienceBaseUri":"5295d12ae4b0becc369c8c95","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":486821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":486819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vallazza, Jonathan M. jvallazza@usgs.gov","contributorId":3651,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":486820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, J. C. 0000-0002-7105-0107 jcnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-7105-0107","contributorId":459,"corporation":false,"usgs":true,"family":"Nelson","given":"J. C.","email":"jcnelson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":486818,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148153,"text":"70148153 - 2013 - Relationships between river discharge and abundance of age 0 redhorses (Moxostoma spp.) in the Oconee River, Georgia, USA, with implications for robust redhorse","interactions":[],"lastModifiedDate":"2015-05-22T10:33:32","indexId":"70148153","displayToPublicDate":"2013-07-01T11:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between river discharge and abundance of age 0 redhorses (Moxostoma spp.) in the Oconee River, Georgia, USA, with implications for robust redhorse","docAbstract":"Robust redhorse (Moxostoma robustum) and notchlip redhorse (M. collapsum) are two species of redhorses that reside in the lower Oconee River, Georgia. Robust redhorse is listed as a state endangered species in Georgia and North Carolina, and attempts to investigate factors affecting its reproductive success have met with limited success. Therefore, catch of robust redhorse young were combined with catch of notchlip redhorse to increase sample size. These congeners with similar spawning repertoire were assumed to respond similarly to environmental conditions. River discharge during spawning and rearing seasons may affect abundance of both redhorses in the lower Oconee River. An information-theoretic approach was used to evaluate the relative support of models relating abundance of age 0 redhorses to monthly discharge statistics that represented magnitude, timing, duration, variability and frequency of river discharge events for April through June 1995–2006. The best-approximating model indicated a negative relationship between the abundance of redhorses and mean maximum river discharge and the number of high pulses during June as well as a positive relationship with intermediate duration of low flows during April–June. This model is 9.6 times more plausible than the next best-fitting model, which revealed a negative relationship between the abundance of redhorses and mean maximum river discharge during May and the number of high pulses during June as well as a positive relationship between abundance and intermediate duration of low flows during April–June. Management implications from the results indicate low-stable flows for at least a 2-week period during spawning and rearing may increase reproductive success of robust and notchlip redhorses.
","language":"English","publisher":"John Wiley & Sons","publisherLocation":"John Wiley & Sons","doi":"10.1002/rra.2566","usgsCitation":"Peterson, R., Jennings, C.A., and Peterson, J., 2013, Relationships between river discharge and abundance of age 0 redhorses (Moxostoma spp.) in the Oconee River, Georgia, USA, with implications for robust redhorse: River Research and Applications, v. 29, no. 6, p. 734-742, https://doi.org/10.1002/rra.2566.","productDescription":"9 p.","startPage":"734","endPage":"742","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-020815","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473710,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.2566","text":"Publisher Index Page"},{"id":300698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2012-03-17","publicationStatus":"PW","scienceBaseUri":"55605332e4b0afeb7072417e","contributors":{"authors":[{"text":"Peterson, R.","contributorId":69773,"corporation":false,"usgs":true,"family":"Peterson","given":"R.","affiliations":[],"preferred":false,"id":547492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jennings, Cecil A. 0000-0002-6159-6026 jennings@usgs.gov","orcid":"https://orcid.org/0000-0002-6159-6026","contributorId":874,"corporation":false,"usgs":true,"family":"Jennings","given":"Cecil","email":"jennings@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, J.T.","contributorId":30170,"corporation":false,"usgs":true,"family":"Peterson","given":"J.T.","email":"","affiliations":[],"preferred":false,"id":547493,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048520,"text":"70048520 - 2013 - Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","interactions":[],"lastModifiedDate":"2013-11-15T10:25:05","indexId":"70048520","displayToPublicDate":"2013-07-01T11:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","docAbstract":"Questions: Do long-term observations in permanent plots confirm the conceptual model of Metrosideros polymorpha cohort dynamics as postulated in 1987? Do regeneration patterns occur independently of substrate age, i.e. of direct volcanic disturbance impact?\n\nLocation: The windward mountain slopes of the younger Mauna Loa and the older Mauna Kea volcanoes (island of Hawaii, USA).\n\nMethods: After widespread forest decline (dieback), permanent plots were established in 1976 in 13 dieback and 13 non-dieback patches to monitor the population structure of M. polymorpha at ca. 5-yr intervals. Within each plot of 20 × 20 m, all trees with DBH >2.5 cm were individually tagged, measured and tree vigour assessed; regeneration was quantified in 16 systematically placed subplots of 3 × 5 m. Data collected in the subplots included the total number of M. polymorpha seedlings and saplings (five stem height classes). Here we analyse monitoring data from six time steps from 1976 to 2003 using repeated measures ANOVA to test specific predictions derived from the 1987 conceptual model.\n\nResults: Regeneration was significantly different between dieback and non-dieback plots. In dieback plots, the collapse in the 1970s was followed by a ‘sapling wave’ that by 2003 led to new cohort stands of M. polymorpha. In non-dieback stands, seedling emergence did not result in sapling waves over the same period. Instead, a ‘sapling gap’ (i.e. very few or no M. polymorpha saplings) prevailed as typical for mature stands. Canopy dieback in 1976, degree of recovery by 2003 and the number of living trees in 2003 were unrelated to substrate age.\n\nConclusions: Population development of M. polymorpha supports the cohort dynamics model, which predicts rebuilding of the forest with the same canopy species after dieback. The lack of association with substrate age suggests that the long-term maintenance of cohort structure in M. polymorpha does not depend on volcanic disturbance but may be related to other environmental mechanisms, such as climate anomalies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Vegetation Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jvs.12000","usgsCitation":"Boehmer, H., Wagner, H.H., Jacobi, J.D., Gerrish, G.C., and Mueller-Dombois, D., 2013, Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest: Journal of Vegetation Science, v. 24, no. 4, p. 639-650, https://doi.org/10.1111/jvs.12000.","productDescription":"12 p.","startPage":"639","endPage":"650","numberOfPages":"12","ipdsId":"IP-026370","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":473711,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/75550","text":"External Repository"},{"id":278376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278375,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jvs.12000"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.707,19.1549 ], [ -155.707,20.1673 ], [ -154.8068,20.1673 ], [ -154.8068,19.1549 ], [ -155.707,19.1549 ] ] ] } } ] }","volume":"24","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"526a4174e4b0c0d229f9f6ae","contributors":{"authors":[{"text":"Boehmer, Hans Juergen","contributorId":45996,"corporation":false,"usgs":true,"family":"Boehmer","given":"Hans Juergen","affiliations":[],"preferred":false,"id":484938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Helene H.","contributorId":12309,"corporation":false,"usgs":true,"family":"Wagner","given":"Helene","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":484937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":484936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerrish, Grant C.","contributorId":69049,"corporation":false,"usgs":true,"family":"Gerrish","given":"Grant","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":484939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller-Dombois, Dieter","contributorId":100730,"corporation":false,"usgs":true,"family":"Mueller-Dombois","given":"Dieter","affiliations":[],"preferred":false,"id":484940,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046137,"text":"70046137 - 2013 - Ambient response of a unique performance-based design tall building with dynamic response modification features","interactions":[],"lastModifiedDate":"2022-03-24T16:52:46.990686","indexId":"70046137","displayToPublicDate":"2013-07-01T10:53:31","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10523,"text":"The Structural Design of Tall and Special Buildings","onlineIssn":"1541-7808","active":true,"publicationSubtype":{"id":10}},"title":"Ambient response of a unique performance-based design tall building with dynamic response modification features","docAbstract":"A 64-story, performance-based design building with reinforced concrete core shear walls and unique dynamic response modification features (tuned liquid sloshing dampers and buckling-restrained braces) has been instrumented with a monitoring array of 72 channels of accelerometers. The responses of the building to ambient motions from ground or wind were recorded and analyzed to identify modes and associated frequencies and damping. Not unexpectedly, the low-amplitude dynamic characteristics are considerably different than those computed from design analyses. Nonetheless, these computed values serve as a baseline against which to compare future strong shaking responses. Such studies help to improve our understanding of the effectiveness of the response modification features at various levels of shaking, to evaluate the predictive capabilities of the design analysis tools and to improve similar designs in the future.
Erosion of volcanic ocean islands creates dramatic landscapes, modulates Earth’s carbon cycle, and delivers sediment to coasts and reefs. Because many volcanic islands have large climate gradients and minimal variations in lithology and tectonic history, they are excellent natural laboratories for studying climatic effects on the evolution of topography. Despite concerns that modern sediment fluxes to island coasts may exceed long-term fluxes, little is known about how erosion rates and processes vary across island interiors, how erosion rates are influenced by the strong climate gradients on many islands, and how modern island erosion rates compare to long-term rates. Here, we present new measurements of erosion rates over 5 yr to 5 m.y. timescales on the Hawaiian island of Kaua‘i, across which mean annual precipitation ranges from 0.5 to 9.5 m/yr. Eroded rock volumes from basins across Kaua‘i indicate that million-year-scale erosion rates are correlated with modern mean annual precipitation and range from 8 to 335 t km–2 yr–1. In Kaua‘i’s Hanalei River basin, 3He concentrations in detrital olivines imply millennial-scale erosion rates of >126 to >390 t km–2 yr–1 from olivine-bearing hillslopes, while fluvial suspended sediment fluxes measured from 2004 to 2009 plus estimates of chemical and bed-load fluxes imply basin-averaged erosion rates of 545 ± 128 t km–2 yr–1. Mapping of landslide scars in satellite imagery of the Hanalei basin from 2004 and 2010 implies landslide-driven erosion rates of 30–47 t km–2 yr–1. These measurements imply that modern erosion rates in the Hanalei basin are no more than 2.3 ± 0.6 times faster than millennial-scale erosion rates, and, to the extent that modern precipitation patterns resemble long-term patterns, they are consistent with a link between precipitation rates and long-term erosion rates.
","language":"English","publisher":"GSA Bulletin","doi":"10.1130/B30726.1","usgsCitation":"Ferrier, K., J. Taylor Perron, Mukhopadhyay, S., Rosener, M., Stock, J.D., Slosberg, M., and Huppert, K.L., 2013, Covariation of climate and long-term erosion rates acrossa steep rainfall gradient on the Hawaiian island of Kaua'i: Geological Society of America Bulletin, v. 125, no. 7-8, p. 1146-1163, https://doi.org/10.1130/B30726.1.","productDescription":"18 p. 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Taylor Perron","contributorId":193528,"corporation":false,"usgs":false,"family":"J. Taylor Perron","affiliations":[],"preferred":false,"id":700732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mukhopadhyay, Sujoy","contributorId":193532,"corporation":false,"usgs":false,"family":"Mukhopadhyay","given":"Sujoy","email":"","affiliations":[],"preferred":false,"id":700736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosener, Matt","contributorId":193531,"corporation":false,"usgs":false,"family":"Rosener","given":"Matt","email":"","affiliations":[],"preferred":false,"id":700735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stock, Jonathan D. 0000-0001-8565-3577 jstock@usgs.gov","orcid":"https://orcid.org/0000-0001-8565-3577","contributorId":3648,"corporation":false,"usgs":true,"family":"Stock","given":"Jonathan","email":"jstock@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":700731,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slosberg, Michelle","contributorId":193533,"corporation":false,"usgs":false,"family":"Slosberg","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":700739,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huppert, Kimberly L.","contributorId":193530,"corporation":false,"usgs":false,"family":"Huppert","given":"Kimberly","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":700734,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70040562,"text":"70040562 - 2013 - Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change","interactions":[],"lastModifiedDate":"2013-07-01T11:29:47","indexId":"70040562","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change","docAbstract":"The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Climatic Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10584-012-0629-8","usgsCitation":"Riverson, J., Coats, R., Costa-Cabral, M., Dettinger, M., Reuter, J., Sahoo, G., and Schladow, G., 2013, Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change: Climatic Change, v. 116, no. 1, p. 35-50, https://doi.org/10.1007/s10584-012-0629-8.","productDescription":"16 p.","startPage":"35","endPage":"50","ipdsId":"IP-041968","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":274350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274349,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10584-012-0629-8"}],"country":"United States","state":"Nevada;California","otherGeospatial":"Lake Tahoe","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.163938,38.936611 ], [ -120.163938,39.248854 ], [ -119.926019,39.248854 ], [ -119.926019,38.936611 ], [ -120.163938,38.936611 ] ] ] } } ] }","volume":"116","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-11-15","publicationStatus":"PW","scienceBaseUri":"51d296d8e4b0ca18483389af","contributors":{"authors":[{"text":"Riverson, John","contributorId":39677,"corporation":false,"usgs":true,"family":"Riverson","given":"John","email":"","affiliations":[],"preferred":false,"id":468539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coats, Robert","contributorId":108007,"corporation":false,"usgs":true,"family":"Coats","given":"Robert","affiliations":[],"preferred":false,"id":468543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costa-Cabral, Mariza","contributorId":42507,"corporation":false,"usgs":true,"family":"Costa-Cabral","given":"Mariza","email":"","affiliations":[],"preferred":false,"id":468540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Mike 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":859,"corporation":false,"usgs":true,"family":"Dettinger","given":"Mike","email":"mddettin@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":468537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reuter, John","contributorId":107169,"corporation":false,"usgs":true,"family":"Reuter","given":"John","email":"","affiliations":[],"preferred":false,"id":468542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sahoo, Goloka","contributorId":82204,"corporation":false,"usgs":true,"family":"Sahoo","given":"Goloka","email":"","affiliations":[],"preferred":false,"id":468541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schladow, Geoffrey","contributorId":10312,"corporation":false,"usgs":true,"family":"Schladow","given":"Geoffrey","email":"","affiliations":[],"preferred":false,"id":468538,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193598,"text":"70193598 - 2013 - Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","interactions":[],"lastModifiedDate":"2017-11-02T14:32:48","indexId":"70193598","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","docAbstract":"Assessments of climate change over time scales that exceed the last 100 years require robust integration of high-quality instrument records with high-resolution paleoclimate proxy data. In this study, we show that the recent biogenic sediments accumulating in two temperate ice-free fjords in Southeast Alaska preserve evidence of North Pacific Ocean climate variability as recorded by both instrument networks and satellite observations. Multicore samples EW0408-32MC and EW0408-43MC were investigated with 137Cs and excess 210Pb geochronometry, three-dimensional computed tomography, high-resolution scanning XRF geochemistry, and organic stable isotope analyses. EW0408-32MC (57.162°N, 135.357°W, 146 m depth) is a moderately bioturbated continuous record that spans AD ∼1930–2004. EW0408-43MC (56.965°N, 135.268°W, 91 m depth) is composed of laminated diatom oozes, a turbidite, and a hypopycnal plume (river flood) deposit. A discontinuous event-based varve chronology indicates 43MC spans AD ∼1940–1981. Decadal-scale fluctuations in sedimentary Br/Cl ratios accurately reflect changes in marine organic matter accumulation that display the same temporal pattern as that of the Pacific Decadal Oscillation. An estimated Sitka summer productivity parameter calibrated using SeaWiFS satellite observations support these relationships. The correlation of North Pacific climate regime states, primary productivity, and sediment geochemistry indicate the accumulation of biogenic sediment in Southeast Alaska temperate fjords can be used as a sensitive recorder of past productivity variability, and by inference, past climate conditions in the high-latitude Gulf of Alaska.
","language":"English","publisher":"AGU","doi":"10.1002/jgrc.20243","usgsCitation":"Addison, J.A., Finney, B., Jaeger, J.M., Stoner, J.S., Norris, R.D., and Hangsterfer, A., 2013, Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska: Journal of Geophysical Research: Oceans, v. 118, no. 7, p. 3444-3461, https://doi.org/10.1002/jgrc.20243.","productDescription":"18 p.","startPage":"3444","endPage":"3461","ipdsId":"IP-043226","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473724,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrc.20243","text":"Publisher Index Page"},{"id":348106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155,\n 50\n ],\n [\n -120,\n 50\n ],\n [\n -120,\n 61\n ],\n [\n -155,\n 61\n ],\n [\n -155,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-17","publicationStatus":"PW","scienceBaseUri":"59fc2eace4b0531197b27fc1","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":719561,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaeger, John M.","contributorId":11423,"corporation":false,"usgs":true,"family":"Jaeger","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":719562,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stoner, Joseph S.","contributorId":84171,"corporation":false,"usgs":true,"family":"Stoner","given":"Joseph","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719563,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Norris, Richard D.","contributorId":51651,"corporation":false,"usgs":true,"family":"Norris","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":719564,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hangsterfer, Alexandra","contributorId":199603,"corporation":false,"usgs":false,"family":"Hangsterfer","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":719560,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70046757,"text":"ofr20121234 - 2013 - Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida","interactions":[],"lastModifiedDate":"2014-09-04T15:49:18","indexId":"ofr20121234","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","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":"2012-1234","title":"Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida","docAbstract":"U.S. Geological Survey (USGS) scientists have provided a model-based assessment of transport and deposition of residual Deepwater Horizon oil along the shoreline within the northern Gulf of Mexico in the form of mixtures of sand and weathered oil, known as surface residual balls (SRBs). The results of this USGS research, in combination with results from other components of the overall study, will inform operational decisionmaking. The results will provide guidance for response activities and data collection needs during future oil spills.
\nIn May 2012 the U.S. Coast Guard, acting as the Deepwater Horizon Federal on-scene coordinator, chartered an operational science advisory team to provide a science-based review of data collected and to conduct additional directed studies and sampling. The goal was to characterize typical shoreline profiles and morphology in the northern Gulf of Mexico to identify likely sources of residual oil and to evaluate mechanisms whereby reoiling phenomena may be occurring (for example, burial and exhumation and alongshore transport). A steering committee cochaired by British Petroleum Corporation (BP) and the National Oceanic and Atmospheric Administration (NOAA) is overseeing the project and includes State on-scene coordinators from four States (Alabama, Florida, Louisiana, and Mississippi), trustees of the U.S. Department of the Interior (DOI), and representatives from the U.S. Coast Guard.
\nThis report presents the results of hydrodynamic and sediment transport models and developed techniques for analyzing potential SRB movement and burial and exhumation along the coastline of Alabama and Florida. Results from these modeling efforts are being used to explain the complexity of reoiling in the nearshore environment and to broaden consideration of the different scenarios and difficulties that are being faced in identifying and removing residual oil. For instance, modeling results suggest that larger SRBs are not, under the most commonly observed low-energy wave conditions, likely to move very far alongshore. This finding suggests that SRBs from one source location may not (outside of storm conditions) be redistributed to other up or down coast locations. This information can guide operational response decisions. In addition, because SRBs are less mobile compared with sand, they are likely to become buried and unburied under normal sand transport processes thereby lengthening the time SRBs may take to move onshore. The rate of onshore movement was not specifically addressed by this study, yet the results resolve the cross-shore domain and cross-shore variations in alongshore transport that are relevant to achieving the primary objectives. Furthermore, during infrequent events (for example, winter storms and severe meteorological events such as Hurricane Isaac of August 2012), energy is shown to be sufficient to move a greater range of SRB sizes and potentially expose and break up submerged oil mats. When SRBs do move alongshore, the models indicate that there are regions that are more conducive to accumulation of SRB material than others. Accumulation can occur where there are reversals and decelerations in alongshore currents and where forces created by shear stress drops below critical thresholds to maintain or initiate SRB movement. In addition, flow and SRB mobility patterns around inlets indicate patterns in hydrodynamic forces that influence redistribution of SRBs and the surface oil that mixed with sediment to form oil mats in the first place.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121234","collaboration":"Prepared in cooperation with the Operational Science Advisory Team (OSAT3) Steering Committee chartered by the Deepwater Horizon Federal On-Scene Coordinator (FOSC)","usgsCitation":"Plant, N.G., Long, J.W., Dalyander, P., Thompson, D.M., and Raabe, E.A., 2013, Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida (First posted July 2, 2013; Revised and reposted September 4, 2014, version 1.1): U.S. Geological Survey Open-File Report 2012-1234, Report PDF: vii, 47 p.; Report HTML and Digital Data, https://doi.org/10.3133/ofr20121234.","productDescription":"Report PDF: vii, 47 p.; Report HTML and Digital Data","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":274406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121234.PNG"},{"id":274405,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1234/pdf/ofr2012-1234.pdf"},{"id":274403,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1234/"},{"id":274404,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1234/title.html"}],"country":"United States","state":"Alabama;Florida","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.2862,29.6323 ], [ -89.2862,30.9921 ], [ -85.3716,30.9921 ], [ -85.3716,29.6323 ], [ -89.2862,29.6323 ] ] ] } } ] }","edition":"First posted July 2, 2013; Revised and reposted September 4, 2014, version 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296cfe4b0ca184833899b","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":480173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":480174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raabe, Ellen A. eraabe@usgs.gov","contributorId":2125,"corporation":false,"usgs":true,"family":"Raabe","given":"Ellen","email":"eraabe@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168465,"text":"70168465 - 2013 - Fall survival of American woodcock in the western Great Lakes Region","interactions":[],"lastModifiedDate":"2016-02-16T11:49:27","indexId":"70168465","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Fall survival of American woodcock in the western Great Lakes Region","docAbstract":"We estimated fall (10 Sep–8 Nov) survival rates, cause-specific mortality rates, and determined the magnitude and sources of mortality of 1,035 radio-marked American woodcock (Scolopax minor) in Michigan, Minnesota, and Wisconsin during 2001–2004. In all 3 states, we radio-marked woodcock on paired study areas; 1 of which was open to hunting and expected to receive moderate to high hunter use and the other of which was either closed to hunting (Michigan and Minnesota) or was relatively inaccessible to hunters (Wisconsin). We used Program MARK to estimate fall survival rates, to evaluate a set of candidate models to examine the effects of hunting and several covariates (sex, age, year, state) on survival, and to examine the relationship between survival rates and kill rates due to hunting. Hunting accounted for 70% of the 86 woodcock deaths in the hunted areas, followed by predation (20%) and various other sources of mortality (10%). Woodcock deaths that occurred in the non-hunted and lightly hunted areas (n = 50) were caused by predators (46%), hunting (32%), and various other sources (22%). Based on small-sample corrected Akaike's Information Criterion values, variation in fall survival of woodcock was best explained by treatment (i.e., hunted vs. non-hunted), year, and period (pre-hunting season intervals vs. hunting season intervals). The average fall survival estimate from our best model for woodcock in the non-hunted areas (0.893, 95% CI = 0.864–0.923) was greater than the average for the hunted areas (0.820, 95% CI = 0.786–0.854 [this estimate includes data from the lightly hunted area in Wisconsin]), and the average treatment effect (i.e., greater survival rates in non-hunted areas) was 0.074 (95% CI = 0.018–0.129). The kill rate due to hunting was 0.120 (95% CI = 0.090–0.151) when data were pooled among states and years. We detected a negative relationship between hunting kill rates and survival in our hunted areas, which suggests that hunting mortality was at least partially additive during fall. Our results illustrate the influence of hunting relative to other sources of mortality in Michigan, Minnesota, and Wisconsin, and indicate that managers may be able to influence fall survival rates by manipulating hunting regulations or access on public land.
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Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1002/grl.50491","usgsCitation":"Polade, S.D., Gershunov, A., Cayan, D.R., Dettinger, M., and Pierce, D.W., 2013, Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models: Geophysical Research Letters, v. 40, no. 10, p. 2296-2301, https://doi.org/10.1002/grl.50491.","productDescription":"6 p.","startPage":"2296","endPage":"2301","ipdsId":"IP-045319","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":473723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/grl.50491","text":"Publisher Index Page"},{"id":274340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274339,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50491"}],"volume":"40","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-05-31","publicationStatus":"PW","scienceBaseUri":"51d296dbe4b0ca18483389bf","contributors":{"authors":[{"text":"Polade, Suraj D.","contributorId":49687,"corporation":false,"usgs":true,"family":"Polade","given":"Suraj","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":477765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gershunov, Alexander","contributorId":35622,"corporation":false,"usgs":true,"family":"Gershunov","given":"Alexander","affiliations":[],"preferred":false,"id":477764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cayan, Daniel R. 0000-0002-2719-6811 drcayan@usgs.gov","orcid":"https://orcid.org/0000-0002-2719-6811","contributorId":1494,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","email":"drcayan@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":477761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Michael D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":31743,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael D.","affiliations":[],"preferred":false,"id":477763,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pierce, David W.","contributorId":26953,"corporation":false,"usgs":true,"family":"Pierce","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":477762,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70041498,"text":"70041498 - 2013 - Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries","interactions":[],"lastModifiedDate":"2013-07-01T11:40:22","indexId":"70041498","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries","docAbstract":"The northern fulmar Fulmarus glacialis is one of the most visible and widespread seabirds in the eastern Bering Sea and Aleutian Islands. However, relatively little is known about its abundance, trends, or the factors that shape its distribution. We used a long-term pelagic dataset to model changes in fulmar at-sea distribution and abundance since the mid-1970s. We used an ensemble model, based on a weighted average of generalized additive model (GAM), multivariate adaptive regression splines (MARS), and random forest models to estimate the pelagic distribution and density of fulmars in the waters of the Aleutian Archipelago and Bering Sea. The most important predictor variables were colony effect, sea surface temperature, distribution of fisheries, location, and primary productivity. We calculated a time series from the ratio of observed to predicted values and found that fulmar at-sea abundance declined from the 1970s to the 2000s at a rate of 0.83% (± 0.39% SE) per annum. Interpolating fulmar densities on a spatial grid through time, we found that the center of fulmar distribution in the Bering Sea has shifted north, coinciding with a northward shift in fish catches and a warming ocean. Our study shows that fisheries are an important, but not the only factor, shaping fulmar distribution and abundance trends in the eastern Bering Sea and Aleutian Islands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ecology Progress Series","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research","doi":"10.3354/meps10347","usgsCitation":"Renner, M., Parrish, J.K., Piatt, J.F., Kuletz, K.J., Edwards, A.E., and Hunt, G.L., 2013, Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries: Marine Ecology Progress Series, v. 484, p. 259-277, https://doi.org/10.3354/meps10347.","productDescription":"19 p.","startPage":"259","endPage":"277","ipdsId":"IP-040194","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10347","text":"Publisher Index Page"},{"id":274354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274353,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps10347"}],"otherGeospatial":"Bering Sea;Aleutian Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 161.98,51.2 ], [ 161.98,66.05 ], [ -150.9,66.05 ], [ -150.9,51.2 ], [ 161.98,51.2 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296d7e4b0ca18483389ab","contributors":{"authors":[{"text":"Renner, Martin","contributorId":18648,"corporation":false,"usgs":true,"family":"Renner","given":"Martin","affiliations":[],"preferred":false,"id":469852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Julia K.","contributorId":47270,"corporation":false,"usgs":true,"family":"Parrish","given":"Julia","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":469854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":469851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuletz, Kathy J.","contributorId":24669,"corporation":false,"usgs":true,"family":"Kuletz","given":"Kathy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Ann E.","contributorId":62110,"corporation":false,"usgs":true,"family":"Edwards","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":469856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunt, George L. Jr.","contributorId":56953,"corporation":false,"usgs":true,"family":"Hunt","given":"George","suffix":"Jr.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":469855,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70094393,"text":"70094393 - 2013 - Framing scenarios of binational water policy with a tool to visualize, quantify and valuate changes in ecosystem services","interactions":[],"lastModifiedDate":"2014-02-20T09:09:04","indexId":"70094393","displayToPublicDate":"2013-06-28T08:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Framing scenarios of binational water policy with a tool to visualize, quantify and valuate changes in ecosystem services","docAbstract":"In the Santa Cruz Watershed, located on the Arizona-Sonora portion of the U.S.-Mexico border, an international wastewater treatment plant treats wastewater from cities on both sides of the border, before discharging it into the river in Arizona. These artificial flows often subsidize important perennial surface water ecosystems in the region. An explicit understanding of the benefits of maintaining instream flow for present and future generations requires the ability to assess and understand the important trade-offs implicit in water-resource management decisions. In this paper, we outline an approach for modeling and visualizing impacts of management decisions in terms of rare terrestrial and aquatic wildlife, vegetation, surface water, groundwater recharge, real-estate values and socio-environmental vulnerable communities. We identify and quantify ecosystem services and model the potential reduction in effluent discharge to the U.S. that is under scrutiny by binational water policy makers and of concern to stakeholders. Results of service provisioning are presented, and implications for policy makers and resource managers are discussed. This paper presents a robust ecosystem services assessment of multiple scenarios of watershed management as a means to discern eco-hydrological responses and consider their potential values for future generations living in the borderlands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI AG","publisherLocation":"Basel, Switzerland","doi":"10.3390/w5030852","usgsCitation":"Norman, L.M., Villarreal, M., Niraula, R., Meixner, T., Frisvold, G., and Labiosa, W., 2013, Framing scenarios of binational water policy with a tool to visualize, quantify and valuate changes in ecosystem services: Water, v. 5, no. 3, p. 852-874, https://doi.org/10.3390/w5030852.","productDescription":"23 p.","startPage":"852","endPage":"874","numberOfPages":"23","ipdsId":"IP-039107","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473725,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w5030852","text":"Publisher Index Page"},{"id":282558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282557,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/w5030852"}],"country":"Mexico;United States","state":"Arizona;Sonora","county":"Santa Cruz County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.6156,30.8551 ], [ -111.6156,32.875 ], [ -109.9786,32.875 ], [ -109.9786,30.8551 ], [ -111.6156,30.8551 ] ] ] } } ] }","volume":"5","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-06-28","publicationStatus":"PW","scienceBaseUri":"53cd5a44e4b0b290850f93e1","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":490596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":490601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niraula, Rewati","contributorId":100714,"corporation":false,"usgs":false,"family":"Niraula","given":"Rewati","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":490600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meixner, Thomas","contributorId":22653,"corporation":false,"usgs":false,"family":"Meixner","given":"Thomas","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":490598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frisvold, George","contributorId":9569,"corporation":false,"usgs":true,"family":"Frisvold","given":"George","email":"","affiliations":[],"preferred":false,"id":490597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Labiosa, William","contributorId":26421,"corporation":false,"usgs":true,"family":"Labiosa","given":"William","affiliations":[],"preferred":false,"id":490599,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046718,"text":"ofr20131142 - 2013 - The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09","interactions":[],"lastModifiedDate":"2013-06-28T11:49:19","indexId":"ofr20131142","displayToPublicDate":"2013-06-28T00:00:00","publicationYear":"2013","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":"2013-1142","title":"The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09","docAbstract":"Juvenile Chinook salmon (Oncorhynchus tshawytscha) emigrating from natal tributaries of the Sacramento River may use a number of migration routes to navigate the Sacramento-San Joaquin River Delta (hereafter called “the Delta”), each of which may influence their probability of surviving. We applied a mark-recapture model to data from acoustically tagged juvenile late fall-run Chinook salmon that migrated through the Delta during the winter of 2008–09 to estimate route entrainment, survival, and migration times through the Delta.\n\nA tag-life study was conducted to determine the potential for premature tag failure. Tag failure began after 12 days and continued until the 45th day. Travel times of tagged fish exceeded minimum tag-failure times, indicating that survival estimates obtained from this study were negatively biased due to tag failure prior to fish exiting the Delta. Survival estimates were not adjusted and represent the joint probability of tag survival and fish survival. However, relative comparisons of survival among Chinook salmon choosing different routes appeared to be robust to tag failure, and migration-routing parameters were unaffected by tag failure.\n\nMigration-routing patterns were consistent among release groups. The Sacramento River was the primary migration route for all release groups except one. The percentage of fish entering the Sacramento River ranged from 33 to 55 percent. Sutter and Steamboat Sloughs were the secondary migration route for 9 of the 10 releases. The percentage of fish migrating through this route ranged from 10 to 35 percent. Entrainment into the interior Delta ranged from 15 to 33 percent. The Delta Cross Channel gates were open for 7 of the 10 releases. Entrainment into the interior Delta through the cross channel ranged from 1 to 27 percent.\n\nWe estimated route-specific survival for 10 release groups that were released between November 14, 2008, and January 19, 2009. Population-level survival through the Delta (SDelta) ranged from 0.019 (standard error of 0.012) to 0.277 (standard error of 0.041) among releases, which represent the probability of a fish surviving from Sacramento to Chipps Island with an operational transmitter. Sacramento River flows throughout the study period were approximately 8,000–15,000 cubic feet per second at Freeport, suggesting that variability in flow contributed little to differences in survival between releases. Fish migrating through the Sacramento River had the highest survival for most releases. Survival in Sutter and Steamboat Sloughs was slightly lower than survival in the Sacramento River for 7 of the 10 releases, but higher than survival in the Sacramento River for 3 releases. Survival in the interior Delta was lowest for all release groups except for one release in November. With the exception of this November release, survival patterns across release groups were similar to those of previous studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131142","collaboration":"Prepared in cooperation with the California Department of Water Resources and Bureau of Reclamation","usgsCitation":"Romine, J.G., Perry, R.W., Brewer, S.J., Adams, N.S., Liedtke, T.L., Blake, A.R., and Burau, J.R., 2013, The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09: U.S. Geological Survey Open-File Report 2013-1142, vi, 36 p., https://doi.org/10.3133/ofr20131142.","productDescription":"vi, 36 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-11-14","temporalEnd":"2009-01-19","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":274296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131142.jpg"},{"id":274293,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1142/"},{"id":274294,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1142/pdf/ofr20131142_appendixD.zip"},{"id":274295,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1142/pdf/ofr20131142.pdf"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,37.833333 ], [ -122.0,38.583333 ], [ -121.333333,38.583333 ], [ -121.333333,37.833333 ], [ -122.0,37.833333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cea255e4b044272b8e890a","contributors":{"authors":[{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Scott J. sbrewer@usgs.gov","contributorId":4407,"corporation":false,"usgs":true,"family":"Brewer","given":"Scott","email":"sbrewer@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":480084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480082,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Aaron R. 0000-0001-7348-2336 ablake@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-2336","contributorId":5059,"corporation":false,"usgs":true,"family":"Blake","given":"Aaron","email":"ablake@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046720,"text":"sir20135069 - 2013 - Conceptual and numerical models of groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties, South Dakota, water years 1985--2009","interactions":[],"lastModifiedDate":"2017-10-14T11:17:29","indexId":"sir20135069","displayToPublicDate":"2013-06-28T00:00:00","publicationYear":"2013","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":"2013-5069","title":"Conceptual and numerical models of groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties, South Dakota, water years 1985--2009","docAbstract":"The Ogallala aquifer is an important water resource for the Rosebud Sioux Tribe in Gregory and Tripp Counties in south-central South Dakota and is used for irrigation, public supply, domestic, and stock water supplies. To better understand groundwater flow in the Ogallala aquifer, conceptual and numerical models of groundwater flow were developed for the aquifer. A conceptual model of the Ogallala aquifer was used to analyze groundwater flow and develop a numerical model to simulate groundwater flow in the aquifer. The MODFLOW–NWT model was used to simulate transient groundwater conditions for water years 1985–2009. The model was calibrated using statistical parameter estimation techniques. Potential future scenarios were simulated using the input parameters from the calibrated model for simulations of potential future drought and future increased pumping.\n\nTransient simulations were completed with the numerical model. A 200-year transient initialization period was used to establish starting conditions for the subsequent 25-year simulation of water years 1985–2009. The 25-year simulation was discretized into three seasonal stress periods per year and used to simulate transient conditions.\n\nA single-layer model was used to simulate flow and mass balance in the Ogallala aquifer with a grid of 133 rows and 282 columns and a uniform spacing of 500 meters (1,640 feet). Regional inflow and outflow were simulated along the western and southern boundaries using specified-head cells. All other boundaries were simulated using no-flow cells. Recharge to the aquifer occurs through precipitation on the outcrop area.\n\nModel calibration was accomplished using the Parameter Estimation (PEST) program that adjusted individual model input parameters and assessed the difference between estimated and model-simulated values of hydraulic head and base flow. This program was designed to estimate parameter values that are statistically the most likely set of values to result in the smallest differences between simulated and observed values, within a given set of constraints. The potentiometric surface of the aquifer calculated during the 200-year initialization period established initial conditions for the transient simulation. Water levels for 38 observation wells were used to calibrate the 25-year simulation. Simulated hydraulic heads for the transient simulation were within plus or minus 20 feet of observed values for 95 percent of observation wells, and the mean absolute difference was 5.1 feet. Calibrated hydraulic conductivity ranged from 0.9 to 227 feet per day (ft/d).\n\nThe annual recharge rates for the transient simulation (water years 1985–2009) ranged from 0.60 to 6.96 inches, with a mean of 3.68 inches for the Ogallala aquifer. This represents a mean recharge rate of 280.5 ft3/s for the model area. Discharge from the aquifer occurs through evapotranspiration, discharge to streams through river leakage and flow from springs and seeps, and well withdrawals. Water is withdrawn from wells for irrigation, public supply, domestic, and stock uses. Simulated mean discharge rates for water years 1985–2009 were about 185 cubic feet per second (ft3/s) for evapotranspiration, 66.7 ft3/s for discharge to streams, and 5.48 ft3/s for well withdrawals. Simulated annual evapotranspiration rates ranged from about 128 to 254 ft3/s, and outflow to streams ranged from 52.2 to 79.9 ft3/s.\n\nA sensitivity analysis was used to examine the response of the calibrated model to changes in model parameters for horizontal hydraulic conductivity, recharge, evapotranspiration, and spring and riverbed conductance. The model was most sensitive to recharge and maximum potential evapotranspiration and least sensitive to riverbed and spring conductances.\n\nTwo potential future scenarios were simulated: a potential drought scenario and a potential increased pumping scenario. To simulate a potential drought scenario, a synthetic drought record was created, the mean of which was equal to 60 percent of the mean estimated recharge rate for the 25-year simulation period. Compared with the results of the calibrated model (non-drought simulation), the simulation representing a potential drought scenario resulted in water-level decreases of as much as 30 feet for the Ogallala aquifer. To simulate the effects of potential future increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 25-year simulation period. Compared with the results of the calibrated model, the simulation representing an increased pumping scenario resulted in water-level decreases of as much as 26 feet for the Ogallala aquifer.\n\nGroundwater budgets for the potential future scenario simulations were compared with the transient simulation representing water years 1985–2009. The simulation representing a potential drought scenario resulted in lower aquifer recharge from precipitation and decreased discharge from streams, springs, seeps, and evapotranspiration. The simulation representing a potential increased pumping scenario was similar to results from the transient simulation, with a slight increase in well withdrawals and a slight decrease in discharge from river leakage and evapotranspiration.\n\nThis numerical model is suitable as a tool that could be used to better understand the flow system of the Ogallala aquifer, to approximate hydraulic heads in the aquifer, and to estimate discharge to rivers, springs, and seeps in the study area. The model also is useful to help assess the response of the aquifer to additional stresses, including potential drought conditions and increased well withdrawals.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135069","collaboration":"Prepared in cooperation with the Rosebud Sioux Tribe","usgsCitation":"Davis, K.W., and Putnam, L.D., 2013, Conceptual and numerical models of groundwater flow in the Ogallala aquifer in Gregory and Tripp Counties, South Dakota, water years 1985--2009: U.S. Geological Survey Scientific Investigations Report 2013-5069, viii, 82 p., https://doi.org/10.3133/sir20135069.","productDescription":"viii, 82 p.","numberOfPages":"94","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1984-10-31","temporalEnd":"2009-09-03","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":274304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135069.gif"},{"id":274302,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5069/"},{"id":274303,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5069/sir13-5069.pdf"}],"country":"United States","state":"South Dakota","county":"Gregory County;Tripp County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.2333,42.9979 ], [ -100.2333,43.7619 ], [ -98.4985,43.7619 ], [ -98.4985,42.9979 ], [ -100.2333,42.9979 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f2bbe4b0bc0bec0a056b","contributors":{"authors":[{"text":"Davis, Kyle W. 0000-0002-8723-0110 kyledavis@usgs.gov","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":3987,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle","email":"kyledavis@usgs.gov","middleInitial":"W.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":480089,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046705,"text":"ds762 - 2013 - Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina","interactions":[],"lastModifiedDate":"2013-06-26T13:05:09","indexId":"ds762","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"762","title":"Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina","docAbstract":"Geologic mapping, the collection of borehole geophysical logs and images, and passive diffusion bag sampling were conducted by the U.S. Geological Survey North Carolina Water Science Center in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina, during March through October 2011. The study purpose was to assist the U.S. Environmental Protection Agency in the development of a conceptual groundwater model for the assessment of current contaminant distribution and future migration of contaminants. Data compilation efforts included geologic mapping of more than 250 features, including rock type and secondary joints, delineation of more than 1,300 subsurface features (primarily fracture orientations) in 15 open borehole wells, and the collection of passive diffusion-bag samples from 42 fracture zones at various depths in the 15 wells.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds762","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Chapman, M.J., Clark, T.W., and Williams, J., 2013, Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina: U.S. Geological Survey Data Series 762, Report: viii, 37 p.; Appendixes 1-8, https://doi.org/10.3133/ds762.","productDescription":"Report: viii, 37 p.; Appendixes 1-8","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":274259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds762.gif"},{"id":274258,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/762/appendix"},{"id":274256,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/762/"},{"id":274257,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/762/pdf/ds762.pdf"}],"country":"United States","state":"North Carolina","city":"Roxboro","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.32,33.84 ], [ -84.32,36.58 ], [ -75.46,36.58 ], [ -75.46,33.84 ], [ -84.32,33.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff54e4b052f2a4539863","contributors":{"authors":[{"text":"Chapman, Melinda J. 0000-0003-4021-0320 mjchap@usgs.gov","orcid":"https://orcid.org/0000-0003-4021-0320","contributorId":1597,"corporation":false,"usgs":true,"family":"Chapman","given":"Melinda","email":"mjchap@usgs.gov","middleInitial":"J.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":480048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Timothy W.","contributorId":104377,"corporation":false,"usgs":true,"family":"Clark","given":"Timothy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":480049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046704,"text":"ds778 - 2013 - SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data","interactions":[],"lastModifiedDate":"2013-06-26T09:52:58","indexId":"ds778","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"778","title":"SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data","docAbstract":"SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (SSRs; for example, microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains three analysis modules along with a fourth control module that can be used to automate analyses of large volumes of data. The modules are used to (1) identify the subset of paired-end sequences that pass quality standards, (2) align paired-end reads into a single composite DNA sequence, and (3) identify sequences that possess microsatellites conforming to user specified parameters. Each of the three separate analysis modules also can be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc).\n\nAll modules are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, Windows). The program suite relies on a compiled Python extension module to perform paired-end alignments. Instructions for compiling the extension from source code are provided in the documentation. Users who do not have Python installed on their computers or who do not have the ability to compile software also may choose to download packaged executable files. These files include all Python scripts, a copy of the compiled extension module, and a minimal installation of Python in a single binary executable. See program documentation for more information.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds778","usgsCitation":"Miller, M.P., Knaus, B.J., Mullins, T., and Haig, S.M., 2013, SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data: U.S. Geological Survey Data Series 778, HTML Document; Program Documentation; Program Executable Files, https://doi.org/10.3133/ds778.","productDescription":"HTML Document; Program Documentation; Program Executable Files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":274247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds778.jpg"},{"id":274240,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/01_SSR_pipeline_0.95_src_and_docs.tgz"},{"id":274241,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/03_SSR_pipeline_sample_data.zip"},{"id":274238,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/778/"},{"id":274242,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/04_SSR_pipeline_documentation.pdf"},{"id":274239,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/02_SSR_pipeline_0.95_src_and_docs.zip"},{"id":274243,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/05_SSR_pipeline_0.95_win32_executeables.zip"},{"id":274244,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/08_SSR_pipeline_0.95_32bit_linux.tar.gz"},{"id":274245,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/06_SSR_pipeline_0.95_64bit_linux.tar.gz"},{"id":274246,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/07_SSR_pipeline_0.95_OSX64bit.tar.gz"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff57e4b052f2a453988b","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":480044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knaus, Brian J.","contributorId":107167,"corporation":false,"usgs":true,"family":"Knaus","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":480045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","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":480043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}