{"pageNumber":"475","pageRowStart":"11850","pageSize":"25","recordCount":40783,"records":[{"id":70175747,"text":"70175747 - 2016 - Methods for exploring uncertainty in groundwater management predictions","interactions":[],"lastModifiedDate":"2016-09-01T13:13:07","indexId":"70175747","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Methods for exploring uncertainty in groundwater management predictions","docAbstract":"

Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Integrated groundwater management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-23576-9_28","isbn":"978-3-319-23575-2","usgsCitation":"Guillaume, J.H., Hunt, R.J., Comunian, A., Fu, B., and Blakers, R.S., 2016, Methods for exploring uncertainty in groundwater management predictions, chap. of Integrated groundwater management, p. 711-737, https://doi.org/10.1007/978-3-319-23576-9_28.","productDescription":"27 p.","startPage":"711","endPage":"737","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057337","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":488538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-319-23576-9_28","text":"Publisher Index Page"},{"id":328111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1a9e4b0f2f0cebf11a9","contributors":{"editors":[{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":647604,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Barreteau, Olivier","contributorId":173849,"corporation":false,"usgs":false,"family":"Barreteau","given":"Olivier","email":"","affiliations":[{"id":27301,"text":"IRSTEA - UMR G-EAU (France)","active":true,"usgs":false}],"preferred":false,"id":647605,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647606,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Rinaudo, Jean-Daniel","contributorId":173850,"corporation":false,"usgs":false,"family":"Rinaudo","given":"Jean-Daniel","email":"","affiliations":[{"id":27302,"text":"BRGM (France)","active":true,"usgs":false}],"preferred":false,"id":647607,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Ross, Andrew","contributorId":173851,"corporation":false,"usgs":false,"family":"Ross","given":"Andrew","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":647608,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Guillaume, Joseph H. A.","contributorId":173856,"corporation":false,"usgs":false,"family":"Guillaume","given":"Joseph","email":"","middleInitial":"H. A.","affiliations":[{"id":6718,"text":"Aalto University, Finland","active":true,"usgs":false}],"preferred":false,"id":646295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Comunian, Alessandro","contributorId":173857,"corporation":false,"usgs":false,"family":"Comunian","given":"Alessandro","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":646296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fu, Baihua 0000-0003-2494-0518","orcid":"https://orcid.org/0000-0003-2494-0518","contributorId":174165,"corporation":false,"usgs":false,"family":"Fu","given":"Baihua","email":"","affiliations":[],"preferred":false,"id":647603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakers, Rachel S","contributorId":173858,"corporation":false,"usgs":false,"family":"Blakers","given":"Rachel","email":"","middleInitial":"S","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":646297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176185,"text":"70176185 - 2016 - Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","interactions":[],"lastModifiedDate":"2016-08-31T14:46:03","indexId":"70176185","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","docAbstract":"

Estimating streamwater solute loads is a central objective of many water-quality monitoring and research studies, as loads are used to compare with atmospheric inputs, to infer biogeochemical processes, and to assess whether water quality is improving or degrading. In this study, we evaluate loads and associated errors to determine the best load estimation technique among three methods (a period-weighted approach, the regression-model method, and the composite method) based on a solute's concentration dynamics and sampling frequency. We evaluated a broad range of varying concentration dynamics with stream flow and season using four dissolved solutes (sulfate, silica, nitrate, and dissolved organic carbon) at five diverse small watersheds (Sleepers River Research Watershed, VT; Hubbard Brook Experimental Forest, NH; Biscuit Brook Watershed, NY; Panola Mountain Research Watershed, GA; and Río Mameyes Watershed, PR) with fairly high-frequency sampling during a 10- to 11-yr period. Data sets with three different sampling frequencies were derived from the full data set at each site (weekly plus storm/snowmelt events, weekly, and monthly) and errors in loads were assessed for the study period, annually, and monthly. For solutes that had a moderate to strong concentration–discharge relation, the composite method performed best, unless the autocorrelation of the model residuals was <0.2, in which case the regression-model method was most appropriate. For solutes that had a nonexistent or weak concentration–discharge relation (modelR2 < about 0.3), the period-weighted approach was most appropriate. The lowest errors in loads were achieved for solutes with the strongest concentration–discharge relations. Sample and regression model diagnostics could be used to approximate overall accuracies and annual precisions. For the period-weighed approach, errors were lower when the variance in concentrations was lower, the degree of autocorrelation in the concentrations was higher, and sampling frequency was higher. The period-weighted approach was most sensitive to sampling frequency. For the regression-model and composite methods, errors were lower when the variance in model residuals was lower. For the composite method, errors were lower when the autocorrelation in the residuals was higher. Guidelines to determine the best load estimation method based on solute concentration–discharge dynamics and diagnostics are presented, and should be applicable to other studies.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1298","usgsCitation":"Aulenbach, B.T., Burns, D.A., Shanley, J.B., Yanai, R.D., Bae, K., Wild, A., Yang, Y., and Yi, D., 2016, Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed: Ecosphere, v. 7, no. 6, e01298; 22 p., https://doi.org/10.1002/ecs2.1298.","productDescription":"e01298; 22 p.","ipdsId":"IP-065579","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1298","text":"Publisher Index Page"},{"id":328145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"57c7f1a3e4b0f2f0cebf119f","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yanai, Ruth D.","contributorId":59720,"corporation":false,"usgs":true,"family":"Yanai","given":"Ruth","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bae, Kikang","contributorId":174183,"corporation":false,"usgs":false,"family":"Bae","given":"Kikang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wild, Adam","contributorId":174184,"corporation":false,"usgs":false,"family":"Wild","given":"Adam","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yang, Yang","contributorId":174185,"corporation":false,"usgs":false,"family":"Yang","given":"Yang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yi, Dong","contributorId":174186,"corporation":false,"usgs":false,"family":"Yi","given":"Dong","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647656,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176162,"text":"70176162 - 2016 - Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","interactions":[],"lastModifiedDate":"2016-09-16T16:21:53","indexId":"70176162","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","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":"Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","docAbstract":"

Question

How closely do plant communities track climate? Research suggests that plant species converge toward similar environmental tolerances relative to the environments that they experience. Whether these patterns apply to severe environments or scale up to plant community-level patterns of relative climatic tolerances is poorly understood. Using estimates of species' climatic tolerances acquired from occurrence records, we determined the contributions of individual species' climatic niche breadths and environmental filtering to the relationships between community-average climatic tolerances and the local climates experienced by those communities.

Location

Southwestern United States drylands.

Methods

Interspecific variation in niche breadth was assessed as a function of species' climatic optima (median climatic niche value). The relationships between climatic optima and tolerances were used as null expectations for the relationship between abundance-weighted mean climatic tolerances of communities and the local climate of that community. Deviations from this null expectation indicate that species with greater or lesser climatic tolerances are favoured relative to co-occurring species. The intensity of environmental filtering was estimated by comparing the range of climatic tolerances within each community to a null distribution generated from a random assembly algorithm.

Results

The temperature niches of species were consistently symmetrical and of similar breadths, regardless of their temperature optima. In contrast, precipitation niches were skewed toward wetter conditions, and niche breadth increased with increasing precipitation optima. At the community level, relationships with climate were much stronger for temperature than for precipitation. Furthermore, cold and heat were stronger assembly filters than drought or precipitation, with the intensity of environmental filtering increasing at both ends of climatic gradients. Community-average climatic tolerances did deviate significantly from null expectations, indicating that species with higher or lower relative climatic tolerances were favoured under certain conditions.

Conclusions

Despite strong water limitation of plant performance in dryland ecosystems, communities tracked variation in temperature much more closely, intimating strong responses to anticipated temperature increases. Furthermore, abundance distributions were biased toward species with higher or lower relative climatic tolerances under different climatic conditions, but predictably so, indicating the need for assembly models that include processes other than simple environmental filtering.

","language":"English","publisher":"International Association for Vegetation Science","publisherLocation":"Uppsala, Sweden","doi":"10.1111/jvs.12440","usgsCitation":"Butterfield, B.J., and Munson, S.M., 2016, Temperature is better than precipitation as a predictor of plant community assembly across a dryland region: Journal of Vegetation Science, v. 27, no. 5, p. 938-947, https://doi.org/10.1111/jvs.12440.","productDescription":"10 p.","startPage":"938","endPage":"947","ipdsId":"IP-060796","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"27","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-04","publicationStatus":"PW","scienceBaseUri":"57c7f1afe4b0f2f0cebf11b7","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":647521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":647520,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176125,"text":"70176125 - 2016 - Allometric and temporal scaling of movement characteristics in Galapagos tortoises","interactions":[],"lastModifiedDate":"2016-08-29T10:33:53","indexId":"70176125","displayToPublicDate":"2016-08-29T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Allometric and temporal scaling of movement characteristics in Galapagos tortoises","docAbstract":"
  1. Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs.
  2. We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour – giant Galapagos tortoises (Chelonoidis spp.) – to test how movement metrics estimated on a monthly basis scaled with body size.
  3. We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex.
  4. Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates.
  5. Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12561","usgsCitation":"Bastille-Rousseau, G., Yackulic, C.B., Frair, J.L., Cabrera, F., and Blake, S., 2016, Allometric and temporal scaling of movement characteristics in Galapagos tortoises: Journal of Animal Ecology, v. 85, no. 5, p. 1171-1181, https://doi.org/10.1111/1365-2656.12561.","productDescription":"11 p.","startPage":"1171","endPage":"1181","ipdsId":"IP-066348","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470637,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12561","text":"Publisher Index Page"},{"id":327985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-21","publicationStatus":"PW","scienceBaseUri":"57c54e9ce4b0f2f0cebc9862","contributors":{"authors":[{"text":"Bastille-Rousseau, Guillaume","contributorId":169986,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","affiliations":[{"id":25645,"text":"State Uni. of New York","active":true,"usgs":false}],"preferred":false,"id":647271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frair, Jacqueline L.","contributorId":140184,"corporation":false,"usgs":false,"family":"Frair","given":"Jacqueline","email":"","middleInitial":"L.","affiliations":[{"id":13404,"text":"SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":647272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cabrera, Freddy","contributorId":174102,"corporation":false,"usgs":false,"family":"Cabrera","given":"Freddy","email":"","affiliations":[],"preferred":false,"id":647273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blake, Stephen","contributorId":65339,"corporation":false,"usgs":false,"family":"Blake","given":"Stephen","email":"","affiliations":[{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false},{"id":30787,"text":"Saint Louis University","active":true,"usgs":false}],"preferred":false,"id":647274,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176124,"text":"70176124 - 2016 - Toward an integrated understanding of perceived biodiversity values and environmental conditions in a national park","interactions":[],"lastModifiedDate":"2016-08-31T11:11:52","indexId":"70176124","displayToPublicDate":"2016-08-29T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Toward an integrated understanding of perceived biodiversity values and environmental conditions in a national park","docAbstract":"

In spatial planning and management of protected areas, increased priority is being given to research that integrates social and ecological data. However, public viewpoints of the benefits provided by ecosystems are not easily quantified and often implicitly folded into natural resource management decisions. Drawing on a spatially explicit participatory mapping exercise and a Social Values for Ecosystem Services (SolVES) analysis tool, the present study empirically examined and integrated social values for ecosystem services and environmental conditions within Channel Islands National Park, California. Specifically, a social value indicator of perceived biodiversity was examined using on-site survey data collected from a sample of people who visited the park. This information was modeled alongside eight environmental conditions including faunal species richness for six taxa, vegetation density, categories of marine and terrestrial land cover, and distance to features relevant for decision-makers. Results showed that biodiversity value points assigned to places by the pooled sample of respondents were widely and unevenly mapped, which reflected the belief that biodiversity was embodied to varying degrees by multiple locations in the park. Models generated for two survey subgroups defined by their self-reported knowledge of the Channels Islands revealed distinct spatial patterns of these perceived values. Specifically, respondents with high knowledge valued large spaces that were publicly inaccessible and unlikely to contain on-ground biodiversity, whereas respondents with low knowledge valued places that were experienced first-hand. Accessibility and infrastructure were also important considerations for anticipating how and where people valued the protected land and seascapes of Channel Islands National Park.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.07.029","usgsCitation":"van Riper, C.J., Kyle, G.T., Sherrouse, B.C., Bagstad, K.J., and Sutton, S., 2016, Toward an integrated understanding of perceived biodiversity values and environmental conditions in a national park: Ecological Indicators, v. 72, p. 278-287, https://doi.org/10.1016/j.ecolind.2016.07.029.","productDescription":"10 p.","startPage":"278","endPage":"287","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058049","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":327978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands National Park, Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":647265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":647269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sutton, Stephen G.","contributorId":14685,"corporation":false,"usgs":true,"family":"Sutton","given":"Stephen G.","affiliations":[],"preferred":false,"id":647268,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175738,"text":"ofr20161138 - 2016 - Time-slice maps showing age, distribution, and style of deformation in Alaska north of 60° N.","interactions":[],"lastModifiedDate":"2016-08-30T10:14:32","indexId":"ofr20161138","displayToPublicDate":"2016-08-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1138","title":"Time-slice maps showing age, distribution, and style of deformation in Alaska north of 60° N.","docAbstract":"
The structural architecture of Alaska is the product of a complex history of tectonism that occurred along the Cordilleran and Arctic margins of North America through interactions with ancient and modern ocean plates and with continental elements derived from Laurentia, Siberia, and Baltica. To unravel the tectonic history of Alaska, we constructed maps showing the age, distribution, structural style, and kinematics of contractional and penetrative extensional deformation in Alaska north of latitude 60° N. at a scale of 1:5,000,000. These maps use the Geologic Map of the Arctic (Harrison and others, 2011) as a base map and follow the guidelines in the Tectonic Map of the Arctic project (Petrov and others, 2013) for construction, including use of the International Commission on Stratigraphy time scale (Cohen and others, 2013) divided into 20 time intervals. We find evidence for deformation in 14 of the 20 time intervals and present maps showing the known or probable extent of deformation for each time interval. Maps and descriptions of deformational style, age constraints, kinematics, and information sources for each deformational episode are discussed in the text and are reported in tabular form. This report also contains maps showing the lithologies and structural geology of Alaska, a terrane map, and the distribution of tectonically important units including post-tectonic sedimentary basins, accretionary complexes, ophiolites, metamorphic rocks.

These new maps show that most deformational belts in Alaska are relatively young features, having developed during the late Mesozoic and Cenozoic. The oldest episode of deformation recognized anywhere in Alaska is found in the basement of the Farewell terrane (~1.75 Ga). Paleozoic and early Mesozoic deformational events, including Devonian deformation in the Arctic Alaska terrane, Pennsylvanian deformation in the Alexander terrane, Permian deformation in the Yukon Composite (Klondike orogeny) and Farewell terranes (Browns Fork orogeny), Early and Late Jurassic deformation in the Peninsular-Wrangellia terranes, and Early Cretaceous deformation in northern Alaska (early Brookian orogeny) show that within-terrane amalgamation events occurred prior to assembly of Alaska. Widespread episodes of deformation in the Late Cretaceous and early Cenozoic, in contrast, affected multiple terranes, indicating they occurred during or following the time of assembly of most of Alaska.

The primary deformational event in northern Alaska was the Late Jurassic and Early Cretaceous (early) Brookian orogeny, which affected most terranes north and west of the early Cenozoic Tintina, Victoria Creek, Kaltag, and Poorman dextral-slip faults in central Alaska. In southern Alaska, formation of the southern Alaska accretionary complex (Chugach, Prince William, Yakutat terranes) and associated magmatism in the Peninsular-Wrangellia terrane began near the Triassic-Jurassic boundary and continued episodically throughout the remainder of the Mesozoic and the Cenozoic. The collision of these terranes with the Farewell and Yukon Composite terranes in central Alaska is recorded by contractional deformation that emanated from the intervening basins in the Late Cretaceous. The boundary between northern and central Alaska is constrained to late Early Cretaceous but is enigmatic and not obviously marked by contractional deformation. Early Cenozoic shortening and transpressional deformation is the most widespread event recorded in Alaska and produced the widespread late Brookian orogenic event in northern Alaska. Middle and late Cenozoic shortening and transpression is significant in southern Alaska inboard of the underthrusting Yakutat terrane at the Pacific margin subduction zone as well as in northeastern Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161138","usgsCitation":"Moore, T.E., and Box, S.E., 2016, Time-slice maps showing age, distribution, and style of deformation in Alaska north of 60° N.: U.S. Geological Survey Open-File Report 2016–1138, 101 p., https://dx.doi.org/10.3133/ofr20161138.","productDescription":"Report: v, 101 p.; 2 Tables","numberOfPages":"107","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059567","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":327913,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1138/coverth.jpg"},{"id":327368,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1138/ofr20161138.pdf","text":"Report","size":"61.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1138"},{"id":327369,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1138/ofr20161138_table1.xlsx","text":"Table 1","size":"41 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1138 Table 1"},{"id":327370,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1138/ofr20161138_table2.xlsx","text":"Table 2","size":"34 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1138 Table 2"}],"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 -139.06494140625,\n 59.99898612060444\n ],\n [\n -139.21874999999997,\n 60.08676274626006\n ],\n [\n -139.053955078125,\n 60.34869562531862\n ],\n [\n -139.713134765625,\n 60.337823495982015\n ],\n [\n -139.98779296875,\n 60.19069475310575\n ],\n [\n -140.47119140625,\n 60.31606836555203\n ],\n [\n -140.51513671875,\n 60.22890276751329\n ],\n [\n -141.009521484375,\n 60.310627317400424\n ],\n [\n -141.15234374999997,\n 71.52490903732816\n ],\n [\n -169.716796875,\n 71.51097803770108\n ],\n [\n -169.4970703125,\n 65.73062649311031\n ],\n [\n -172.529296875,\n 63.724183392123315\n ],\n [\n -175.4296875,\n 59.99898612060444\n ],\n [\n -139.06494140625,\n 59.99898612060444\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Geology, Minerals, Energy, and Geophysics Science Center
U.S. Geological Survey
345 Middlefield Road, MS 901
Menlo Park, CA 94025-3591
http://geomaps.wr.usgs.gov/gmeg/
","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-08-29","noUsgsAuthors":false,"publicationDate":"2016-08-29","publicationStatus":"PW","scienceBaseUri":"57c54ea0e4b0f2f0cebc9870","contributors":{"authors":[{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":1033,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":646244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":646245,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175507,"text":"ofr20161134 - 2016 - Centimeter-scale surface deformation caused by the 2011 Mineral, Virginia, earthquake sequence at the Carter farm site—Subsidiary structures with a quaternary history","interactions":[],"lastModifiedDate":"2016-09-12T09:58:17","indexId":"ofr20161134","displayToPublicDate":"2016-08-25T08:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1134","title":"Centimeter-scale surface deformation caused by the 2011 Mineral, Virginia, earthquake sequence at the Carter farm site—Subsidiary structures with a quaternary history","docAbstract":"

Centimeter-scale ground-surface deformation was produced by the August 23, 2011, magnitude (M) 5.8 earthquake that occurred in Mineral, Virginia. Ground-surface deformation also resulted from the earthquake aftershock sequence. This deformation occurred along a linear northeast-trend near Pendleton, Virginia. It is approximately 10 kilometers (km) northeast of the M5.8 epicenter and near the northeastern periphery of the epicentral area as defined by aftershocks. The ground-surface deformation extends over a distance of approximately 1.4 km and consists of parallel, small-scale (a few centimeters (cm) in amplitude) linear ridges and swales. Individual ridge and swale features are discontinuous and vary in length across a zone that ranges from about 20 meters (m) to less than 5 m in width. At one location, three fence posts and adjoining rails were vertically misaligned. Approximately 5 cm of uplift on one post provides a maximum estimate of vertical change from pre-earthquake conditions along the ridge and swale features. There was no change in the alignment of fence posts, indicating that deformation was entirely vertical. A broad monoclinal flexure with approximately 1 m of relief was identified by transit survey across surface deformation at the Carter farm site. There, surface deformation overlies the Carter farm fault, which is a zone of brittle faulting and fracturing along quartz veins, striking N40°E and dipping approximately 75°SE. Brecciation and shearing along this fault is interpreted as Quaternary in age because it disrupts the modern B-soil horizon. However, deformation is confined to saprolitized schist of the Ordovician Quantico Formation and the lowermost portion of overlying residuum, and is absent in the uppermost residuum and colluvial layer at the ground surface. Because there is a lack of surface shearing and very low relief, landslide processes were not a causative mechanism for the surface deformation. Two possible tectonic models and one non-tectonic model are considered: (1) tectonic, monoclinal flexuring along the Carter farm fault, probably aseismic, (2) tectonic, monoclinal flexuring related to a shallow (1–3 km) cluster of aftershocks (M2 to M3) that occurred approximately 1 to 1.5 km to the east of Carter farm, and (3) non-tectonic, differential response to seismic shaking between more-rigid quartz veins and soft residuum-saprolite under vertical motions that were created by Rayleigh surface waves radiating away from the August 23, 2011, hypocenter and propagating along strike of the Carter farm fault. These processes are not considered mutually exclusive, and all three support brittle deformation on the Carter farm fault during the Quaternary. In addition, abandoned stream valleys and active stream piracy are consistent with long-term uplift in vicinity of the Carter farm fault.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161134","usgsCitation":"Harrison, R.W., Schindler, J.S., Pavich, M.J., Horton, J.W., Jr., and Carter, M.W., 2016, Centimeter-scale surface deformation caused by the 2011 Mineral, Virginia, earthquake sequence at the Carter farm site—Subsidiary structures with a Quaternary history: U.S. Geological Survey Open-File Report 2016–1134, 18 p., https://dx.doi.org/10.3133/ofr20161134.","productDescription":"iv, 18 p.","onlineOnly":"Y","ipdsId":"IP-055730","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":327108,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1134/coverthb1.jpg"},{"id":327109,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1134/ofr20161134.pdf","text":"Report","size":"31.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1134"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.970278,\n 38.008333\n ],\n [\n -77.970278,\n 37.941667\n ],\n [\n -77.814444,\n 37.941667\n ],\n [\n -77.814444,\n 38.008333\n ],\n [\n -77.970278,\n 38.008333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egpsc/

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-08-25","noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"57c0089ae4b0f2f0ceb85657","contributors":{"authors":[{"text":"Harrison, Richard W. rharriso@usgs.gov","contributorId":544,"corporation":false,"usgs":true,"family":"Harrison","given":"Richard W.","email":"rharriso@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":645517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schindler, J. Stephen 0000-0001-9550-5957 sschindl@usgs.gov","orcid":"https://orcid.org/0000-0001-9550-5957","contributorId":3270,"corporation":false,"usgs":true,"family":"Schindler","given":"J.","email":"sschindl@usgs.gov","middleInitial":"Stephen","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":645519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pavich, Milan J. mpavich@usgs.gov","contributorId":2348,"corporation":false,"usgs":true,"family":"Pavich","given":"Milan","email":"mpavich@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":645518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton, J. Wright Jr. 0000-0001-6756-6365 whorton@usgs.gov","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":173694,"corporation":false,"usgs":true,"family":"Horton","given":"J.","suffix":"Jr.","email":"whorton@usgs.gov","middleInitial":"Wright","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":645520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":645521,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175900,"text":"ofr20161139 - 2016 - Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15","interactions":[],"lastModifiedDate":"2017-10-12T19:55:27","indexId":"ofr20161139","displayToPublicDate":"2016-08-25T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1139","title":"Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15","docAbstract":"

The U.S. Geological Survey, in cooperation with the Fargo Diversion Board of Authority, collected water-surface elevations during a range of discharges needed for calibration of hydrologic and hydraulic models for specific reaches of interest in water years 2014–15. These water-surface elevation and discharge measurement data were collected for design planning of diversion structures on the Red River of the North and Wild Rice River and the aqueduct/diversion structures on the Sheyenne and Maple Rivers. The Red River of the North and Sheyenne River reaches were surveyed six times, and discharges ranged from 276 to 6,540 cubic feet per second and from 166 to 2,040 cubic feet per second, respectively. The Wild Rice River reach also was surveyed six times during 2014 and 2015, and discharges ranged from 13 to 1,550 cubic feet per second. The Maple River reach was surveyed four times, and discharges ranged from 16.4 to 633 cubic feet per second. Water-surface elevation differences from upstream to downstream in the reaches ranged from 0.33 feet in the Red River of the North reach to 9.4 feet in the Maple River reach.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161139","collaboration":"Prepared in cooperation with the Fargo Diversion Board of Authority","usgsCitation":"Damschen, W.C., and Galloway, J.M., 2016, Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15: U.S. Geological Survey Open-File Report 2016–1139, 16 p., https://dx.doi.org/10.3133/ofr20161139.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074364","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":327822,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1139/coverthb.jpg"},{"id":327823,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1139/ofr20161139.pdf","text":"Report","size":"1.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1139"}],"country":"United States","state":"North Dakota","city":"Fargo","otherGeospatial":"Maple River, Red River of the North, Sheyenne River, Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97,\n 46.6667\n ],\n [\n -97,\n 47.10378387099161\n ],\n [\n -96.6667,\n 47.10378387099161\n ],\n [\n -96.6667,\n 46.6667\n ],\n [\n -97,\n 46.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, North Dakota Water Science Center
U.S. Geological Survey
821 E Interstate Ave
Bismarck, ND 58503

http://nd.water.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-08-25","noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"57c0089be4b0f2f0ceb85662","contributors":{"authors":[{"text":"Damschen, William C. wcdamsch@usgs.gov","contributorId":1610,"corporation":false,"usgs":true,"family":"Damschen","given":"William C.","email":"wcdamsch@usgs.gov","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176085,"text":"70176085 - 2016 - Precipitation changes in the western tropical Pacific over the past millennium","interactions":[],"lastModifiedDate":"2016-08-25T10:35:36","indexId":"70176085","displayToPublicDate":"2016-08-25T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation changes in the western tropical Pacific over the past millennium","docAbstract":"Modern seasonal and inter-annual precipitation variability in\nPalau is linked to both meridional movement of the Intertropical Convergence Zone (ITCZ) and changes in the Pacific Walker Circula- tion (PWC) associated with the El Niño–Southern Oscillation. Thus, Palau’s hydroclimate should be sensitive to mean shifts in the ITCZ and PWC on decadal to centennial time scales. Using compound- specific hydrogen isotope ratios (δ2H) of dinosterol in lake sediments, we generated a decadal-resolution proxy record of hydroclimatic variability in Palau spanning the past 800 yr. Results indicate a dry- ing trend during the Little Ice Age in Palau, consistent with a south- ward displacement of the ITCZ. In addition to the secular drying trend, there are persistent large (~20‰) multi-decadal to centennial oscillations in the δ2H record, the most recent of which indicates an abrupt shift to drier conditions in the mid-1970s that coincides with a decadal-scale negative shift in the Southern Oscillation Index.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G37822.1","collaboration":"Julian P. Sachs","usgsCitation":"Richey, J.N., and Sachs, J.P., 2016, Precipitation changes in the western tropical Pacific over the past millennium: Geology, v. 8, no. 44, p. 671-674, https://doi.org/10.1130/G37822.1.","productDescription":"4 p.","startPage":"671","endPage":"674","ipdsId":"IP-073428","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":327837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Palau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 134.7418212890625,\n 8.18430516386163\n ],\n [\n 134.79400634765625,\n 8.059229627200192\n ],\n [\n 134.67041015625,\n 7.768144452028487\n ],\n [\n 134.70062255859375,\n 7.490473334419796\n ],\n [\n 134.64569091796875,\n 7.3325025437640114\n ],\n [\n 134.49188232421875,\n 7.231698708367139\n ],\n [\n 134.12109375,\n 6.820079977465815\n ],\n [\n 134.033203125,\n 6.885527022341312\n ],\n [\n 134.7418212890625,\n 8.18430516386163\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"44","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-01","publicationStatus":"PW","scienceBaseUri":"57c0089be4b0f2f0ceb8565c","contributors":{"authors":[{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sachs, Julian P.","contributorId":174047,"corporation":false,"usgs":false,"family":"Sachs","given":"Julian","email":"","middleInitial":"P.","affiliations":[{"id":27348,"text":"School of Oceanography, University of Washington, Seattle, WA 98195, USA","active":true,"usgs":false}],"preferred":false,"id":647048,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176073,"text":"70176073 - 2016 - Patchiness in a large floodplain river: Associations among hydrology, nutrients, and fish communities","interactions":[],"lastModifiedDate":"2016-11-09T09:55:29","indexId":"70176073","displayToPublicDate":"2016-08-24T17:30:00","publicationYear":"2016","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":"Patchiness in a large floodplain river: Associations among hydrology, nutrients, and fish communities","docAbstract":"

Large floodplain rivers have internal structures shaped by directions and rates of water movement. In a previous study, we showed that spatial variation in local current velocities and degrees of hydrological exchange creates a patch-work mosaic of nitrogen and phosphorus concentrations and ratios in the Upper Mississippi River. Here, we used long-term fish and limnological data sets to test the hypothesis that fish communities differ between the previously identified patches defined by high or low nitrogen to phosphorus ratios (TN:TP) and to determine the extent to which select limnological covariates might explain those differences. Species considered as habitat generalists were common in both patch types but were at least 2 times as abundant in low TN:TP patches. Dominance by these species resulted in lower diversity in low TN:TP patches, whereas an increased relative abundance of a number of rheophilic (flow-dependent) species resulted in higher diversity and a more even species distribution in high TN:TP patches. Of the limnological variables considered, the strongest predictor of fish species assemblage and diversity was water flow velocity, indicating that spatial patterns in water-mediated connectivity may act as the main driver of both local nutrient concentrations and fish community composition in these reaches. The coupling among hydrology, biogeochemistry, and biodiversity in these river reaches suggests that landscape-scale restoration projects that manipulate hydrogeomorphic patterns may also modify the spatial mosaic of nutrients and fish communities. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.3026","usgsCitation":"De Jager, N.R., and Houser, J.N., 2016, Patchiness in a large floodplain river: Associations among hydrology, nutrients, and fish communities: River Research and Applications, v. 32, no. 9, p. 1915-1926, https://doi.org/10.1002/rra.3026.","productDescription":"12 p.","startPage":"1915","endPage":"1926","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062928","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":327828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-31","publicationStatus":"PW","scienceBaseUri":"57c6a086e4b0f2f0cebdb037","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647012,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176048,"text":"70176048 - 2016 - The Earthquake‐Source Inversion Validation (SIV) Project","interactions":[],"lastModifiedDate":"2016-08-24T11:37:58","indexId":"70176048","displayToPublicDate":"2016-08-24T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The Earthquake‐Source Inversion Validation (SIV) Project","docAbstract":"
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Finite‐fault earthquake source inversions infer the (time‐dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake‐source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward‐modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source‐model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake‐source imaging problem.

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","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0220150231","usgsCitation":"Mai, P.M., Schorlemmer, D., Page, M.T., Ampuero, J., Asano, K., Causse, M., Custodio, S., Fan, W., Festa, G., Galis, M., Gallovic, F., Imperatori, W., Kaser, M., Malytskyy, D., Okuwaki, R., Pollitz, F., Passone, L., Razafindrakoto, H.N., Sekiguchi, H., Song, S.G., Somala, S.N., Thingbaijam, K.K., Twardzik, C., van Driel, M., Vyas, J.C., Wang, R., Yagi, Y., and Zielke, O., 2016, The Earthquake‐Source Inversion Validation (SIV) Project: Seismological Research Letters, v. 87, no. 3, p. 690-708, https://doi.org/10.1785/0220150231.","startPage":"690","endPage":"708","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076410","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470642,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://gfzpublic.gfz-potsdam.de/pubman/item/item_1587912","text":"External Repository"},{"id":327791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"57c6a08ee4b0f2f0cebdb059","contributors":{"authors":[{"text":"Mai, P. 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Managing inland fisheries in the 21st century presents several obstacles, including the need to view fisheries from multiple spatial and temporal scales, which usually involves populations and resources spanning sociopolitical boundaries. Though collaboration is not new to fisheries science, inland aquatic systems have historically been managed at local scales and present different challenges than in marine or large freshwater systems like the Laurentian Great Lakes. Therefore, we outline a flexible strategy that highlights organization, cooperation, analytics, and implementation as building blocks toward effectively addressing transboundary fisheries issues. Additionally, we discuss the use of Bayesian hierarchical models (within the analytical stage), due to their flexibility in dealing with the variability present in data from multiple scales. With growing recognition of both ecological drivers that span spatial and temporal scales and the subsequent need for collaboration to effectively manage heterogeneous resources, we expect implementation of transboundary approaches to become increasingly critical for effective inland fisheries management.

","language":"English, Spanish","publisher":"Taylor & Francis","doi":"10.1080/03632415.2016.1208090","usgsCitation":"Midway, S.R., Wagner, T., Zydlewski, J.D., Irwin, B.J., and Paukert, C.P., 2016, Transboundary fisheries science: Meeting the challenges of inland fisheries management in the 21st century: Fisheries, v. 41, no. 9, p. 536-546, https://doi.org/10.1080/03632415.2016.1208090.","productDescription":"11 p.","startPage":"536","endPage":"546","ipdsId":"IP-067099","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":336732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-24","publicationStatus":"PW","scienceBaseUri":"58b7eba7e4b01ccd5500bb11","contributors":{"authors":[{"text":"Midway, Stephen R.","contributorId":172159,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":680395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":673751,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":680396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":680397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":879,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":680398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189894,"text":"70189894 - 2016 - NHDPlusHR: A national geospatial framework for surface-water information","interactions":[],"lastModifiedDate":"2017-08-06T16:51:06","indexId":"70189894","displayToPublicDate":"2016-08-24T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"NHDPlusHR: A national geospatial framework for surface-water information","docAbstract":"

The U.S. Geological Survey is developing a new geospatial hydrographic framework for the United States, called the National Hydrography Dataset Plus High Resolution (NHDPlusHR), that integrates a diversity of the best-available information, robustly supports ongoing dataset improvements, enables hydrographic generalization to derive alternate representations of the network while maintaining feature identity, and supports modern scientific computing and Internet accessibility needs. This framework is based on the High Resolution National Hydrography Dataset, the Watershed Boundaries Dataset, and elevation from the 3-D Elevation Program, and will provide an authoritative, high precision, and attribute-rich geospatial framework for surface-water information for the United States. Using this common geospatial framework will provide a consistent basis for indexing water information in the United States, eliminate redundancy, and harmonize access to, and exchange of water information.

","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12429","usgsCitation":"Viger, R.J., Rea, A.H., Simley, J.D., and Hanson, K.M., 2016, NHDPlusHR: A national geospatial framework for surface-water information: JAWRA, v. 52, no. 4, p. 901-905, https://doi.org/10.1111/1752-1688.12429.","productDescription":"5 p.","startPage":"901","endPage":"905","ipdsId":"IP-074030","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-20","publicationStatus":"PW","scienceBaseUri":"59882a95e4b05ba66e9ffdda","contributors":{"authors":[{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rea, Alan H. ahrea@usgs.gov","contributorId":1813,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","email":"ahrea@usgs.gov","middleInitial":"H.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simley, Jeffrey D. jdsimley@usgs.gov","contributorId":4582,"corporation":false,"usgs":true,"family":"Simley","given":"Jeffrey","email":"jdsimley@usgs.gov","middleInitial":"D.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Karen M. khanson@usgs.gov","contributorId":936,"corporation":false,"usgs":true,"family":"Hanson","given":"Karen","email":"khanson@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":706644,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174858,"text":"sir20165091 - 2016 - Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin","interactions":[],"lastModifiedDate":"2016-08-24T09:36:42","indexId":"sir20165091","displayToPublicDate":"2016-08-23T13:20:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5091","title":" Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin","docAbstract":"

A groundwater/surface-water model was constructed and calibrated for the Black Earth Creek watershed in south-central Wisconsin. The model was then run to simulate scenarios representing common societal concerns in the basin, focusing on maintaining a cold-water resource in an urbanizing fringe near its upper stream reaches and minimizing downstream flooding. Although groundwater and surface water are considered a single resource, many hydrologic models simplistically simulate feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system; however, computer models can now routinely and iteratively couple the surface-water and groundwater systems—albeit with longer model run times. In this study, preliminary calibrations of uncoupled transient surface-water and steady-state groundwater models were used to form the starting point for final calibration of one transient computer simulation that iteratively couples groundwater and surface water. The computer code GSFLOW (Groundwater/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, and streams. The coupled GSFLOW model was run on a daily time step during water years 1985–2007. Early simulation times (1985–2000) were used for spin-up to make the simulation results less sensitive to initial conditions specified; the spin-up period was not included in the model calibration. Model calibration used observed heads, streamflows, solar radiation, and snowpack measurements from 2000 to 2007 for history matching. Calibration was performed by using the PEST parameter estimation software suite.

\n

Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model. SNTEMP was used to simulate daily stream temperature in selected stream reaches in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2005. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the years 2010 through 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the simulation period showed increases in maximum and minimum air temperature. Scenarios of future precipitation, however, did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased with time for both temperature and precipitation.

\n

Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snowmelt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions, with relatively less drying expected in groundwater-fed systems. Groundwater discharge in the current upper cold-water reaches of Black Earth Creek is expected to decrease; flooding in downstream reaches may appreciably increase. The magnitude of changes in forecasted flow and associated groundwater/surface-water interaction is dependent on the General Circulation Model and emission scenario chosen.

\n

Potential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165091","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources, Village of Cross Plains, Village of Black Earth, Town of Black Earth, Town of Vermont, Village of Mazomanie, and City of Middleton","usgsCitation":"Hunt, R.J., Westenbroek, S.M., Walker, J.F., Selbig, W.R., Regan, R.S., Leaf, A.T., and Saad, D.A., 2016, Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2016–5091, 117 p., https://dx.doi.org/10.3133/sir20165091.","productDescription":"Report: x, 49 p.; Appendixes: 1–6","startPage":"1","endPage":"117","numberOfPages":"132","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072633","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":327327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5091/coverthb.jpg"},{"id":327328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5091/sir20165091.pdf","text":"Report","size":"8.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5091"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Black Earth Creek Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.73333333333333,43.06666666666667 ], [ -89.73333333333333,43.18333333333333 ], [ -89.55,43.18333333333333 ], [ -89.55,43.06666666666667 ], [ -89.73333333333333,43.06666666666667 ] ] ] } } ] }","contact":"

Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562

http://wi.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-08-23","noUsgsAuthors":false,"publicationDate":"2016-08-23","publicationStatus":"PW","scienceBaseUri":"57bd6598e4b03fd6b7de724c","contributors":{"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, R. Steven 0000-0003-4803-8596","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":87237,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"","middleInitial":"Steven","affiliations":[],"preferred":false,"id":642843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642844,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642845,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176038,"text":"70176038 - 2016 - The Eastern California Shear Zone as the northward extension of the southern San Andreas Fault","interactions":[],"lastModifiedDate":"2016-08-24T11:23:20","indexId":"70176038","displayToPublicDate":"2016-08-23T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The Eastern California Shear Zone as the northward extension of the southern San Andreas Fault","docAbstract":"

Cluster analysis offers an agnostic way to organize and explore features of the current GPS velocity field without reference to geologic information or physical models using information only contained in the velocity field itself. We have used cluster analysis of the Southern California Global Positioning System (GPS) velocity field to determine the partitioning of Pacific-North America relative motion onto major regional faults. Our results indicate the large-scale kinematics of the region is best described with two boundaries of high velocity gradient, one centered on the Coachella section of the San Andreas Fault and the Eastern California Shear Zone and the other defined by the San Jacinto Fault south of Cajon Pass and the San Andreas Fault farther north. The ~120 km long strand of the San Andreas between Cajon Pass and Coachella Valley (often termed the San Bernardino and San Gorgonio sections) is thus currently of secondary importance and carries lesser amounts of slip over most or all of its length. We show these first order results are present in maps of the smoothed GPS velocity field itself. They are also generally consistent with currently available, loosely bounded geologic and geodetic fault slip rate estimates that alone do not provide useful constraints on the large-scale partitioning we show here. Our analysis does not preclude the existence of smaller blocks and more block boundaries in Southern California. However, attempts to identify smaller blocks along and adjacent to the San Gorgonio section were not successful.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015JB012678","usgsCitation":"Thatcher, W.R., Savage, J.C., and Simpson, R.W., 2016, The Eastern California Shear Zone as the northward extension of the southern San Andreas Fault: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2904-2914, https://doi.org/10.1002/2015JB012678.","startPage":"2904","endPage":"2914","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066319","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470643,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012678","text":"Publisher Index Page"},{"id":327784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Eastern California Shear Zone","volume":"121","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"57c6a08fe4b0f2f0cebdb05b","contributors":{"authors":[{"text":"Thatcher, Wayne R. 0000-0001-6324-545X thatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-545X","contributorId":2599,"corporation":false,"usgs":true,"family":"Thatcher","given":"Wayne","email":"thatcher@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":646859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":646860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simpson, Robert W. simpson@usgs.gov","contributorId":1053,"corporation":false,"usgs":true,"family":"Simpson","given":"Robert","email":"simpson@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":646861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176034,"text":"70176034 - 2016 - State-space modeling of population sizes and trends in Nihoa Finch and Millerbird","interactions":[],"lastModifiedDate":"2018-01-04T12:30:43","indexId":"70176034","displayToPublicDate":"2016-08-23T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"State-space modeling of population sizes and trends in Nihoa Finch and Millerbird","docAbstract":"

Both of the 2 passerines endemic to Nihoa Island, Hawai‘i, USA—the Nihoa Millerbird (Acrocephalus familiaris kingi) and Nihoa Finch (Telespiza ultima)—are listed as endangered by federal and state agencies. Their abundances have been estimated by irregularly implemented fixed-width strip-transect sampling from 1967 to 2012, from which area-based extrapolation of the raw counts produced highly variable abundance estimates for both species. To evaluate an alternative survey method and improve abundance estimates, we conducted variable-distance point-transect sampling between 2010 and 2014. We compared our results to those obtained from strip-transect samples. In addition, we applied state-space models to derive improved estimates of population size and trends from the legacy time series of strip-transect counts. Both species were fairly evenly distributed across Nihoa and occurred in all or nearly all available habitat. Population trends for Nihoa Millerbird were inconclusive because of high within-year variance. Trends for Nihoa Finch were positive, particularly since the early 1990s. Distance-based analysis of point-transect counts produced mean estimates of abundance similar to those from strip-transects but was generally more precise. However, both survey methods produced biologically unrealistic variability between years. State-space modeling of the long-term time series of abundances obtained from strip-transect counts effectively reduced uncertainty in both within- and between-year estimates of population size, and allowed short-term changes in abundance trajectories to be smoothed into a long-term trend.

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This report, chapter A of Scientific Investigations Report 2016–5089, provides an overview of the U.S. Geological Survey (USGS) Sagebrush Mineral-Resource Assessment (SaMiRA). The report also describes the methods, procedures, and voluminous fundamental reference information used throughout the assessment. Data from several major publicly available databases and other published sources were used to develop an understanding of the locatable, leaseable, and salable mineral resources of this vast area. This report describes the geologic, mineral-occurrence, geochemical, geophysical, remote-sensing, and Bureau of Land Management mineral-case-status data used for the assessment, along with the methods for evaluating locatable mineral-resource potential. The report also discusses energy-resource data (oil and gas, coal, and geothermal) used in the assessment. Appendixes include summary descriptive mineral-deposit models that provide the criteria necessary to assess for the pertinent locatable minerals and market-demand commodity profiles for locatable mineral commodities relevant to the project. Datasets used in the assessment are available as USGS data releases.

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Contact Information, Mineral Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/

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Avian cholera, caused by the bacterium Pasteurella multocida, is an endemic disease globally, often causing annual epizootics in North American wild bird populations with thousands of mortalities. From December 2006 to March 2007, an avian cholera outbreak caused mortality in marine birds off the coast of Atlantic Canada, largely centered 300–400 km off the coast of the island of Newfoundland. Scavenging gulls (Larus spp.) were the primary species detected; however, mortality was also identified in Black-legged Kittiwakes (Rissa tridactyla) and one Common Raven (Corvus corax), a nonmarine species. The most common gross necropsy findings in the birds with confirmed avian cholera were acute fibrinous and necrotizing lesions affecting the spleen, air sacs, and pericardium, and nonspecific hepatomegaly and splenomegaly. The etiologic agent, P. multocida serotype 1, was recovered from 77 of 136 carcasses examined, and confirmed or probable avian cholera was diagnosed in 85 cases. Mortality observed in scavenging gull species was disproportionately high relative to their abundance, particularly when compared to nonscavenging species. The presence of feather shafts in the ventricular lumen of the majority of larid carcasses diagnosed with avian cholera suggests scavenging of birds that died from avian cholera as a major mode of transmission. This documentation of an outbreak of avian cholera in a North American pelagic environment affecting primarily scavenging gulls indicates that offshore marine environments may be a component of avian cholera dynamics.

","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2015-12-342","usgsCitation":"Wille, M., McBurney, S., Robertson, G.J., Wilhelm, S., Blehert, D.S., Soos, C., Dunphy, R., and Whitney, H., 2016, A pelagic outbreak of avian cholera in North American gulls: Scavenging as a primary mechanism for transmission?: Journal of Wildlife Diseases, v. 52, no. 4, p. 793-802, https://doi.org/10.7589/2015-12-342.","productDescription":"10 p.","startPage":"793","endPage":"802","ipdsId":"IP-071539","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":470650,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/2015-12-342","text":"Publisher Index Page"},{"id":327099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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Catherine","contributorId":99042,"corporation":false,"usgs":true,"family":"Soos","given":"Catherine","affiliations":[],"preferred":false,"id":646507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunphy, Ron","contributorId":173885,"corporation":false,"usgs":false,"family":"Dunphy","given":"Ron","email":"","affiliations":[{"id":27313,"text":"Private Veterinary Practice, St. John's, NL A1K1G8, Canada","active":true,"usgs":false}],"preferred":false,"id":646508,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitney, Hugh","contributorId":173886,"corporation":false,"usgs":false,"family":"Whitney","given":"Hugh","email":"","affiliations":[{"id":27314,"text":"Animal Health Division. Forestry and Agrifoods Agency. P.O. Box 7400. St. John’s, NL A1E","active":true,"usgs":false}],"preferred":false,"id":646509,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70175956,"text":"70175956 - 2016 - Effects of salinity and flooding on post-hurricane regeneration potential in coastal wetland vegetation","interactions":[],"lastModifiedDate":"2016-12-16T11:44:12","indexId":"70175956","displayToPublicDate":"2016-08-18T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Effects of salinity and flooding on post-hurricane regeneration potential in coastal wetland vegetation","docAbstract":"

PREMISE OF THE STUDY: The nature of regeneration dynamics after hurricane flooding and salinity intrusion may play an important role in shaping coastal vegetation patterns.

\n

METHODS: The regeneration potentials of coastal species, types and gradients (wetland types from seaward to landward) were studied on the Delmarva Peninsula after Hurricane Sandy using seed bank assays to examine responses to various water regimes (unflooded and flooded to 8 cm) and salinity levels (0, 1, and 5 ppt). Seed bank responses to treatments were compared using a generalized linear models approach. Species relationships to treatment and geographical variables were explored using nonmetric multidimensional scaling.

\n

KEY RESULTS: Flooding and salinity treatments affected species richness even at low salinity levels (1 and 5 ppt). Maritime forest was especially intolerant of salinity intrusion so that species richness was much higher in unflooded and low salinity conditions, despite the proximity of maritime forest to saltmarsh along the coastal gradient. Other vegetation types were also affected, with potential regeneration of these species affected in various ways by flooding and salinity, suggesting relationships to post-hurricane environment and geographic position.

\n

CONCLUSIONS: Seed germination and subsequent seedling growth in coastal wetlands may in some cases be affected by salinity intrusion events even at low salinity levels (1 and 5 ppt). These results indicate that the potential is great for hurricanes to shift vegetation type in sensitive wetland types (e.g., maritime forest) if post-hurricane environments do not support the regeneration of extent vegetation.

","language":"English","publisher":"Botanical Society of America","doi":"10.3732/ajb.1600062","usgsCitation":"Middleton, B.A., 2016, Effects of salinity and flooding on post-hurricane regeneration potential in coastal wetland vegetation: American Journal of Botany, v. 103, no. 8, p. 1420-1435, https://doi.org/10.3732/ajb.1600062.","productDescription":"16 p.","startPage":"1420","endPage":"1435","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072858","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3732/ajb.1600062","text":"Publisher Index Page"},{"id":327376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.04736328125,\n 39.42346418978382\n ],\n [\n -76.3055419921875,\n 39.21948715423953\n ],\n [\n -76.39892578125,\n 38.878204997061474\n ],\n [\n -76.3165283203125,\n 38.35027253825765\n ],\n [\n -76.1627197265625,\n 38.08701320402273\n ],\n [\n -76.0418701171875,\n 37.735969208590504\n ],\n [\n -76.036376953125,\n 37.501010429493284\n ],\n [\n -76.09130859375,\n 37.212831514455964\n ],\n [\n -75.9539794921875,\n 37.01571219880126\n ],\n [\n -75.69580078125,\n 37.18657859524883\n ],\n [\n -75.377197265625,\n 37.65773212628274\n ],\n [\n -75.0421142578125,\n 38.151837403006766\n ],\n [\n -74.937744140625,\n 38.59540719940386\n ],\n [\n -75.1629638671875,\n 39.031986028740086\n ],\n [\n -75.38818359375,\n 39.30029918615029\n ],\n [\n -75.56396484375,\n 39.49556336059472\n ],\n [\n -76.04736328125,\n 39.42346418978382\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57bd73bae4b03fd6b7df2c8f","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":646693,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70175123,"text":"ofr20161121 - 2016 - U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)","interactions":[],"lastModifiedDate":"2018-10-11T15:01:32","indexId":"ofr20161121","displayToPublicDate":"2016-08-18T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1121","title":"U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)","docAbstract":"

Introduction

Through the Science Strategy for Highly Pathogenic Avian Influenza (HPAI) in Wildlife and the Environment, the USGS will assess avian influenza (AI) dynamics in an ecological context to inform decisions made by resource managers and policymakers from the local to national level. Through collection of unbiased scientific information on the ecology of AI viruses and wildlife hosts in a changing world, the U.S. Geological Survey (USGS) will enhance the development of AI forecasting tools and ensure this information is integrated with a quality decision process for managing HPAI.

The overall goal of this USGS Science Strategy for HPAI in Wildlife and the Environment goes beyond document­ing the occurrence and distribution of AI viruses in wild birds. The USGS aims to understand the epidemiological processes and environmental factors that influence HPAI distribution and describe the mechanisms of transmission between wild birds and poultry. USGS scientists developed a conceptual model describing the process linking HPAI dispersal in wild waterfowl to the outbreaks in poul­try. This strategy focuses on five long-term science goals, which include:

These goals will help define and describe the processes outlined in the conceptual model with the ultimate goal of facilitating biosecurity and minimizing transfer of diseases across the wildlife-poultry interface. The first four science goals are focused on scientific discovery and the fifth goal is application-based. Decision analyses in the fifth goal will guide prioritization of proposed actions in the first four goals.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161121","usgsCitation":"Harris, M.C., Pearce, J.M., Prosser, D.J., White, C.L., Miles, A.K., Sleeman, J.M., Brand, C.J., Cronin, J.P., De La Cruz, S., Densmore, C.L., Doyle, T.W., Dusek, R.J., Fleskes, J.P., Flint, P.L., Guala, G.F., Hall, J.S., Hubbard, L.E., Hunt, R.J., Ip, H.S., Katz, R.A., Laurent, K.W., Miller, M.P., Munn, M.D., Ramey, A.M., Richards, K.D., Russell, R.E., Stokdyk, J.P., Takekawa, J.Y., and Walsh, D.P., 2016, U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020): U.S. Geological Survey Open-File Report 2016–1121, 38 p., https://dx.doi.org/10.3133/ofr20161121.","productDescription":"v, 38 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070395","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":326589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1121/coverthb.jpg"},{"id":326590,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1121/ofr20161121.pdf","text":"Report","size":"4.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1121"}],"country":"United States","contact":"

Associate Director for Ecosystems
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
https://www2.usgs.gov/ecosystems/

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-08-18","noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57b6ce29e4b03fd6b7d919ea","contributors":{"authors":[{"text":"Harris, M. 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,{"id":70175544,"text":"ofr20161135 - 2016 - Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington","interactions":[],"lastModifiedDate":"2016-08-19T08:27:59","indexId":"ofr20161135","displayToPublicDate":"2016-08-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1135","title":"Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington","docAbstract":"

Information about groundwater-flow paths and locations where groundwater discharges at and near Puget Sound Naval Shipyard is necessary for understanding the potential migration of subsurface contaminants by groundwater at the shipyard. The design of some remediation alternatives would be aided by knowledge of whether groundwater flowing at specific locations beneath the shipyard will eventually discharge directly to Sinclair Inlet of Puget Sound, or if it will discharge to the drainage system of one of the six dry docks located in the shipyard. A 1997 numerical (finite difference) groundwater-flow model of the shipyard and surrounding area was constructed to help evaluate the potential for groundwater discharge to Puget Sound. That steady-state, multilayer numerical model with homogeneous hydraulic characteristics indicated that groundwater flowing beneath nearly all of the shipyard discharges to the dry-dock drainage systems, and only shallow groundwater flowing beneath the western end of the shipyard discharges directly to Sinclair Inlet.

Updated information from a 2016 regional groundwater-flow model constructed for the greater Kitsap Peninsula was used to update the 1997 groundwater model of the Puget Sound Naval Shipyard. That information included a new interpretation of the hydrogeologic units underlying the area, as well as improved recharge estimates. Other updates to the 1997 model included finer discretization of the finite-difference model grid into more layers, rows, and columns, all with reduced dimensions. This updated Puget Sound Naval Shipyard model was calibrated to 2001–2005 measured water levels, and hydraulic characteristics of the model layers representing different hydrogeologic units were estimated with the aid of state-of-the-art parameter optimization techniques.

The flow directions and discharge locations predicted by this updated model generally match the 1997 model despite refinements and other changes. In the updated model, most groundwater discharge recharged within the boundaries of the shipyard is to the dry docks; only at the western end of the shipyard does groundwater discharge directly to Puget Sound. Particle tracking for the existing long-term monitoring well network suggests that only a few wells intercept groundwater that originates as recharge within the shipyard boundary.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161135","collaboration":"Prepared in cooperation with the Naval Facilities Engineering Command-Northwest","usgsCitation":"Jones, J.L., Johnson, K.H., and Frans, L.M., 2016, Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington: U.S. Geological Survey Open-File Report 2016-1135, 35 p., https://dx.doi.org/10.3133/ofr20161135.","productDescription":"Report:","startPage":"1","endPage":"35","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076467","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":438574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94FCYGV","text":"USGS data release","linkHelpText":"MODFLOW-NWT model to simulate the groundwater flow system at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington"},{"id":326832,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1135/coverthb.jpg"},{"id":326833,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1135/ofr20161135.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1135"}],"country":"United States","state":"Washington","city":"Bremerton","otherGeospatial":"Puget Sound Naval Shipyard, Naval Base Kitsap,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6953125,\n 47.529488341715265\n ],\n [\n -122.67230987548828,\n 47.53899190311993\n ],\n [\n -122.67093658447266,\n 47.54432241518175\n ],\n [\n -122.65960693359374,\n 47.55150616084034\n ],\n [\n -122.6513671875,\n 47.55382328811835\n ],\n [\n -122.63866424560547,\n 47.556603705614094\n ],\n [\n -122.63248443603514,\n 47.5586889219186\n ],\n [\n -122.62390136718749,\n 47.5610057315948\n ],\n [\n -122.62115478515625,\n 47.569808674020344\n ],\n [\n -122.62493133544922,\n 47.575136052077276\n ],\n [\n -122.64038085937499,\n 47.58023129789275\n ],\n [\n -122.64896392822264,\n 47.584168193691696\n ],\n [\n -122.65445709228516,\n 47.58903100916583\n ],\n [\n -122.65926361083984,\n 47.5996813120644\n ],\n [\n -122.66578674316406,\n 47.60384823184624\n ],\n [\n -122.67162322998047,\n 47.604774168947614\n ],\n [\n -122.68054962158202,\n 47.593198777144636\n ],\n [\n -122.68466949462892,\n 47.58301031389572\n ],\n [\n -122.68260955810545,\n 47.5714301073211\n ],\n [\n -122.69359588623047,\n 47.557067094186735\n ],\n [\n -122.70973205566406,\n 47.54663986006874\n ],\n [\n -122.6953125,\n 47.529488341715265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-08-18","noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57b6ce29e4b03fd6b7d919e1","contributors":{"authors":[{"text":"Jones, Joseph L. jljones@usgs.gov","contributorId":3492,"corporation":false,"usgs":true,"family":"Jones","given":"Joseph","email":"jljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":645607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kenneth H. johnson@usgs.gov","contributorId":3103,"corporation":false,"usgs":true,"family":"Johnson","given":"Kenneth","email":"johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":645608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frans, Lonna M. 0000-0002-3217-1862 lmfrans@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-1862","contributorId":1493,"corporation":false,"usgs":true,"family":"Frans","given":"Lonna","email":"lmfrans@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":645609,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175482,"text":"ofr20161132 - 2016 - Dam Removal Information Portal (DRIP)—A map-based resource linking scientific studies and associated geospatial information about dam removals","interactions":[],"lastModifiedDate":"2018-08-10T16:35:37","indexId":"ofr20161132","displayToPublicDate":"2016-08-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1132","title":"Dam Removal Information Portal (DRIP)—A map-based resource linking scientific studies and associated geospatial information about dam removals","docAbstract":"

The removal of dams has recently increased over historical levels due to aging infrastructure, changing societal needs, and modern safety standards rendering some dams obsolete. Where possibilities for river restoration, or improved safety, exceed the benefits of retaining a dam, removal is more often being considered as a viable option. Yet, as this is a relatively new development in the history of river management, science is just beginning to guide our understanding of the physical and ecological implications of dam removal. Ultimately, the “lessons learned” from previous scientific studies on the outcomes dam removal could inform future scientific understanding of ecosystem outcomes, as well as aid in decision-making by stakeholders. We created a database visualization tool, the Dam Removal Information Portal (DRIP), to display map-based, interactive information about the scientific studies associated with dam removals. Serving both as a bibliographic source as well as a link to other existing databases like the National Hydrography Dataset, the derived National Dam Removal Science Database serves as the foundation for a Web-based application that synthesizes the existing scientific studies associated with dam removals. Thus, using the DRIP application, users can explore information about completed dam removal projects (for example, their location, height, and date removed), as well as discover sources and details of associated of scientific studies. As such, DRIP is intended to be a dynamic collection of scientific information related to dams that have been removed in the United States and elsewhere. This report describes the architecture and concepts of this “metaknowledge” database and the DRIP visualization tool.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161132","usgsCitation":"Duda, J.J., Wieferich, D.J., Bristol, R.S., Bellmore, J.R., Hutchison, V.B., Vittum, K.M., Craig, Laura, and Warrick, J.A., 2016, Dam Removal Information Portal (DRIP)—A map-based resource linking scientific studies and associated geospatial information about dam removals: U.S. Geological Survey Open-File Report 2016-1132, 14 p., https://dx.doi.org/10.3133/ofr20161132.","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076705","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":326867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1132/coverthb.jpg"},{"id":326868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1132/ofr20161132.pdf","text":"Report","size":"441 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1132"}],"contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-08-18","noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57b6ce28e4b03fd6b7d919cf","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":145486,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":645409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":173859,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel J.","affiliations":[],"preferred":false,"id":645410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":645411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bellmore, J. Ryan","contributorId":104790,"corporation":false,"usgs":true,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":645412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":147815,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian","email":"vhutchison@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":645413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vittum, Katherine M.","contributorId":173860,"corporation":false,"usgs":false,"family":"Vittum","given":"Katherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":645414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Craig, Laura","contributorId":173675,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","affiliations":[{"id":27270,"text":"American Rivers","active":true,"usgs":false}],"preferred":false,"id":645415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":146720,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","email":"jwarrick@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":645416,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174855,"text":"ofr20161117 - 2016 - Estimating suspended sediment using acoustics in a fine-grained riverine system, Kickapoo Creek at Bloomington, Illinois","interactions":[],"lastModifiedDate":"2016-08-19T09:31:46","indexId":"ofr20161117","displayToPublicDate":"2016-08-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1117","title":"Estimating suspended sediment using acoustics in a fine-grained riverine system, Kickapoo Creek at Bloomington, Illinois","docAbstract":"

Acoustic technologies have the potential to be used as a surrogate for measuring suspended-sediment concentration (SSC). This potential was examined in a fine-grained (97-100 percent fines) riverine system in central Illinois by way of installation of an acoustic instrument. Acoustic data were collected continuously over the span of 5.5 years. Acoustic parameters were regressed against SSC data to determine the accuracy of using acoustic technology as a surrogate for measuring SSC in a fine-grained riverine system. The resulting regressions for SSC and sediment acoustic parameters had coefficients of determination ranging from 0.75 to 0.97 for various events and configurations. The overall Nash-Sutcliffe model-fit efficiency was 0.95 for the 132 observed and predicted SSC values determined using the sediment acoustic parameter regressions. The study of using acoustic technologies as a surrogate for measuring SSC in fine-grained riverine systems is ongoing. The results at this site are promising in the realm of surrogate technology.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161117","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency and the Federal Interagency Sedimentation Project","usgsCitation":"Manaster, A.D, Domanski, M.M., Straub, T.D., and Boldt, J.A., 2016, Estimating suspended sediment using acoustics in a fine-grained riverine system on Kickapoo Creek at Bloomington, Illinois: U.S. Geological Survey Open-File Report 2016–1117, 42 p., https://dx.doi.org/10.3133/ofr20161117.","productDescription":"viii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074002","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":326412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1117/coverthb.jpg"},{"id":326413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1117/ofr20161117.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1117"}],"country":"United States","state":"Illinois","city":"Bloomington","otherGeospatial":"Kickapoo Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.02952575683594,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.57432635193039\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-08-18","noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57b6ce28e4b03fd6b7d919d7","contributors":{"authors":[{"text":"Manaster, Amanda D.","contributorId":173615,"corporation":false,"usgs":true,"family":"Manaster","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":642822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boldt, Justin A. jboldt@usgs.gov","contributorId":4375,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin A.","email":"jboldt@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642825,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176237,"text":"70176237 - 2016 - Climate change and future fire regimes: Examples from California","interactions":[],"lastModifiedDate":"2016-09-03T21:29:26","indexId":"70176237","displayToPublicDate":"2016-08-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1813,"text":"Geoscience Canada","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and future fire regimes: Examples from California","docAbstract":"Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.","language":"English","publisher":"MDPI AG","doi":"10.3390/geosciences6030037","usgsCitation":"Keeley, J.E., and Syphard, A.D., 2016, Climate change and future fire regimes: Examples from California: Geoscience Canada, v. 6, no. 37, 14 p., https://doi.org/10.3390/geosciences6030037.","productDescription":"14 p.","ipdsId":"IP-076461","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences6030037","text":"Publisher Index Page"},{"id":328233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"37","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-17","publicationStatus":"PW","scienceBaseUri":"57cbf42ae4b0f2f0cec3b9ff","contributors":{"authors":[{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647998,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174975,"text":"sir20165106 - 2016 - Sediment load and distribution in the lower Skagit River, Skagit County, Washington","interactions":[],"lastModifiedDate":"2016-08-18T10:25:47","indexId":"sir20165106","displayToPublicDate":"2016-08-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5106","title":"Sediment load and distribution in the lower Skagit River, Skagit County, Washington","docAbstract":"

The Skagit River delivers about 40 percent of all fluvial sediment that enters Puget Sound, influencing flood hazards in the Skagit lowlands, critically important estuarine habitat in the delta, and some of the most diverse and productive agriculture in western Washington. A total of 175 measurements of suspended-sediment load, made routinely from 1974 to 1993, and sporadically from 2006 to 2009, were used to develop and evaluate regression models of sediment transport (also known as “sediment-rating curves”) for estimating suspended-sediment load as a function of river discharge. Using a flow-range model and 75 years of daily discharge record (acquired from 1941 to 2015), the mean annual suspended-sediment load for the Skagit River near Mount Vernon, Washington, was estimated to be 2.5 teragrams (Tg, where 1 Tg = 1 million metric tons). The seasonal model indicates that 74 percent of the total annual suspended‑sediment load is delivered to Puget Sound during the winter storm season (from October through March), but also indicates that discharge is a poor surrogate for suspended‑sediment concentration (SSC) during the summer low-flow season. Sediment-rating curves developed for different time periods revealed that the regression model slope of the SSC-discharge relation increased 66 percent between the periods of 1974–76 and 2006–09 when suspended-sediment samples were collected, implying that changes in sediment supply, channel hydraulics, and (or) basin hydrology occurred between the two time intervals. In the relatively wet water year 2007 (October 1, 2006, through September 30, 2007), an automated sampler was used to collect daily samples of suspended sediment from which an annual load of 4.5 Tg was calculated, dominated by a single large flood event that contributed 1.8 Tg, or 40 percent of the total. In comparison, the annual load calculated for water year 2007 using the preferred flow-range model was 4.8 Tg (+6.7 percent), in close agreement with the measured value.

Particle size affects sediment transport, fate and distribution across watersheds, and therefore is important for predicting how coastal environments, particularly deltas and beaches, will respond to changes in climate and sea-level. Particle-size analysis of winter storm samples indicated that about one-half of the suspended-sediment load consisted of fines (that is, silt- and clay-sized particles smaller than 0.0625 mm in diameter), and the remainder consisted of mostly fine- to medium-sized sand (0.0625–0.5 mm), whereas bedload during winter storm flows (about 1–3 percent of total sediment load) was predominantly composed of medium to coarse sand (0.25–1 mm). A continuous turbidity record from the Anacortes Water Treatment Plant (water years 1999–2013), used as a surrogate for the concentration of fines (R2 = 0.93, p = 4.2E-10, n = 17), confirms that about one-half of the mean annual suspended-sediment load is composed of fines.

The distribution of flow through the delta distributaries (that is, the channels into which the main stem splits as it approaches the delta) is dynamic, with twice as much flow through the North Fork of the Skagit River relative to the South Fork during low-flow conditions, and close to equal flows in the two channels during high-flow conditions. Turbidity, monitored at several locations in the lower river in spring 2009, was essentially uniform among sites, indicating that fines are well mixed in the lower Skagit River system (defined as the Skagit River and all its distributaries downstream of the Mount Vernon streamgage). A strong relation (R2 = 0.95, p = 3.2E-14, n = 21; linear regression) between the concentration of fines and turbidity measured at various locations in summer 2009 indicates that turbidity is an effective surrogate for the concentration of fines, independent of location in the river, under naturally well-mixed fluvial conditions. This relation is especially useful for monitoring suspended sediment in western Washington rivers that are seasonally dominated by glacier meltwater because glacial melting typically produces suspended-sediment concentrations that are not well correlated with discharge. These results provide a comprehensive set of tools to estimate sediment delivery and delta responses of interest to scientists and resource managers including decision-makers examining options for flood hazard mitigation, estuary restoration, and climate change adaptation.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165106","collaboration":"A Study by the U.S. Geological Survey Coastal Habitats in Puget Sound (CHIPS) Project","usgsCitation":"Curran, C.A., Grossman, E.E., Mastin, M.C., and Huffman, R.L., 2016, Sediment load and distribution in the lower Skagit River, Skagit County, Washington: U.S. Geological Survey Scientific Investigations Report 2016–5106, 24 p., https://dx.doi.org/10.3133/sir20165106.","productDescription":"vi, 24 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059558","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":326607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5106/coverthb.jpg"},{"id":326608,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5106/sir20165106.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5106"}],"country":"United States","state":"Washington","county":"Skagit County","otherGeospatial":"Lower Skagit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.541667,\n 48.466667\n ],\n [\n -122.541667,\n 48.3\n ],\n [\n -122.283333,\n 48.3\n ],\n [\n -122.283333,\n 48.466667\n ],\n [\n -122.541667,\n 48.466667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-08-17","noUsgsAuthors":false,"publicationDate":"2016-08-17","publicationStatus":"PW","scienceBaseUri":"57b57ca5e4b03bcb0104bb44","contributors":{"authors":[{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":2334,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric E.","email":"egrossman@usgs.gov","affiliations":[],"preferred":false,"id":643475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mastin, Mark C. 0000-0003-4018-7861 mcmastin@usgs.gov","orcid":"https://orcid.org/0000-0003-4018-7861","contributorId":1652,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","email":"mcmastin@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huffman, Raegan L. 0000-0001-8523-5439 rhuffman@usgs.gov","orcid":"https://orcid.org/0000-0001-8523-5439","contributorId":1638,"corporation":false,"usgs":true,"family":"Huffman","given":"Raegan","email":"rhuffman@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}