Aims
Biological soil crusts (biocrusts) are soil-surface communities in drylands, dominated by cyanobacteria, mosses, and lichens. They provide key ecosystem functions by increasing soil stability and influencing soil hydrologic, nutrient, and carbon cycles. Because of this, methods to reestablish biocrusts in damaged drylands are needed. Here we test the reintroduction of field-collected vs. greenhouse-cultured biocrusts for rehabilitation.
Methods
We collected biocrusts for 1) direct reapplication, and 2) artificial cultivation under varying hydration regimes. We added field-collected and cultivated biocrusts (with and without hardening treatments) to bare field plots and monitored establishment.
Results
Both field-collected and cultivated cyanobacteria increased cover dramatically during the experimental period. Cultivated biocrusts established more rapidly than field-collected biocrusts, attaining ~82% cover in only one year, but addition of field-collected biocrusts led to higher species richness, biomass (as assessed by chlorophyll a) and level of development. Mosses and lichens did not establish well in either case, but late successional cover was affected by hardening and culture conditions.
Conclusions
This study provides further evidence that it is possible to culture biocrust components from later successional materials and reestablish cultured organisms in the field. However, more research is needed into effective reclamation techniques.
“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.03123","usgsCitation":"Fieberg, J.R., Forester, J.D., Street, G.M., Johnson, D.H., ArchMiller, A.A., and Matthiopoulos, J., 2018, Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models: Ecography, v. 41, no. 5, p. 737-752, https://doi.org/10.1111/ecog.03123.","productDescription":"16 p.","startPage":"737","endPage":"752","ipdsId":"IP-078796","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.03123","text":"Publisher Index Page"},{"id":343437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","scienceBaseUri":"595f4c33e4b0d1f9f057e2db","contributors":{"authors":[{"text":"Fieberg, John R. 0000-0002-3180-7021","orcid":"https://orcid.org/0000-0002-3180-7021","contributorId":194333,"corporation":false,"usgs":false,"family":"Fieberg","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forester, James D.","contributorId":194334,"corporation":false,"usgs":false,"family":"Forester","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Street, Garrett M.","contributorId":194335,"corporation":false,"usgs":false,"family":"Street","given":"Garrett","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":703759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":703756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"ArchMiller, Althea A.","contributorId":194336,"corporation":false,"usgs":false,"family":"ArchMiller","given":"Althea","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matthiopoulos, Jason","contributorId":194337,"corporation":false,"usgs":false,"family":"Matthiopoulos","given":"Jason","email":"","affiliations":[],"preferred":false,"id":703761,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249244,"text":"70249244 - 2018 - Defining and classifying migratory habitats as sources and sinks: The migratory pathway approach","interactions":[],"lastModifiedDate":"2023-10-03T11:54:03.817211","indexId":"70249244","displayToPublicDate":"2017-06-08T06:51:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Defining and classifying migratory habitats as sources and sinks: The migratory pathway approach","docAbstract":"Background and aims
We characterized fungal endophytes of seeds of invasive, non-native Phragmites from three sites in the Great Lakes region to determine if fungal symbiosis could contribute to invasiveness through their effects on seed germination and seedling growth.
Methods
Field-collected seeds were surface sterilized and plated on agar to culture endophytes for ITS sequencing. Prevalence of specific endophytes from germinated and non-germinated seeds, and from seedlings, was compared.
Results
One-third of 740 seeds yielded endophyte isolates. Fifteen taxa were identified with Alternaria sp. representing 54% of all isolates followed by Phoma sp. (21%) and Penicillium corylophilum (12%). Overall germination of seeds producing an isolate (36%) was significantly higher than seeds not producing an isolate (20%). Penicillium in particular was strongly associated with increased germination of seeds from one site. Sixty-three isolates and 11 taxa were also obtained from 30 seedlings where Phoma, Penicillium and Alternaria respectively were most prevalent. There was a significant effect of isolating an endophyte from the seed on seedling growth.
Conclusions
These results suggest that many endophyte taxa are transmitted in seeds and can increase seed germination and seedling growth of invasive Phragmites. The role of fungal endophytes in host establishment, growth and invasiveness in nature requires further research.
Environmental flows have become important restoration tools on regulated rivers. However, environmental flows are often constrained by other demands within the river system and thus typically are comprised of smaller water volumes than the natural flows they are meant to replace, which can limit their functional efficacy. We review environmental flow programs aimed at restoring riparian vegetation on four arid zone rivers: the Tarim River in China; the Bill Williams River in Arizona, U.S.; the delta of the Colorado River in Mexico; and the Murrumbidgee River in southern Australia. Our goal is to determine what worked and what did not work to accomplish restoration goals. The lower Tarim River in China formerly formed a “green corridor” across the Taklamakan Desert. The riparian zone deteriorated due to diversion of surface and groundwater for irrigated agriculture. A massive restoration program began in 2000 with release of 1038 million cubic meters of water over the first three years. Groundwater levels rose but the ecological response was less than expected politically, socially and within the scientific community. However, releases continued and by 2015 portions of the original iconic Populus euphratica (Euphrates poplar) forest were reestablished. The natural flow regime of the Bill Williams River was disrupted by construction of a dam in 1968, dramatically reducing peak flows along with associated fluvial processes. As a result, the channel narrowed and riparian vegetation expanded and was comprised largely of an introduced shrub species (Tamarix spp.). Environmental flow releases including small, managed floods and sustained base flows have been implemented since the mid 1990’s to promote establishment and maintenance of native riparian trees (cottonwoods and willows) and have been successful, although in a “downsized” portion of the valley bottom. Experience from the Bill Williams was used to help design the Minute 319 environmental flow in the delta of the Colorado River in 2014. Water was released as a short, one-time pulse during spring with the intent of starting new cohorts of cottonwood and willow. However, fluvial disturbance was limited by the relatively small magnitude pulse, low flows did not continue throughout the growing season in some reaches, native tree recruitment was low, and most of the new plants recruited were Tamarix. The inundated portion of the floodplain did respond with a temporary increase in greenness as measured by satellite vegetation indices, however. The Murrumbidgee River in Australia is a tributary in the Murray-Darling River Basin, which supports iconic red gum (Eucalyptus camaldulensis) forests that depend on near-yearly floods for maintenance. During the recent Millennial Drought (2000–2010) environmental flows were provided on an experimental basis to small portions of the Yanga National Forest to see how much water was needed. As with the Colorado River delta, gains in vegetation vigor as measured by satellite vegetation indices following the flows were temporary. Environmental flows in the Bill Williams were able to restore enough overbank flooding and fluvial disturbance to promote some establishment of new cohorts of trees, but on the Colorado and Murrumbidgee Rivers larger volumes of total flows released over longer periods and targeted restoration will be needed to restore the ecosystems. A measure of success in restoring the Euphrates poplar forest on the Tarim and germinating new chorts of willows on the Bill Williams has been achieved after 15–20 years of environmental flows, but the Colorado River delta and Murrumbidgee Rivers have only received one or two flows. Success in enhancing native trees in the Colorado delta has been achieved in restoration plots, but the Murrumbidgee will require large overbank flows on a continuing schedule to rejuvenate the red gum forest.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.01.009","usgsCitation":"Glenn, E., Nagler, P.L., Shafroth, P.B., and Jarchow, C., 2017, Effectiveness of environmental flows for riparian restoration in arid regions: A tale of four rivers: Ecological Engineering, v. 106, no. Part B, p. 695-703, https://doi.org/10.1016/j.ecoleng.2017.01.009.","productDescription":"9 p.","startPage":"695","endPage":"703","ipdsId":"IP-077206","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2017.01.009","text":"Publisher Index Page"},{"id":356190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"Part B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc50ae4b0f5d57878eae8","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":741632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":741631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":741633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":741634,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197311,"text":"70197311 - 2017 - Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales","interactions":[],"lastModifiedDate":"2018-05-29T15:21:46","indexId":"70197311","displayToPublicDate":"2018-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2409,"text":"Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales","title":"Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales","docAbstract":"Although the use of bird-borne data loggers has become widespread in avian field research, the effects of capture and transmitter attachment on behavior and demographic rates are not often measured. Tag- and capture-induced effects on individual behavior, survival and reproduction may limit extrapolation of transmitter data to wider populations. However, measuring individual responses to capture and tagging is a necessary step in developing research techniques that minimize negative effects. We measured the short-term behavioral effects of handling and GPS transmitter attachment on Brown Pelicans under both captive and field conditions, and followed tagged individuals through a full breeding season to assess whether capture and transmitter attachment increased rates of nest abandonment or breeding failure. We observed slight increases in preening among tagged individuals 0–2 h after capture relative to controls that had not been captured or tagged, with a corresponding reduction in time spent resting. One to three days post-capture, nesting behavior of tagged pelicans resembled that of neighbors that had not been captured or tagged. Eighty-eight percent of tagged breeders remained at the same nest location for more than 48 h after capture, attending nests and chicks for an average of 49 days, and 51% were assumed to successfully fledge young. Breeding success was driven primarily by variation in location; however, sex and handling time also influenced the probability of successful breeding in tagged pelicans, suggesting that individual characteristics and the capture process itself can confound the effects of capture and transmitter attachment. We conclude that pelicans fitted with GPS transmitters exhibit comparable behaviors to untagged individuals within a day of capture and that GPS tracking is a viable technique for studying behavior and demography in this species. We also identify measures to minimize post-capture nest abandonment rates in tracking studies, including minimizing handling time and covering nests during processing.
","language":"English","publisher":"Springer","doi":"10.1007/s10336-016-1418-3","usgsCitation":"Lamb, J.S., Satge, Y.G., Fiorello, C.V., and Jodice, P.G., 2017, Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales: Journal of Ornithology, v. 158, no. 2, p. 617-627, https://doi.org/10.1007/s10336-016-1418-3.","productDescription":"11 p.","startPage":"617","endPage":"627","ipdsId":"IP-073599","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10336-016-1418-3","text":"Publisher Index Page"},{"id":354546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.7783203125,\n 25\n ],\n [\n -82,\n 25\n ],\n [\n -82,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"158","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-01","publicationStatus":"PW","scienceBaseUri":"5b155df4e4b092d9651e1b96","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":736677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":736678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiorello, Christine V.","contributorId":172678,"corporation":false,"usgs":false,"family":"Fiorello","given":"Christine","email":"","middleInitial":"V.","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":736679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":736617,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194673,"text":"70194673 - 2017 - Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China)","interactions":[],"lastModifiedDate":"2018-09-20T16:35:26","indexId":"70194673","displayToPublicDate":"2018-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China)","docAbstract":"The strongly deformed Yuleken porphyry Cu deposit (YPCD) occurs in the Kalaxiangar porphyry Cu belt (KPCB), which occupies the central area of the Central Asian Orogenic Belt (CAOB) between the Sawu’er island arc and the Altay Terrane in northern Xinjiang. The YPCD is one of several typical subduction-related deposits in the KPCB, which has undergone syn-collisional and post-collisional metallogenic overprinting. The YPCD is characterized by three pyrite-forming stages, namely a hydrothermal stage A (Py I), a syn-ductile deformation stage B (Py II) characterized by Cu-Au enrichment, and a fracture-filling stage C (Py III). In this study, we conducted systematic petrographic and geochemical studies of pyrites and coexist biotite, which formed during different stages, in order to constrain the physicochemical conditions of the ore formation. Euhedral, fragmented Py I has low Pb and high Te and Se concentration and Ni contents are low with Co/Ni ratios mostly between 1 and 10 (average 9.00). Py I is further characterized by enrichments of Bi, As, Ni, Cu, Te and Se in the core relative to the rim domains. Anhedral round Py II has moderate Co and Ni contents with high Co/Ni ratios >10 (average 95.2), and average contents of 46.5 ppm Pb and 5.80 ppm Te. Py II is further characterized by decreasing Bi, Cu, Pb, Zn, Ag, Te, Mo, Sb and Au contents from the rim to the core domains. Annealed Py III has the lowest Co content of all pyrite types with Co/Ni ratios mostly <0.1 (average 1.33). Furthermore, Py III has average contents of 3.31 ppm Pb, 1.33 ppm Te and 94.6 ppm Se. In addition, Fe does not correlate with Cu and S in the Py I and Py III, while Py II displays a negative correlation between Fe and Cu as well as a positive correlation between Fe and S. Therefore, pyrites which formed during different tectonic regimes also have different chemical compositions. Biotite geothermometer and oxygen fugacity estimates display increasing temperatures and oxygen fugacities from stage A to stage B, while temperature and oxygen fugacities decrease from stage B to stage C. The Co/Ni ratio of pyrite depends discriminates between the different mineralizing stages in the Yuleken porphyry copper deposit: Py II, associated with the deformation stage B and Cu-enrichment, shows higher Co/Ni ratios and enrichments of Pb, Zn, Mo, Te and Sb than the pyrites formed during the other two stages. The Co/Ni ratio of pyrite can not only apply to discriminate the submarine exhalative, magmatic or sedimentary origins for ore deposits but also can distinguish different ore-forming stages in a single porphyry Cu deposit. Thus, Co/Ni ratio of pyrites may act as an important exploration tool to distinguish pyrites from Cu-rich versus barren area. Furthermore, the distribution of Cu, Mo, Pb, Au, Bi, Sb and Zn in the variably deformed pyrite is proportional to the extent of deformation of the pyrites, indicating in accordance with variable physicochemical conditions different element migration behavior during the different stages of deformation and, thus, mineralisation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2017.10.019","usgsCitation":"Hong, T., Xu, X., Gao, J., Peters, S., Li, J., Cao, M., Xiang, P., Wu, C., and You, J., 2017, Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China): Ore Geology Reviews, v. 100, p. 205-219, https://doi.org/10.1016/j.oregeorev.2017.10.019.","productDescription":"15 p.","startPage":"205","endPage":"219","ipdsId":"IP-092178","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2ba","contributors":{"authors":[{"text":"Hong, Tao","contributorId":201265,"corporation":false,"usgs":false,"family":"Hong","given":"Tao","email":"","affiliations":[],"preferred":false,"id":724856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Xing-Wang","contributorId":201266,"corporation":false,"usgs":false,"family":"Xu","given":"Xing-Wang","email":"","affiliations":[],"preferred":false,"id":724857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gao, Jungang","contributorId":201267,"corporation":false,"usgs":false,"family":"Gao","given":"Jungang","email":"","affiliations":[],"preferred":false,"id":724858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Stephen 0000-0002-4431-5675 speters@usgs.gov","orcid":"https://orcid.org/0000-0002-4431-5675","contributorId":167263,"corporation":false,"usgs":true,"family":"Peters","given":"Stephen","email":"speters@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":724855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Jilei","contributorId":201276,"corporation":false,"usgs":false,"family":"Li","given":"Jilei","email":"","affiliations":[],"preferred":false,"id":724859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cao, Mingjian","contributorId":201277,"corporation":false,"usgs":false,"family":"Cao","given":"Mingjian","email":"","affiliations":[],"preferred":false,"id":724860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiang, Peng","contributorId":201270,"corporation":false,"usgs":false,"family":"Xiang","given":"Peng","email":"","affiliations":[],"preferred":false,"id":724861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wu, Chu","contributorId":201272,"corporation":false,"usgs":false,"family":"Wu","given":"Chu","email":"","affiliations":[],"preferred":false,"id":724862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"You, Jun","contributorId":201273,"corporation":false,"usgs":false,"family":"You","given":"Jun","email":"","affiliations":[],"preferred":false,"id":724863,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195008,"text":"70195008 - 2017 - Operationalizing the telecoupling framework for migratory species using the spatial subsidies approach to examine ecosystem services provided by Mexican free-tailed bats","interactions":[],"lastModifiedDate":"2020-09-01T20:33:42.624469","indexId":"70195008","displayToPublicDate":"2018-02-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Operationalizing the telecoupling framework for migratory species using the spatial subsidies approach to examine ecosystem services provided by Mexican free-tailed bats","docAbstract":"Drivers of environmental change in one location can have profound effects on ecosystem services and human well-being in distant locations, often across international borders. The telecoupling provides a conceptual framework for describing these interactions—for example, locations can be defined as sending areas (sources of flows of ecosystem services, energy, or information) or receiving areas (recipients of flows). However, the ability to quantify feedbacks between ecosystem change in one area and societal benefits in other areas requires analytical approaches. We use spatial subsidies—an approach developed to measure the degree to which a migratory species’ ability to provide services in one location depends on habitat in another location—as an example of how telecoupling can be operationalized. Using the cotton pest control and ecotourism services of Mexican free-tailed bats as an example, we determined that of the 16 states in the United States and Mexico where the species resides, three states (Texas, New Mexico, and Colorado) are receiving areas, while the rest of the states are sending areas. In addition, the magnitude of spatial subsidy can be used as an indicator of the degree to which different locations are telecoupled to other locations. In this example, the Mexican free-tailed bat ecosystem services to cotton production and ecotourism in Texas and New Mexico are heavily dependent on winter habitat in four states in central and southern Mexico. In sum, spatial subsidies can be used to operationalize the telecoupling conceptual framework by identifying sending and receiving areas, and by indicating the degree to which locations are telecoupled to other locations.","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ES-09589-220423","usgsCitation":"Lopez Hoffman, L., Diffendorfer, J., Widerholt, R., Thogmartin, W.E., McCraken, G., Medellin, R., Bagstad, K.J., Russell, A., and Semmens, D.J., 2017, Operationalizing the telecoupling framework for migratory species using the spatial subsidies approach to examine ecosystem services provided by Mexican free-tailed bats: Ecology and Society, v. 22, no. 4, 23, 8 p., https://doi.org/10.5751/ES-09589-220423.","productDescription":"23, 8 p.","ipdsId":"IP-085597","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09589-220423","text":"Publisher Index Page"},{"id":350951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.34374999999999,\n 14.179186142354181\n ],\n [\n -90.791015625,\n 14.179186142354181\n ],\n [\n -90.791015625,\n 36.59788913307022\n ],\n [\n -122.34374999999999,\n 36.59788913307022\n ],\n [\n -122.34374999999999,\n 14.179186142354181\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81e0","contributors":{"authors":[{"text":"Lopez Hoffman, Laura","contributorId":201605,"corporation":false,"usgs":false,"family":"Lopez Hoffman","given":"Laura","email":"","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":726550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Widerholt, Ruscena","contributorId":201606,"corporation":false,"usgs":false,"family":"Widerholt","given":"Ruscena","email":"","affiliations":[{"id":17761,"text":"Everglades Foundation","active":true,"usgs":false}],"preferred":false,"id":726551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":726552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCraken, Gary","contributorId":201607,"corporation":false,"usgs":false,"family":"McCraken","given":"Gary","email":"","affiliations":[{"id":36217,"text":"Univ of Tennessee","active":true,"usgs":false}],"preferred":false,"id":726553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Medellin, Rodrigo","contributorId":201608,"corporation":false,"usgs":false,"family":"Medellin","given":"Rodrigo","affiliations":[{"id":36218,"text":"UNAM Mexico City","active":true,"usgs":false}],"preferred":false,"id":726554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":726555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Russell, Amy","contributorId":149129,"corporation":false,"usgs":false,"family":"Russell","given":"Amy","affiliations":[{"id":17656,"text":"Department of Biology, Grand Valley State University, Allendale, MI","active":true,"usgs":false}],"preferred":false,"id":726556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":726557,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198023,"text":"70198023 - 2017 - Geologic overview of the Mars Science Laboratory rover mission at the Kimberley, Gale crater, Mars","interactions":[],"lastModifiedDate":"2018-07-06T14:36:28","indexId":"70198023","displayToPublicDate":"2018-01-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Geologic overview of the Mars Science Laboratory rover mission at the Kimberley, Gale crater, Mars","docAbstract":"The Mars Science Laboratory (MSL) Curiosity rover completed a detailed investigation at the Kimberley waypoint within Gale crater from sols 571-634 using its full science instrument payload. From orbital images examined early in the Curiosity mission, the Kimberley region had been identified as a high-priority science target based on its clear stratigraphic relationships in a layered sedimentary sequence that had been exposed by differential erosion. Observations of the stratigraphic sequence at the Kimberley made by Curiosity are consistent with deposition in a prograding, fluvio-deltaic system during the late Noachian to early Hesperian, prior to the existence of most of Mt. Sharp. Geochemical and mineralogic analyses suggest that sediment deposition likely took place under cold conditions with relatively low water-to-rock ratios. Based on elevated K2O abundances throughout the Kimberley formation, an alkali feldspar protolith is likely one of several igneous sources from which the sediments were derived. After deposition, the rocks underwent multiple episodes of diagenetic alteration with different aqueous chemistries and redox conditions, as evidenced by the presence of Ca-sulfate veins, Mn-oxide fracture-fills, and erosion-resistant nodules. More recently, the Kimberley has been subject to significant aeolian abrasion and removal of sediments to create modern topography that slopes away from Mt. Sharp, a process that has continued to the present day.
Several cubic kilometers of Paleozoic graphite-bearing argillitic country rocks are present as lithic fragments in Bishop Tuff ignimbrite and fallout. The lithics were entrained by the 650 km3 of rhyolite magma that vented during the 5- to 6-day-long, caldera-forming eruption at Long Valley, California. The caldera is floored by a 350 km2 roof plate that collapsed during the eruption and consists in large part of the Paleozoic strata that provided the abundant hornfelsed metapelitic lithic clasts in the tuff. Graphite has been identified by Raman spectroscopy, electron-dispersive spectroscopy, and X-ray diffraction as an irregularly dispersed component in the small fraction of Bishop Tuff pumice that is dark-colored. Carbon concentration has been determined in pumice, lithics, and wall rocks. Values of δ13C range from –21‰ to –29‰ Vienna Peedee Belemnite (VPDB) for pumice, lithics, and argillitic wall rocks, reflecting the biogenic origin of the reduced carbon in oxygen-limited black Paleozoic marine mudrocks. Carbonate contents, measured separately, are negligible in fresh pumice and lithics. Microprobe analyses of titanomagnetite-ilmenite pairs show that oxygen-fugacity values of numerous batches of postcaldera Early Rhyolite (750–640 ka; ~100 km3) are up to one log unit more reduced than those of the temperature–oxygen fugacity (T-fO2) array of the Bishop Tuff (767 ka), despite similar major-element compositions and Fe-Ti–oxide temperature ranges. All of the many batches of Early Rhyolite, which erupted episodically over an interval of ~125,000 years, yield the reduced fO2 values, indicating that reaction with graphite lowered magmatic fO2 after the caldera-forming eruption but before the first eruption of Early Rhyolite. It is inferred that reaction of postcaldera rhyolite magma with the reduced carbon in a great mass of subsided roof rocks lowered its fO2. It is suggested that comparable effects could have attended caldera collapse of other magma chambers hosted in continental sedimentary rocks.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01548.1","usgsCitation":"Hildreth, E., Ryan-Davis, J., and Harlow, B., 2017, Graphite in the Bishop Tuff and its effect on postcaldera oxygen fugacity: Geosphere, v. 14, no. 1, p. 343-359, https://doi.org/10.1130/GES01548.1.","productDescription":"17p.","startPage":"343","endPage":"359","ipdsId":"IP-082658","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":461321,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01548.1","text":"Publisher Index Page"},{"id":353117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Long Valley caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.1,\n 37.75\n ],\n [\n -119.67,\n 37.75\n ],\n [\n -119.67,\n 37.5\n ],\n [\n -119.1,\n 37.5\n ],\n [\n -119.1,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-28","publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2c4","contributors":{"authors":[{"text":"Hildreth, Edward 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":146999,"corporation":false,"usgs":true,"family":"Hildreth","given":"Edward","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":732582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryan-Davis, Juliet 0000-0001-7048-5937 jryan-davis@usgs.gov","orcid":"https://orcid.org/0000-0001-7048-5937","contributorId":193071,"corporation":false,"usgs":true,"family":"Ryan-Davis","given":"Juliet","email":"jryan-davis@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":732581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harlow, Benjamin","contributorId":203879,"corporation":false,"usgs":false,"family":"Harlow","given":"Benjamin","email":"","affiliations":[{"id":36739,"text":"Stable Isotope Core Laboratory, School of Biological Sciences, Washington State Universtity","active":true,"usgs":false}],"preferred":false,"id":732583,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205968,"text":"70205968 - 2017 - Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","interactions":[],"lastModifiedDate":"2019-10-11T17:22:03","indexId":"70205968","displayToPublicDate":"2017-12-31T17:20:04","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","title":"Characterization of microsatellite loci for the Gulf Coast waterdog (Necturus beyeri) using paired-end Illumina shotgun sequencing and cross-amplification in other Necturus","docAbstract":"Amphibians are one of the most threatened groups of vertebrates (Stuart et al. 2004; Wake and Vredenburg 2008), and the application of molecular techniques to amphibian ecology and genetics has dramatically improved our ability to conserve species and populations (see Shaffer et al. [2015] for review). Microsatellites, tandem repeats of two to six nucleotides in the nuclear genome, are highly variable molecular markers that can be used to describe gene flow and genetic diversity, each of which is positively correlated with population persistence (Allendorf and Luikart 2007; Allentoft and O’Brien 2010; Avise 2004; Selkoe and Toonen 2006). Microsatellite loci have frequently been applied to studies involving terrestrial and pond breeding amphibians (Emel and Storfer 2012), but fewer studies have focused on taxa inhabiting lotic systems (Emel and Storfer 2012). For example, studies characterizing microsatellite loci are completely lacking for a group of permanently aquatic salamanders, the waterdogs and mudpuppies (Family Proteidae, Genus Necturus) (Rafinesque 1819).
The genus Necturus consists of several species of perennibranch salamanders that can be found throughout many freshwater streams, rivers, and lakes in North America (Petranka 1998). Some authorities recognize five species (Crother 2012; Petranka 1998), including the Mudpuppy (Necturus maculosus) (Rafinesque 1819), Gulf Coast Waterdog (N. beyeri) (Viosca 1937), Black Warrior Waterdog (N. alabamensis) (Viosca 1937), Neuse River Waterdog (N. lewisi) (Brimley 1924), and Dwarf Waterdog (N. punctatus) (Gibbes 1850). This taxonomy also recognizes two subspecies within N. maculosus, including the Common Mudpuppy (N. m. maculosus) and the Red River Waterdog (N. m. louisianensis) (Crother 2012; Petranka 1998; Schmidt 1953). Other authorities suggest that there are six or seven species within Necturus (Collins 1990; Frost 2016; Powell et al. 2016). These more diverse schemes recognize each of the aforementioned five species while also elevating the Red River Waterdog (N. louisianensis) (Collins 1990; Frost 2016; Powell et al. 2016; Viosca 1938) and Löding’s Waterdog (N. lödingi or N. cf. beyeri) (Bart et al. 1997; Guyer 2005a; Viosca 1938). Allozyme work by Guttman et al. (1990) suggests that there is at least one cryptic species of Necturus in drainages east of the Mobile Basin and south of the Alabama River, and both Bart et al. (1997) and Guyer (2005a) advise that these populations should be referred to as N. cf. beyeri. However, until range wide studies incorporating genetic and other data are published, we will follow the five species taxonomy outlined by Crother (2012) while acknowledging that certain taxa, such as N. maculosus and N. beyeri, may require systematic revision.
Geologic features, particularly volcanic features, have been protected by the National Park Service since its inception. Some volcanic areas were nationally protected even before the National Park Service was established. The first national park, Yellowstone National Park, is one of the most widely known geothermal and volcanic areas in the world. It contains the largest volcanic complex in North America and has experienced three eruptions which rate among the largest eruptions known to have occurred on Earth. Half of the twelve areas established as national parks before the 1916 Organic Act which created the National Park Service are centered on volcanic features. The National Park Service now manages lands that contain nearly every conceivable volcanic resource, with at least seventy-six managed lands that contain volcanoes or volcanic rocks. Given that so many lands managed by the National Park Service contain volcanoes and volcanic rocks, we cannot give an overview of the history of each one; rather we highlight four notable examples of parks that were established on account of their volcanic landscapes. These parks all helped to encourage the creation and success of the National Park Service by inspiring the imagination of the public. In addition to preserving and providing access to the nation's volcanic heritage, volcanic national parks are magnificent places to study and understand volcanoes and volcanic landscapes in general. Scientists from around the world study volcanic hazards, volcanic history, and the inner working of the Earth within U.S. national parks. Volcanic landscapes and associated biomes that have been relatively unchanged by human and economic activities provide unique natural laboratories for understanding how volcanoes work, how we might predict eruptions and hazards, and how these volcanoes affect surrounding watersheds, flora, fauna, atmosphere, and populated areas.
","language":"English","publisher":"History of the Earth Sciences Society","doi":"10.17704/1944-6178-36.2.197","usgsCitation":"Walkup, L., Casadevall, T., and Santucci, V.L., 2017, Born of fire: In search of volcanoes in U.S. national parks, four striking examples: Earth Sciences History, v. 36, no. 2, p. 197-244, https://doi.org/10.17704/1944-6178-36.2.197.","productDescription":"45 p.","startPage":"197","endPage":"244","ipdsId":"IP-084133","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":365090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"36","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walkup, Laura 0000-0002-1962-5364","orcid":"https://orcid.org/0000-0002-1962-5364","contributorId":205009,"corporation":false,"usgs":true,"family":"Walkup","given":"Laura","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casadevall, Thomas 0000-0002-9447-6864","orcid":"https://orcid.org/0000-0002-9447-6864","contributorId":216616,"corporation":false,"usgs":true,"family":"Casadevall","given":"Thomas","affiliations":[],"preferred":false,"id":765166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santucci, Vincent L.","contributorId":192886,"corporation":false,"usgs":false,"family":"Santucci","given":"Vincent","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":765165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219001,"text":"70219001 - 2017 - Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization","interactions":[],"lastModifiedDate":"2021-04-20T11:56:57.637835","indexId":"70219001","displayToPublicDate":"2017-12-31T08:49:40","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization","docAbstract":"Raman spectroscopy has been suggested as a method for characterizing the thermal maturity of rocks. The literature contains many empirical correlations between thermal maturity proxies, such as vitrinite reflectance (VRo) and pyrolysis-Tmax, with spectral metrics such as Raman peak-widths, peak-center positions, peak-areas and all manner of differences and ratios of these parameters. However, while these correlations may be convincing for small data sets from limited sample series, broader application of these metrics to disparate and heterogeneous samples proves difficult and there remains no consensus.
In this extended abstract, Raman spectroscopy is introduced and the history of Raman analysis of carbonaceous material is briefly outlined, highlighting some of the latent difficulties and potential sources of bias. We suggest the organization of a community working group to establish terminology, guidelines, procedures and standards necessary for the successful development of this technique to characterize organic matter in an accessible, unbiased, and reproducible manner.
For the present multi-phase study, immature shale samples from the Bakken and Duvernay formations were subjected to hydrous pyrolysis for 72 hours at temperatures from 280°C to 360°C. Rock residues were mounted and polished for analysis via confocal laser-scanning Raman microscopy and reflectance. The maturation series from the Bakken was randomized for the Phase-I single-blind study to be presented at this conference. For the Phase-II study, solid bitumen reflectance (BRo) values for the Duvernay series will be known.
Multiple hyperspectral maps were collected from each Bakken sample, with each map consisting of a single diffraction-limited spot-size spectrum per 1 µm2 in rectangular areas several hundred micrometers on a side. Initial attempts at using basic spectral metrics on small numbers of hand-selected spectra to sort the blind series produced inconclusive results: any number of possible correlations could be found. In an improved approach, the statistics of the full spectral datasets were leveraged to: 1) objectively identify organic carbon types (OCTs) in a given map based on Raman and fluorescence spectral characteristics, 2) identify those OCTs in other maps from the same sample and determine if the heterogeneity of the sample has been adequately characterized, and 3) identify the same OCTs in maps from other samples in the maturation series. In ongoing work, our goals are to: 1) use these analyses of the blind series to develop a hypothesis for a correlation to maturation, 2) test the hypothesis by applying the same analyses to the known Duvernay series (in Phase-II), 3) if necessary refine the hypothesis based on observations from the Duvernay analysis, and 4) finally reveal the true order of the Bakken series to verify if the hypothesized correlation accurately predicts the maturity order of the samples.
In this document, we share progress to date. The analysis of one area of interest is detailed showing the differentiation of two OCTs based on Raman and fluorescence spectral features, including the use of 2-factor histograms, Principle Components Analysis (PCA), and Nonlinear Iterative Peak Fitting (NIPF).
","conferenceTitle":"Unconventional Resources Technology Conference","conferenceDate":"July 24-26, 2017","conferenceLocation":"Austin, TX","language":"English","publisher":"Curran Associates","doi":"10.15530/urtec-2017-2671253","usgsCitation":"Myers, G.A., Kehoe, K., and Hackley, P.C., 2017, Analysis of artificially matured shales with confocal laser scanning raman microscopy: Applications to organic matter characterization, Unconventional Resources Technology Conference, Austin, TX, July 24-26, 2017, 2671253, 16 p., https://doi.org/10.15530/urtec-2017-2671253.","productDescription":"2671253, 16 p.","ipdsId":"IP-086591","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":385188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Grant A.","contributorId":255533,"corporation":false,"usgs":false,"family":"Myers","given":"Grant","email":"","middleInitial":"A.","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":814475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kehoe, Kelsey","contributorId":255534,"corporation":false,"usgs":false,"family":"Kehoe","given":"Kelsey","email":"","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":814476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812433,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195641,"text":"70195641 - 2017 - Reproductive success of Mariana swiftlets (Aerodramus bartschi) on the Hawaiian island of O'ahu","interactions":[],"lastModifiedDate":"2018-02-24T10:50:07","indexId":"70195641","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive success of Mariana swiftlets (Aerodramus bartschi) on the Hawaiian island of O'ahu","title":"Reproductive success of Mariana swiftlets (Aerodramus bartschi) on the Hawaiian island of O'ahu","docAbstract":"Mariana Swiftlets (Aerodramus bartschi) are federally listed as endangered, with populations currently limited to just three islands in the Mariana Islands plus an introduced population on the Hawaiian island of O'ahu. Before efforts are made to reintroduce Mariana Swiftlets to other islands in the Mariana archipelago, additional information is needed concerning their breeding biology. Therefore, our objective was to examine the reproductive biology of Mariana Swiftlets over five annual cycles on the Hawaiian island of O'ahu. This introduced population used a human-made tunnel for roosting and nesting, and was studied as a surrogate to negate interference with endangered populations in the Mariana Islands. Active nests (N = 478) were observed in every month of the year, with peak nesting activity between May and September. All clutches consisted of one egg. Mean duration of incubation and nestling periods were 23.9 d (range = 18–30 d, N = 233) and 55.0 d (range = 41–84 d, N = 228), respectively. Estimated nest success was 63%. Over half (52%) of nest failures were attributed to eggs found on the tunnel floor. Predation by rats (Rattus spp.) was also an important cause of nest failure and often resulted in the loss of most active nests. However, Mariana Swiftlets did re-nest after these predation events. Our results suggest that rat predation of both nests and adults may limit growth of the Mariana Swiftlet population on O'ahu, and could also affect the chances for successful establishment of relocated populations in the Mariana Islands. Another limiting factor on O'ahu is that only one nesting site is apparently available on the island. Current goals for downlisting Mariana Swiftlets from endangered to threatened include establishing populations on Guam, Rota, Aguiguan, and Saipan. To meet these goals, the population of Mariana Swiftlets on O'ahu can be important for testing reintroduction techniques, learning more about the natural history of these swiftlets, and providing individuals for reintroduction efforts in the Mariana Islands.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12236","usgsCitation":"Johnson, N.C., Haig, S.M., Mosher, S.M., and Hollenbeck, J.P., 2017, Reproductive success of Mariana swiftlets (Aerodramus bartschi) on the Hawaiian island of O'ahu: Journal of Field Ornithology, v. 88, no. 4, p. 362-373, https://doi.org/10.1111/jofo.12236.","productDescription":"12 p.","startPage":"362","endPage":"373","ipdsId":"IP-080242","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":438118,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T43S1J","text":"USGS data release","linkHelpText":"Nest success and predation data for Mariana swiftlets (Aerodramus bartschi), Hawai'i, USA, 2006-2011"},{"id":351981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.35418701171875,\n 21.128059607618706\n ],\n [\n -157.58789062499997,\n 21.128059607618706\n ],\n [\n -157.58789062499997,\n 21.785006291915956\n ],\n [\n -158.35418701171875,\n 21.785006291915956\n ],\n [\n -158.35418701171875,\n 21.128059607618706\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-15","publicationStatus":"PW","scienceBaseUri":"5afee789e4b0da30c1bfc2e6","contributors":{"authors":[{"text":"Johnson, Nathan C. ncjohnson@usgs.gov","contributorId":196296,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"ncjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":729529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":729528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosher, Stephen M.","contributorId":202753,"corporation":false,"usgs":false,"family":"Mosher","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":36522,"text":"U.S. Navy","active":true,"usgs":false}],"preferred":false,"id":729530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollenbeck, Jeff P. 0000-0001-6481-5354 jhollenbeck@usgs.gov","orcid":"https://orcid.org/0000-0001-6481-5354","contributorId":5130,"corporation":false,"usgs":true,"family":"Hollenbeck","given":"Jeff","email":"jhollenbeck@usgs.gov","middleInitial":"P.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":729531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196355,"text":"70196355 - 2017 - Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation","interactions":[],"lastModifiedDate":"2018-04-03T14:24:41","indexId":"70196355","displayToPublicDate":"2017-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation","docAbstract":"Free-flowing river segments provide refuges for many imperiled aquatic biota that have been extirpated elsewhere in their native ranges. These biodiversity refuges are also foci of conservation concerns because species persisting within isolated habitat fragments may be particularly vulnerable to local environmental change. We have analyzed long-term (14- and 20-y) survey data to assess evidence of fish species declines in two southeastern U.S. rivers where managers and stakeholders have identified potentially detrimental impacts of current and future land uses. The Conasauga River (Georgia and Tennessee) and the Etowah River (Georgia) form free-flowing headwaters of the extensively dammed Coosa River system. These rivers are valued in part because they harbor multiple species of conservation concern, including three federally endangered and two federally threatened fishes. We used data sets comprising annual surveys for fish species at multiple, fixed sites located at river shoals to analyze occupancy dynamics and temporal changes in species richness. Our analyses incorporated repeated site-specific surveys in some years to estimate and account for incomplete species detection, and test for species-specific (rarity, mainstem-restriction) and year-specific (elevated frequencies of low- or high-flow days) covariates on occupancy dynamics. In the Conasauga River, analysis of 26 species at 13 sites showed evidence of temporal declines in colonization rates for nearly all taxa, accompanied by declining species richness. Four taxa (including one federally endangered species) had reduced occupancy across the Conasauga study sites, with three of these taxa apparently absent for at least the last 5 y of the study. In contrast, a similar fauna of 28 taxa at 10 sites in the Etowah River showed no trends in species persistence, colonization, or occupancy. None of the tested covariates showed strong effects on persistence or colonization rates in either river. Previous studies and observations identified contaminants, nutrient loading, or changes in benthic habitat as possible causes for fish species declines in the Conasauga River. Our analysis provides baseline information that could be used to assess effectiveness of future management actions in the Conasauga or Etowah rivers, and illustrates the use of dynamic occupancy models to evaluate evidence of faunal decline from time-series data.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/122016-JFWM-090","usgsCitation":"Freeman, M., Hagler, M.M., Bumpers, P.M., Wheeler, K., Wenger, S., and Freeman, B.J., 2017, Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 418-434, https://doi.org/10.3996/122016-JFWM-090.","productDescription":"17p.","startPage":"418","endPage":"434","ipdsId":"IP-082143","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Conasauga River, Etowah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.49560546875,\n 33.99802726234877\n ],\n [\n -83.9959716796875,\n 33.99802726234877\n ],\n [\n -83.9959716796875,\n 35.007502842952896\n ],\n [\n -85.49560546875,\n 35.007502842952896\n ],\n [\n -85.49560546875,\n 33.99802726234877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-01","publicationStatus":"PW","scienceBaseUri":"5afee789e4b0da30c1bfc2e2","contributors":{"authors":[{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":732551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagler, Megan M.","contributorId":203870,"corporation":false,"usgs":false,"family":"Hagler","given":"Megan","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bumpers, Phillip M.","contributorId":203871,"corporation":false,"usgs":false,"family":"Bumpers","given":"Phillip","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheeler, Kit","contributorId":203872,"corporation":false,"usgs":false,"family":"Wheeler","given":"Kit","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":732555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Byron J.","contributorId":49782,"corporation":false,"usgs":false,"family":"Freeman","given":"Byron","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":732556,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226960,"text":"70226960 - 2017 - Element partitioning in magnetite under low-grade metamorphic conditions – A case study from the Proterozoic Belt Supergroup, USA","interactions":[],"lastModifiedDate":"2021-12-22T12:51:20.668789","indexId":"70226960","displayToPublicDate":"2017-12-22T06:49:49","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1593,"text":"European Journal of Mineralogy","active":true,"publicationSubtype":{"id":10}},"title":"Element partitioning in magnetite under low-grade metamorphic conditions – A case study from the Proterozoic Belt Supergroup, USA","docAbstract":"The distribution and partitioning of elements in igneous rocks is well established for various melt –(fluid) –solid pairs and provides important insights into the petrogenesis of these rocks. Studies of the partitioning behavior of elements under metamorphic conditions are scarce and commonly focus on high-grade metamorphic facies. Little is known about the partitioning behavior of elements under low-grade metamorphic conditions. Greenschist-facies metasedimentary rocks of the North American Belt Supergroup host magnetite that displays equilibrium features with co-existing mineral phases such as quartz and carbonate. Magnetite is an ideal target for geochemical investigations because it can incorporate a large number of cations and is sensitive to changes in temperature, oxygen fugacity, pressure, whole-rock composition, and cooling trends. Whole-rock major and trace element analyses have been undertaken on representative samples from Belt Supergroup metasedimentary rocks using X-ray luorescence. Electron microprobe and laser ablation ICP-MS were used to obtain major and trace element concentrations for magnetite hosted in these rocks. Stable-isotope geothermometry of magnetite–quartz and magnetite–carbonate pairs constrain metamorphic temperatures to ca. 390°C. Partition coefficients (D) for magnetite–matrix pairs presumably reflect equilibrium at these low-grade metamorphic conditions. Except for Mn and Ni, which show comparable partition coefficients, the calculated values are one to two orders of magnitude lower than those for igneous magnetite. Aluminum displays the lowest calculated partition coefficient with a value of 0.006 and Ni and Fe the highest values with 6.3 and 20.9, respectively. Of the elements that commonly occur in spinel-group minerals, two groups can be distinguished: (1) elements that preferentially partition into the host rock (D<1): Al, Mg, Pb, and Ti and (2) elements that show a preference to partition into magnetite (D>1): Zn, Mn, Cr, V, Ni, and Fe.
","language":"English","publisher":"Shweizerbart Science","doi":"10.1127/ejm/2017/0029-2657","usgsCitation":"Nadoll, P., Mauk, J.L., Hayes, T., Koenig, A., and Box, S.E., 2017, Element partitioning in magnetite under low-grade metamorphic conditions – A case study from the Proterozoic Belt Supergroup, USA: European Journal of Mineralogy, v. 29, no. 5, p. 795-805, https://doi.org/10.1127/ejm/2017/0029-2657.","productDescription":"11 p.","startPage":"795","endPage":"805","ipdsId":"IP-079866","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":393293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nadoll, Patrick 0000-0002-4061-7203","orcid":"https://orcid.org/0000-0002-4061-7203","contributorId":270292,"corporation":false,"usgs":false,"family":"Nadoll","given":"Patrick","email":"","affiliations":[{"id":56136,"text":"Friedrich-Alexander Universität Erlangen-Nürnberg","active":true,"usgs":false}],"preferred":false,"id":828943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Timothy 0000-0002-1224-4219","orcid":"https://orcid.org/0000-0002-1224-4219","contributorId":206109,"corporation":false,"usgs":true,"family":"Hayes","given":"Timothy","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koenig, Alan 0000-0002-5230-0924","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":206119,"corporation":false,"usgs":true,"family":"Koenig","given":"Alan","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828946,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":828947,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194659,"text":"70194659 - 2017 - Increased sediment load during a large-scale dam removal changes nearshore subtidal communities","interactions":[],"lastModifiedDate":"2017-12-11T11:55:12","indexId":"70194659","displayToPublicDate":"2017-12-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Increased sediment load during a large-scale dam removal changes nearshore subtidal communities","docAbstract":"The coastal marine ecosystem near the Elwha River was altered by a massive sediment influx—over 10 million tonnes—during the staged three-year removal of two hydropower dams. We used time series of bathymetry, substrate grain size, remotely sensed turbidity, scuba dive surveys, and towed video observations collected before and during dam removal to assess responses of the nearshore subtidal community (3 m to 17 m depth). Biological changes were primarily driven by sediment deposition and elevated suspended sediment concentrations. Macroalgae, predominantly kelp and foliose red algae, were abundant before dam removal with combined cover levels greater than 50%. Where persistent sediment deposits formed, macroalgae decreased greatly or were eliminated. In areas lacking deposition, macroalgae cover decreased inversely to suspended sediment concentration, suggesting impacts from light reduction or scour. Densities of most invertebrate and fish taxa decreased in areas with persistent sediment deposition; however, bivalve densities increased where mud deposited over sand, and flatfish and Pacific sand lance densities increased where sand deposited over gravel. In areas without sediment deposition, most invertebrate and fish taxa were unaffected by increased suspended sediment or the loss of algae cover associated with it; however, densities of tubeworms and flatfish, and primary cover of sessile invertebrates increased suggesting benefits of increased particulate matter or relaxed competition with macroalgae for space. As dam removal neared completion, we saw evidence of macroalgal recovery that likely owed to water column clearing, indicating that long-term recovery from dam removal effects may be starting. Our results are relevant to future dam removal projects in coastal areas and more generally to understanding effects of increased sedimentation on nearshore subtidal benthic communities.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0187742","usgsCitation":"Rubin, S., Miller, I.M., Foley, M.M., Berry, H.D., Duda, J., Hudson, B., Elder, N.E., Beirne, M.M., Warrick, J.A., McHenry, M.L., Stevens, A.W., Eidam, E., Ogston, A., Gelfenbaum, G.R., and Pedersen, R., 2017, Increased sediment load during a large-scale dam removal changes nearshore subtidal communities: PLoS ONE, v. 12, no. 12, p. 1-46, https://doi.org/10.1371/journal.pone.0187742.","productDescription":"e0187742; 46 p.","startPage":"1","endPage":"46","ipdsId":"IP-088231","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469239,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0187742","text":"Publisher Index Page"},{"id":438127,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JS9PDK","text":"USGS data release","linkHelpText":"Data collected in 2008-2014 to assess nearshore subtidal community response to increased sediment load during removal of the Elwha River dams, Washington State, USA"},{"id":349906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River, Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.70605468750001,\n 48.09459164290992\n ],\n [\n -123.22677612304688,\n 48.09459164290992\n ],\n [\n -123.22677612304688,\n 48.177991372208\n ],\n [\n -123.70605468750001,\n 48.177991372208\n ],\n [\n -123.70605468750001,\n 48.09459164290992\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-08","publicationStatus":"PW","scienceBaseUri":"5a60faeae4b06e28e9c2297a","contributors":{"authors":[{"text":"Rubin, Stephen P. 0000-0003-3054-7173 srubin@usgs.gov","orcid":"https://orcid.org/0000-0003-3054-7173","contributorId":189436,"corporation":false,"usgs":true,"family":"Rubin","given":"Stephen P.","email":"srubin@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":724794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Melissa M. 0000-0002-5832-6404 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0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724807,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Pedersen, Rob","contributorId":201259,"corporation":false,"usgs":false,"family":"Pedersen","given":"Rob","email":"","affiliations":[],"preferred":false,"id":724808,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70194640,"text":"70194640 - 2017 - Navigating translational ecology: Creating opportunities for scientist participation","interactions":[],"lastModifiedDate":"2017-12-07T16:25:04","indexId":"70194640","displayToPublicDate":"2017-12-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Navigating translational ecology: Creating opportunities for scientist participation","docAbstract":"Interest in translational ecology (TE) – a research approach that yields useful scientific outcomes through ongoing collaboration between scientists and stakeholders – is growing among both of these groups. Translational ecology brings together participants from different cultures and with different professional incentives. We address ways to cultivate a culture of TE, such as investing time in understanding one another's decision context and incentives, and outline common entry points to translational research, such as working through boundary organizations, building place-based research programs, and being open to opportunities as they arise. We also highlight common institutional constraints on scientists and practitioners, and ways in which collaborative research can overcome these limitations, emphasizing considerations for navigating TE within current institutional frameworks, but also pointing out ways in which institutions are evolving to facilitate translational research approaches.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.1734","usgsCitation":"Hallett, L.M., Morelli, T.L., Gerber, L.R., Moritz, M.A., Schwartz, M.W., Stephenson, N.L., Tank, J.L., Williamson, M.A., and Woodhouse, C.A., 2017, Navigating translational ecology: Creating opportunities for scientist participation: Frontiers in Ecology and the Environment, v. 15, no. 10, p. 578-586, https://doi.org/10.1002/fee.1734.","productDescription":"9 p.","startPage":"578","endPage":"586","ipdsId":"IP-074729","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469241,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.1734","text":"Publisher Index Page"},{"id":349876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faeae4b06e28e9c22985","contributors":{"authors":[{"text":"Hallett, Lauren M.","contributorId":175310,"corporation":false,"usgs":false,"family":"Hallett","given":"Lauren","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":724699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerber, Leah R.","contributorId":147236,"corporation":false,"usgs":false,"family":"Gerber","given":"Leah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":724700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moritz, Max A.","contributorId":182434,"corporation":false,"usgs":false,"family":"Moritz","given":"Max","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwartz, Mark W.","contributorId":145938,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":724702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":724697,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tank, Jennifer L.","contributorId":201231,"corporation":false,"usgs":false,"family":"Tank","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":724703,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williamson, Matthew A.","contributorId":201232,"corporation":false,"usgs":false,"family":"Williamson","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724704,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":724705,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195106,"text":"70195106 - 2017 - Considerations in comparing the U.S. Geological Survey one‐year induced‐seismicity hazard models with “Did You Feel It?” and instrumental data","interactions":[],"lastModifiedDate":"2018-02-08T12:43:25","indexId":"70195106","displayToPublicDate":"2017-12-06T00:00:00","publicationYear":"2017","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":"Considerations in comparing the U.S. Geological Survey one‐year induced‐seismicity hazard models with “Did You Feel It?” and instrumental data","docAbstract":"The recent steep increase in seismicity rates in Oklahoma, southern Kansas, and other parts of the central United States led the U.S. Geological Survey (USGS) to develop, for the first time, a probabilistic seismic hazard forecast for one year (2016) that incorporates induced seismicity. In this study, we explore a process to ground‐truth the hazard model by comparing it with two databases of observations: modified Mercalli intensity (MMI) data from the “Did You Feel It?” (DYFI) system and peak ground acceleration (PGA) values from instrumental data. Because the 2016 hazard model was heavily based on earthquake catalogs from 2014 to 2015, this initial comparison utilized observations from these years. Annualized exceedance rates were calculated with the DYFI and instrumental data for direct comparison with the model. These comparisons required assessment of the options for converting hazard model results and instrumental data from PGA to MMI for comparison with the DYFI data. In addition, to account for known differences that affect the comparisons, the instrumental PGA and DYFI data were declustered, and the hazard model was adjusted for local site conditions. With these adjustments, examples at sites with the most data show reasonable agreement in the exceedance rates. However, the comparisons were complicated by the spatial and temporal completeness of the instrumental and DYFI observations. Furthermore, most of the DYFI responses are in the MMI II–IV range, whereas the hazard model is oriented toward forecasts at higher ground‐motion intensities, usually above about MMI IV. Nevertheless, the study demonstrates some of the issues that arise in making these comparisons, thereby informing future efforts to ground‐truth and improve hazard modeling for induced‐seismicity applications.
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Hawaii","interactions":[],"lastModifiedDate":"2020-10-06T20:29:25.699679","indexId":"70194645","displayToPublicDate":"2017-12-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling fine-scale coral larval dispersal and interisland connectivity to help designate mutually-supporting coral reef marine protected areas: Insights from Maui Nui, Hawaii","docAbstract":"Connectivity among individual marine protected areas (MPAs) is one of the most important considerations in the design of integrated MPA networks. To provide such information for managers in Hawaii, USA, a numerical circulation model was developed to determine the role of ocean currents in transporting coral larvae from natal reefs throughout the high volcanic islands of the Maui Nui island complex in the southeastern Hawaiian Archipelago. Spatially- and temporally-varying wind, wave, and circulation model outputs were used to drive a km-scale, 3-dimensional, physics-based circulation model for Maui Nui. The model was calibrated and validated using satellite-tracked ocean surface current drifters deployed during coral-spawning conditions, then used to simulate the movement of the larvae of the dominant reef-building coral, Porites compressa, from 17 reefs during eight spawning events in 2010–2013. These simulations make it possible to investigate not only the general dispersal patterns from individual coral reefs, but also how anomalous conditions during individual spawning events can result in large deviations from those general patterns. These data also help identify those reefs that are dominated by self-seeding and those where self-seeding is limited to determine their relative susceptibility to stressors and potential roadblocks to recovery. Overall, the numerical model results indicate that many of the coral reefs in Maui Nui seed reefs on adjacent islands, demonstrating the interconnected nature of the coral reefs in Maui Nui and providing a key component of the scientific underpinning essential for the design of a mutually supportive network of MPAs to enhance conservation of coral reefs.
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Although variability in water-year precipitation explains more of the variability in water-year UCRB streamflow than water-year UCRB temperature, since the late 1980s, increases in temperature in the UCRB have caused a substantial reduction in UCRB runoff efficiency (the ratio of streamflow to precipitation). These reductions in flow because of increasing temperatures are the largest documented temperature-related reductions since record keeping began. Increases in UCRB temperature over the past three decades have resulted in a mean UCRB water-year streamflow departure of −1306 million m3 (or −7% of mean water-year streamflow). Additionally, warm-season (April through September) temperature has had a larger effect on variability in water-year UCRB streamflow than the cool-season (October through March) temperature. The greater contribution of warm-season temperature, relative to cool-season temperature, to variability of UCRB flow suggests that evaporation or snowmelt, rather than changes from snow to rain during the cool season, has driven recent reductions in UCRB flow. It is expected that as warming continues, the negative effects of temperature on water-year UCRB streamflow will become more evident and problematic.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-17-0007.1","usgsCitation":"McCabe, G.J., Wolock, D.M., Pederson, G.T., Woodhouse, C.A., and McAfee, S., 2017, Evidence that recent warming is reducing upper Colorado River flows: Earth Interactions, v. 21, no. 10, p. 1-14, https://doi.org/10.1175/EI-D-17-0007.1.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-082888","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":469255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-17-0007.1","text":"Publisher Index Page"},{"id":405898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"upper Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.90673828125,\n 36.52288052805137\n ],\n [\n -111.796875,\n 36.48755716938576\n ],\n [\n -108.65478515625,\n 35.40696093270201\n ],\n [\n -108.28125,\n 35.53222622770337\n ],\n [\n -107.09472656249999,\n 36.56260003738545\n ],\n [\n -106.41357421875,\n 38.13455657705411\n ],\n [\n -105.5126953125,\n 39.57182223734374\n ],\n [\n -105.62255859375,\n 40.22921818870117\n ],\n [\n -106.74316406249999,\n 41.47566020027821\n ],\n [\n -108.017578125,\n 43.03677585761058\n ],\n [\n -109.62158203125,\n 43.50075243569041\n ],\n [\n -110.478515625,\n 43.54854811091286\n ],\n [\n -110.80810546875,\n 43.29320031385282\n ],\n [\n -110.93994140625,\n 41.672911819602085\n ],\n [\n -111.15966796875,\n 41.42625319507269\n ],\n [\n -111.46728515624999,\n 40.613952441166596\n ],\n [\n -112.0166015625,\n 39.58875727696545\n ],\n [\n -112.30224609374999,\n 38.09998264736481\n ],\n [\n -112.32421875,\n 37.125286284966805\n ],\n [\n -111.90673828125,\n 36.52288052805137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"10","noUsgsAuthors":false,"publicationDate":"2017-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":850257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":850259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":850260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":850261,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195325,"text":"70195325 - 2017 - A statistical method to predict flow permanence in dryland streams from time series of stream temperature","interactions":[],"lastModifiedDate":"2018-02-08T13:51:52","indexId":"70195325","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A statistical method to predict flow permanence in dryland streams from time series of stream temperature","docAbstract":"Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
","language":"English","publisher":"MDPI","doi":"10.3390/w9120946","usgsCitation":"Arismendi, I., Dunham, J.B., Heck, M., Schultz, L., and Hockman-Wert, D., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 1-13, https://doi.org/10.3390/w9120946.","productDescription":"Article 946; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087892","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469281,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9120946","text":"Publisher Index Page"},{"id":438137,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ0ZW2","text":"USGS data release","linkHelpText":"Stream temperature and drying data from Willow/Whitehorse watersheds, southeast Oregon, 2014-16, and Willow/Rock/Frazer watersheds, northern Nevada, 2015-2016"},{"id":351364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 42\n ],\n [\n -118,\n 42.33\n ],\n [\n -118.33,\n 42.33\n ],\n [\n -118.33,\n 42\n ],\n [\n -118,\n 42\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.33,\n 41.1667\n ],\n [\n -116.8333,\n 41.1667\n ],\n [\n -116.8333,\n 41.4167\n ],\n [\n -116.33,\n 41.4167\n ],\n [\n -116.33,\n 41.1667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-05","publicationStatus":"PW","scienceBaseUri":"5a7d6ffee4b00f54eb2441c0","contributors":{"authors":[{"text":"Arismendi, Ivan 0000-0002-8774-9350","orcid":"https://orcid.org/0000-0002-8774-9350","contributorId":202207,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":727859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":727858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Luke 0000-0002-6751-4626 lschultz@usgs.gov","orcid":"https://orcid.org/0000-0002-6751-4626","contributorId":193171,"corporation":false,"usgs":true,"family":"Schultz","given":"Luke","email":"lschultz@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197207,"text":"70197207 - 2017 - Translating statistical species-habitat models to interactive decision support tools","interactions":[],"lastModifiedDate":"2018-05-22T16:40:42","indexId":"70197207","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Translating statistical species-habitat models to interactive decision support tools","docAbstract":"Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188244","usgsCitation":"Wszola, L.S., Simonsen, V.L., Stuber, E.F., Gillespie, C.R., Messinger, L.N., Decker, K.L., Lusk, J.J., Jorgensen, C.F., Bishop, A.A., and Fontaine, J.J., 2017, Translating statistical species-habitat models to interactive decision support tools: PLoS ONE, v. 12, no. 12, p. 1-13, https://doi.org/10.1371/journal.pone.0188244.","productDescription":"e0188244; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087203","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188244","text":"Publisher Index Page"},{"id":354401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1ba2","contributors":{"authors":[{"text":"Wszola, Lyndsie S.","contributorId":205135,"corporation":false,"usgs":false,"family":"Wszola","given":"Lyndsie","email":"","middleInitial":"S.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonsen, Victoria L.","contributorId":205136,"corporation":false,"usgs":false,"family":"Simonsen","given":"Victoria","email":"","middleInitial":"L.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuber, Erica F.","contributorId":198581,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":736186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillespie, Caitlyn R.","contributorId":195835,"corporation":false,"usgs":false,"family":"Gillespie","given":"Caitlyn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":736187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Messinger, Lindsey N.","contributorId":205139,"corporation":false,"usgs":false,"family":"Messinger","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Decker, Karie L.","contributorId":51094,"corporation":false,"usgs":true,"family":"Decker","given":"Karie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":736189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lusk, Jeffrey J.","contributorId":198584,"corporation":false,"usgs":false,"family":"Lusk","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":736190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jorgensen, Christopher F.","contributorId":87444,"corporation":false,"usgs":true,"family":"Jorgensen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":736191,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bishop, Andrew A.","contributorId":93323,"corporation":false,"usgs":true,"family":"Bishop","given":"Andrew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":736192,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":736183,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70196268,"text":"70196268 - 2017 - Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife","interactions":[],"lastModifiedDate":"2018-03-29T10:23:16","indexId":"70196268","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife","docAbstract":"Understanding how anthropogenic impacts on the landscape affect wildlife requires a knowledge of community assemblages. Species surveys are the first step in assessing community structure, and recent molecular applications such as metabarcoding and environmental DNA analyses have been proposed as an additional and complementary wildlife survey method. Here, we test eDNA metabarcoding as a survey tool to examine the potential use of uranium mine containment ponds as water sources by wildlife. We tested samples from surface water near mines and from one mine containment pond using two markers, 12S and 16S rRNA gene amplicons, to survey for vertebrate species. We recovered large numbers of sequence reads from taxa expected to be in the area and from less common or hard to observe taxa such as the tiger salamander and gray fox. Detection of these two species is of note because they were not observed in a previous species assessment, and tiger salamander DNA was found in the mine containment pond sample. We also found that sample concentration by centrifugation was a more efficient and more feasible method than filtration in these highly turbid surface waters. Ultimately, the use of eDNA metabarcoding could allow for a better understanding of the area’s overall biodiversity and community composition as well as aid current ecotoxicological risk assessment work.
","language":"English","publisher":"MDPI","doi":"10.3390/d9040054","usgsCitation":"Klymus, K.E., Richter, C.A., Thompson, N., and Hinck, J.E., 2017, Metabarcoding of environmental DNA samples to explore the use of uranium mine containment ponds as a water source for wildlife: Diversity, v. 9, no. 4, Article 54; 18 p., https://doi.org/10.3390/d9040054.","productDescription":"Article 54; 18 p.","ipdsId":"IP-091285","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":461341,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d9040054","text":"Publisher Index Page"},{"id":438133,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC02Q5","text":"USGS data release","linkHelpText":"eDNA sampling sites in the Grand Canyon region near breccia pipe uranium mines_2015_2016"},{"id":352922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc31a","contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinck, Jo Ellen 0000-0002-4912-5766 jhinck@usgs.gov","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":2743,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"jhinck@usgs.gov","middleInitial":"Ellen","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":731999,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}