Climate change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. Here, we provide a more comprehensive CCVA approach that incorporates all three elements used for assessing species’ climate change vulnerability: exposure, sensitivity, and adaptive capacity. We illustrate our approach using case studies of two threatened salmonids with different life histories – anadromous steelhead trout (Oncorhynchus mykiss) and non-anadromous bull trout (Salvelinus confluentus) – within the Columbia River Basin, USA. We identified general patterns of high vulnerability in low-elevation and southernmost habitats for both species. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the two species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multi-species conservation. Our results highlight how CCVAs should be considered within a broader conceptual and computational framework for refining hypotheses, guiding research, and comparing plausible scenarios of species’ vulnerability for ongoing and projected climate change.
","language":"English","publisher":"Society for Conservation Biology","publisherLocation":"Malden, MA","doi":"10.1111/cobi.12764","usgsCitation":"Wade, A., Hand, B.K., Kovach, R., Luikart, G., Whited, D., and Muhlfeld, C.C., 2016, Accounting for adaptive capacity and uncertainty in assessments of species’ climate-change vulnerability: Conservation Biology, v. 31, no. 1, p. 136-149, https://doi.org/10.1111/cobi.12764.","productDescription":"14 p.","startPage":"136","endPage":"149","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072886","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":498973,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.12764","text":"Publisher Index Page"},{"id":326091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River Basin","volume":"31","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-27","publicationStatus":"PW","scienceBaseUri":"57a4672ee4b0ebae89b63ca1","contributors":{"authors":[{"text":"Wade, Alisa A.","contributorId":145917,"corporation":false,"usgs":false,"family":"Wade","given":"Alisa A.","affiliations":[{"id":16296,"text":"University of Montana, Polson Montana 59860 USA","active":true,"usgs":false}],"preferred":false,"id":644689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hand, Brian K.","contributorId":145915,"corporation":false,"usgs":false,"family":"Hand","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":16296,"text":"University of Montana, Polson Montana 59860 USA","active":true,"usgs":false}],"preferred":false,"id":644690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":644692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whited, Diane","contributorId":126718,"corporation":false,"usgs":false,"family":"Whited","given":"Diane","affiliations":[{"id":6576,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":644693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168682,"text":"pp1822 - 2016 - Late Holocene volcanism at Medicine Lake Volcano, northern California Cascades","interactions":[],"lastModifiedDate":"2016-05-24T08:43:11","indexId":"pp1822","displayToPublicDate":"2016-05-23T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1822","title":"Late Holocene volcanism at Medicine Lake Volcano, northern California Cascades","docAbstract":"Late Holocene volcanism at Medicine Lake volcano in the southern Cascades arc exhibited widespread and compositionally diverse magmatism ranging from basalt to rhyolite. Nine well-characterized eruptions have taken place at this very large rear-arc volcano since 5,200 years ago, an eruptive frequency greater than nearly all other Cascade volcanoes. The lavas are widely distributed, scattered over an area of ~300 km2 across the >2,000-km2 volcano. The eruptions are radiocarbon dated and the ages are also constrained by paleomagnetic data that provide strong evidence that the volcanic activity occurred in three distinct episodes at ~1 ka, ~3 ka, and ~5 ka. The ~1-ka final episode produced a variety of compositions including west- and north-flank mafic flows interspersed in time with fissure rhyolites erupted tangential to the volcano’s central caldera, including the youngest and most spectacular lava flow at the volcano, the ~950-yr-old compositionally zoned Glass Mountain flow. At ~3 ka, a north-flank basalt eruption was followed by an andesite eruption 27 km farther south that contains quenched basalt inclusions. The ~5-ka episode produced two caldera-focused dacitic eruptions. Quenched magmatic inclusions record evidence of intrusions that did not independently reach the surface. The inclusions are present in five andesitic, dacitic, and rhyolitic host lavas, and were erupted in each of the three episodes. Compositional and mineralogic evidence from mafic lavas and inclusions indicate that both tholeiitic (dry) and calcalkaline (wet) parental magmas were present. Petrologic evidence records the operation of complex, multi-stage processes including fractional crystallization, crustal assimilation, and magma mixing. Experimental evidence suggests that magmas were stored at 3 to 6 km depth prior to eruption, and that both wet and dry parental magmas were involved in generating the more silicic magmas. The broad distribution of eruptive events and the relative accessibility and good exposure of lavas, combined with physical and petrologic evidence for multiple and varied mafic inputs, has created an unusual opportunity to understand the workings of this large magmatic system. A combined total of more than 25 intrusive and extrusive events are indicated for late Holocene time. Plutonic inclusions, some with ages as young as Holocene, were also brought to the surface in five of the eruptions. All eruptions took place along northwest- to northeast-trending alignments of vents, reflecting the overall east-west extensional tectonic environment. The interaction of tectonism and volcanism is a dominant influence at this subduction-related volcano, located where the west edge of the extensional Basin and Range Province impinges on the Cascades arc. Ongoing subsidence focused at the central caldera has been documented along with geophysical evidence for a small magma body. This evidence, combined with the frequency of eruptive and intrusive activity in late Holocene time, an active geothermal system, and intermittent long-period seismic events indicate that the volcano is likely to erupt again.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1822","usgsCitation":"Donnelly-Nolan, J.M., Champion, D.E., and Grove, T.L., 2016, Late Holocene volcanism at Medicine Lake volcano, northern California Cascades: U.S. Geological Survey Professional Paper 1822, 59 p.,\nhttps://dx.doi.org/10.3133/pp1822.","productDescription":"Report: vi, 59 p.; Tables 1-3","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-055982","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":321256,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1822/coverthb.jpg"},{"id":321257,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1822/pp1822.pdf","text":"Report","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP1822"},{"id":321258,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1822/pp1822_table1.xls","text":"Table 1","size":"411 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP1822 Table 1"},{"id":321259,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1822/pp1822_table2.xls","text":"Table 2","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"PP1822 Table 2"},{"id":321260,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/pp/1822/pp1822_table3.pdf","text":"Table 3","size":"132 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP1822 Table 3"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.74224853515625,\n 41.35413387210046\n ],\n [\n -121.74224853515625,\n 41.71700538790365\n ],\n [\n -121.3385009765625,\n 41.71700538790365\n ],\n [\n -121.3385009765625,\n 41.35413387210046\n ],\n [\n -121.74224853515625,\n 41.35413387210046\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
http://volcanoes.usgs.gov/
A wide range of studies show global environmental change will profoundly affect the structure, function, and dynamics of terrestrial ecosystems. The research synthesized here underscores that biocrust communities are also likely to respond significantly to global change drivers, with a large potential for modification to their abundance, composition, and function. We examine how elevated atmospheric CO2 concentrations, climate change (increased temperature and altered precipitation), and nitrogen deposition affect biocrusts and the ecosystems they inhabit. We integrate experimental and observational data, as well as physiological, community ecology, and biogeochemical perspectives. Taken together, these data highlight the potential for biocrust organisms to respond dramatically to environmental change and show how changes to biocrust community composition translate into effects on ecosystem function (e.g., carbon and nutrient cycling, soil stability, energy balance). Due to the importance of biocrusts in regulating dryland ecosystem processes and the potential for large modifications to biocrust communities, an improved understanding and predictive capacity regarding biocrust responses to environmental change are of scientific and societal relevance.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biological soil crusts: An organizing principle in drylands","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-30214-0_22","usgsCitation":"Reed, S.C., Maestre, F.T., Ochoa-Hueso, R., Kuske, C., Darrouzet-Nardi, A., Darby, B., Sinsabaugh, B., Oliver, M., Sancho, L., and Belnap, J., 2016, Biocrusts in the context of global change, chap. of Biological soil crusts: An organizing principle in drylands, p. 451-476, https://doi.org/10.1007/978-3-319-30214-0_22.","productDescription":"26 p. ","startPage":"451","endPage":"476","ipdsId":"IP-060490","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":332112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"585268e0e4b0e2663625ec84","contributors":{"authors":[{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":620065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maestre, Fernando T.","contributorId":62450,"corporation":false,"usgs":true,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":620066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ochoa-Hueso, Raul","contributorId":166773,"corporation":false,"usgs":false,"family":"Ochoa-Hueso","given":"Raul","email":"","affiliations":[{"id":24505,"text":"Hawkesbury Institute for the Environment, Penrith Australia 2751","active":true,"usgs":false}],"preferred":false,"id":620067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuske, Cheryl","contributorId":22262,"corporation":false,"usgs":true,"family":"Kuske","given":"Cheryl","affiliations":[],"preferred":false,"id":620068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Darrouzet-Nardi, Anthony N. adarrouzet-nardi@usgs.gov","contributorId":5766,"corporation":false,"usgs":true,"family":"Darrouzet-Nardi","given":"Anthony N.","email":"adarrouzet-nardi@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":620069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Darby, Brian","contributorId":166774,"corporation":false,"usgs":false,"family":"Darby","given":"Brian","email":"","affiliations":[{"id":24506,"text":"University of North Dakota, Grand Forks, ND USA 58202-9019","active":true,"usgs":false}],"preferred":false,"id":620070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sinsabaugh, Bob","contributorId":166775,"corporation":false,"usgs":false,"family":"Sinsabaugh","given":"Bob","email":"","affiliations":[{"id":24507,"text":"University of New Mexico, Albuquerque, NM USA 87131","active":true,"usgs":false}],"preferred":false,"id":620071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oliver, Mel","contributorId":166776,"corporation":false,"usgs":false,"family":"Oliver","given":"Mel","email":"","affiliations":[{"id":24508,"text":"USDA-ARS, University of Missouri, Columbia campus, Columbia, MO USA 65211","active":true,"usgs":false}],"preferred":false,"id":620072,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sancho, Leo","contributorId":166777,"corporation":false,"usgs":false,"family":"Sancho","given":"Leo","affiliations":[{"id":24509,"text":"Complutense University of Madrid, Madrid Spain","active":true,"usgs":false}],"preferred":false,"id":620073,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":620076,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70176223,"text":"70176223 - 2016 - Synthesis on biological soil crust research","interactions":[],"lastModifiedDate":"2016-09-06T13:29:15","indexId":"70176223","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Synthesis on biological soil crust research","docAbstract":"In this closing chapter, we summarize the advances in biocrust research made during the last 1.5 decades. In the first part of the chapter, we discuss how in some research fields, such as the microbial diversity of fungi, bacteria, and microfauna; the interaction between biocrusts and vascular plants; and in the rehabilitation of biocrusts; particularly large achievements have been made. In other fields, previously established knowledge of overall patterns has been corroborated and refined by additional studies, e.g., in the fields of soil stabilization and disturbance effects. In the second part of the chapter, we outline the research gaps and challenges foreseen by us. We identify multiple knowledge gaps, including many understudied geographic regions, the largely missing link between genetic and morphological species identification data, and the answers to some mechanistic questions, such as the overall role of biocrusts in hydrology and nutrient cycles. With some ideas on promising new research questions and approaches we close this chapter and the overall book.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_25","usgsCitation":"Weber, B., Belnap, J., and Buedel, B., 2016, Synthesis on biological soil crust research, chap. of Ecological studies, p. 527-534, https://doi.org/10.1007/978-3-319-30214-0_25.","productDescription":"8 p.","startPage":"527","endPage":"534","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071476","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8bee4b04836416a0e3a","contributors":{"authors":[{"text":"Weber, Bettina","contributorId":21447,"corporation":false,"usgs":true,"family":"Weber","given":"Bettina","affiliations":[],"preferred":false,"id":647899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buedel, Burkhard","contributorId":172210,"corporation":false,"usgs":false,"family":"Buedel","given":"Burkhard","email":"","affiliations":[{"id":27000,"text":"Department of Biology, University of Kaiserslautern, Kaiserlautern, Germany","active":true,"usgs":false}],"preferred":false,"id":647900,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176217,"text":"70176217 - 2016 - How biological soil crusts became recognized as a functional unit: a selective history","interactions":[],"lastModifiedDate":"2016-09-06T13:46:43","indexId":"70176217","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"How biological soil crusts became recognized as a functional unit: a selective history","docAbstract":"It is surprising that despite the world-wide distribution and general importance of biological soil crusts (biocrusts), scientific recognition and functional analysis of these communities is a relatively young field of science. In this chapter, we sketch the historical lines that led to the recognition of biocrusts as a community with important ecosystem functions. The idea of biocrusts as a functional ecological community has come from two main scientific branches: botany and soil science. For centuries, botanists have long recognized that multiple organisms colonize the soil surface in the open and often dry areas occurring between vascular plants. Much later, after the initial taxonomic and phyto-sociological descriptions were made, soil scientists and agronomists observed that these surface organisms interacted with soils in ways that changed the soil structure. In the 1970’s, research on these communities as ecological units that played an important functional role in drylands began in earnest, and these studies have continued to this day. Here, we trace the history of these studies from the distant past until 1990, when biocrusts became well-known to scientists and the public.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_2","usgsCitation":"Lange, O., and Belnap, J., 2016, How biological soil crusts became recognized as a functional unit: a selective history, p. 15-33, https://doi.org/10.1007/978-3-319-30214-0_2.","productDescription":"19 p. ","startPage":"15","endPage":"33","ipdsId":"IP-070325","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8b6e4b04836416a0db5","contributors":{"authors":[{"text":"Lange, Otto L.","contributorId":17193,"corporation":false,"usgs":true,"family":"Lange","given":"Otto L.","affiliations":[],"preferred":false,"id":647868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647867,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176220,"text":"70176220 - 2016 - Carbon budgets of biological soil crusts at micro-, meso-, and global scales","interactions":[],"lastModifiedDate":"2016-09-06T13:42:21","indexId":"70176220","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Carbon budgets of biological soil crusts at micro-, meso-, and global scales","docAbstract":"The importance of biocrusts in the ecology of arid lands across all continents is widely recognized. In spite of this broad distribution, contributions of biocrusts to the global biogeochemical cycles have only recently been considered. While these studies opened a new view on the global role of biocrusts, they also clearly revealed the lack of data for many habitats and of overall standards for measurements and analysis. In order to understand carbon cycling in biocrusts and the progress which has been made during the last 15 years, we offer a multi-scale approach covering different climatic regions. We also include a discussion on available measurement techniques at each scale: A micro-scale section focuses on the individual organism level, including modeling based on the combination of field and lab data. The meso-scale section addresses the CO2 exchange of a complete ecosystem or at the community level. Finally, we consider the contribution of biocrusts at a global scale, giving a general perspective of the most relevant findings regarding the role of biological soil crusts in the global terrestrial carbon cycle.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_15","usgsCitation":"Sancho, L.G., Belnap, J., Colesie, C., Raggio, J., and Weber, B., 2016, Carbon budgets of biological soil crusts at micro-, meso-, and global scales, chap. of Ecological studies, p. 287-304, https://doi.org/10.1007/978-3-319-30214-0_15.","productDescription":"18 p. ","startPage":"287","endPage":"304","ipdsId":"IP-071038","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8b0e4b04836416a0d33","contributors":{"authors":[{"text":"Sancho, Leopoldo G","contributorId":174261,"corporation":false,"usgs":false,"family":"Sancho","given":"Leopoldo","email":"","middleInitial":"G","affiliations":[{"id":27404,"text":"Departamento de Biologıa Vegetal II, Facultad de Farmacia, Universidad Complutense, Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":647883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colesie, Claudia","contributorId":174262,"corporation":false,"usgs":false,"family":"Colesie","given":"Claudia","email":"","affiliations":[{"id":27405,"text":"Plant Ecology and Systematics, Biology, University of Kaiserslautern, Kaiserlautern, Germany","active":true,"usgs":false}],"preferred":false,"id":647884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raggio, Jose","contributorId":174263,"corporation":false,"usgs":false,"family":"Raggio","given":"Jose","email":"","affiliations":[{"id":27404,"text":"Departamento de Biologıa Vegetal II, Facultad de Farmacia, Universidad Complutense, Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":647885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Bettina","contributorId":21447,"corporation":false,"usgs":true,"family":"Weber","given":"Bettina","affiliations":[],"preferred":false,"id":647886,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176219,"text":"70176219 - 2016 - Patterns and controls on nitrogen cycling of biological soil crusts","interactions":[],"lastModifiedDate":"2016-09-06T13:39:33","indexId":"70176219","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Patterns and controls on nitrogen cycling of biological soil crusts","docAbstract":"Biocrusts play a significant role in the nitrogen [N ] cycle within arid and semi-arid ecosystems, as they contribute major N inputs via biological fixation and dust capture, harbor internal N transformation processes, and direct N losses via N dissolved, gaseous and erosional loss processes (Fig. 1). Because soil N availability in arid and semi-arid ecosystems is generally low and may limit net primary production (NPP), especially during periods when adequate water is available, understanding the mechanisms and controls of N input and loss pathways in biocrusts is critically important to our broader understanding of N cycling in dryland environments. In particular, N cycling by biocrusts likely regulates short-term soil N availability to support vascular plant growth, as well as long-term N accumulation and maintenance of soil fertility. \nIn this chapter, we review the influence of biocrust nutrient input, internal cycling, and loss pathways across a range of biomes. We examine linkages between N fixation capabilities of biocrust organisms and spatio-temporal patterns of soil N availability that may influence the longer-term productivity of dryland ecosystems. Lastly, biocrust influence on N loss pathways such as N gas loss, leakage of N compounds from biocrusts, and transfer in wind and water erosion are important to understand the maintenance of dryland soil fertility over longer time scales. Although great strides have been made in understanding the influence of biocrusts on ecosystem N cycling, there are important knowledge gaps in our understanding of the influence of biocrusts on ecosystem N cycling that should be the focus of future studies. Because work on the interaction of N cycling and biocrusts was reviewed in Belnap and Lange (2003), this chapter will focus primarily on research findings that have emerged over the last 15 years (2000-2015).","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_14","usgsCitation":"Barger, N., Zaady, E., Weber, B., Garcia-Pichel, F., and Belnap, J., 2016, Patterns and controls on nitrogen cycling of biological soil crusts, p. 257-285, https://doi.org/10.1007/978-3-319-30214-0_14.","productDescription":"29 p. ","startPage":"257","endPage":"285","ipdsId":"IP-070429","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328201,"type":{"id":15,"text":"Index Page"},"url":"https://www.springer.com/us/book/9783319302126"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8bbe4b04836416a0e00","contributors":{"authors":[{"text":"Barger, Nichole N.","contributorId":102392,"corporation":false,"usgs":true,"family":"Barger","given":"Nichole N.","affiliations":[],"preferred":false,"id":647878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaady, Eli","contributorId":39638,"corporation":false,"usgs":true,"family":"Zaady","given":"Eli","email":"","affiliations":[],"preferred":false,"id":647879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Bettina","contributorId":21447,"corporation":false,"usgs":true,"family":"Weber","given":"Bettina","affiliations":[],"preferred":false,"id":647880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia-Pichel, Ferran","contributorId":166779,"corporation":false,"usgs":false,"family":"Garcia-Pichel","given":"Ferran","email":"","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":647881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647877,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176221,"text":"70176221 - 2016 - Biological soil crusts: An organizing principle in dryland ecosystems (aka: the role of biocrusts in arid land hydrology)","interactions":[],"lastModifiedDate":"2016-09-06T13:27:23","indexId":"70176221","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Biological soil crusts: An organizing principle in dryland ecosystems (aka: the role of biocrusts in arid land hydrology)","docAbstract":"Biocrusts exert a strong influence on hydrological processes in drylands by modifying numerous soil properties that affect water retention and movement in soils. Yet, their role in these processes is not clearly understood due to the large number of factors that act simultaneously and can mask the biocrust effect. The influence of biocrusts on soil hydrology depends on biocrust intrinsic characteristics such as cover, composition, and external morphology, which differ greatly among climate regimes, but also on external factors as soil type, topography and vegetation distribution patterns, as well as interactions among these factors. This chapter reviews the most recent literature published on the role of biocrusts in infiltration and runoff, soil moisture, evaporation and non-rainfall water inputs (fog, dew, water absorption), in an attempt to elucidate the key factors that explain how biocrusts affect land hydrology. In addition to the crust type and site characteristics, recent studies point to the crucial importance of the type of rainfall and the spatial scale at which biocrust effects are analyzed to understand their role in hydrological processes. Future studies need to consider the temporal and spatial scale investigated to obtain more accurate generalizations on the role of biocrusts in land hydrology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_17","usgsCitation":"Chamizo, S., Belnap, J., Elridge, D.J., and Issa, O., 2016, Biological soil crusts: An organizing principle in dryland ecosystems (aka: the role of biocrusts in arid land hydrology), chap. of Ecological studies, p. 321-346, https://doi.org/10.1007/978-3-319-30214-0_17.","productDescription":"26 p.","startPage":"321","endPage":"346","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070333","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8b0e4b04836416a0d2f","contributors":{"authors":[{"text":"Chamizo, Sonia 0000-0002-2980-1683","orcid":"https://orcid.org/0000-0002-2980-1683","contributorId":174264,"corporation":false,"usgs":false,"family":"Chamizo","given":"Sonia","email":"","affiliations":[{"id":27406,"text":"Department of Agronomy, University of Almeria, 04120 Almeria, Spain","active":true,"usgs":false}],"preferred":false,"id":647888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elridge, David J","contributorId":174265,"corporation":false,"usgs":false,"family":"Elridge","given":"David","email":"","middleInitial":"J","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":647889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Issa, Oumarou M","contributorId":174266,"corporation":false,"usgs":false,"family":"Issa","given":"Oumarou M","affiliations":[{"id":27408,"text":"URCA, GEGENAA EA 3795, 51100 Reims – France / UMR 242 IEES-Paris, IRD representation au Niger BP11416 Niamey, Niger","active":true,"usgs":false}],"preferred":false,"id":647890,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171126,"text":"ofr20161080 - 2016 - Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","interactions":[],"lastModifiedDate":"2016-06-23T16:23:54","indexId":"ofr20161080","displayToPublicDate":"2016-05-20T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1080","title":"Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","docAbstract":"Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.
Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.
We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161080","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, California Department of Fish and Wildlife, and Idaho State University","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee B.E., Ricca, M.A., Gustafson, K.B., Sanchez-Chopitea, E., Mauch, K., Niell, L., Gardner, S., Espinosa, S., and Delehanty, D.J., 2016, Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management: U.S. Geological Survey Open-File Report 2016-1080, 160 p., https://dx.doi.org/10.3133/ofr20161080.","productDescription":"Report: viii, 160 p.; Dataset","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072897","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322138,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7CC0XRV","text":"USGS data release - Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Nevada and Northeastern California - an Updated Decision-Support Tool for Management"},{"id":321471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1080/coverthb.jpg"},{"id":321472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1080/ofr20161080.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1080 Report PDF"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.87158203125,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 37.50972584293751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
The Colorado Plateau is a physiographic region that encompasses 330,000 square kilometers in parts of four states in the southwestern United States (Colorado, Utah, New Mexico, and Arizona). Known for its high deserts, the Colorado Plateau also includes isolated mountains, high plateaus, and rugged canyons. Not only is the region topographically diverse, but geologically, biologically, and culturally diverse as well. The landscape is managed by Federal entities including the Bureau of Land Management, the National Park Service, and the U.S. Forest Service; Tribal nations including the Navajo Nation, Kaibab Paiute, Mountain Ute, Southern Ute, Hopi, Zuni, Hualapai, Havasupai, and White Mountain Apache Tribes; State land and wildlife management agencies; and privately owned holdings, creating complex interactions and management challenges. Population growth, increased tourism to Federal and State lands, and energy development have increased water demands and altered land-use patterns, and these changes have emerged as management challenges facing the people working and living in the region. Climate change, particularly the ongoing drought, has exacerbated the effects of population growth, land-use change, and other stressors such as invasive species. As managers seek solutions to the challenges facing the region’s natural and cultural resources, the Biennial Conference of Science and Management of the Colorado Plateau has become an important venue for exchanging information about emerging management concerns and recent scientific research. Each biennial conference has sought to promote discussion, information sharing, and productive communication among the managers, scientists, students, administrators, tribal representatives, and others who attend the conference with the goal of enhancing the use of the best available science to manage the region’s incomparable natural and cultural resources.
\nThe publication and dissemination of a conference proceedings series expands the reach of the conference beyond those people in attendance and creates a record on the research presented. The idea of producing a conference proceedings, and its subsequent publication, first occurred in 1993 following the first biennial conference in 1991. A published volume of contributed papers has followed each subsequent biennial conference, including this volume. The venue for publishing proceedings has changed over the years and has included the National Park Service, the Government Printing Office, the U.S. Geological Survey, and University of Arizona Press. Recently, van Riper and others (2015) published a compilation of the abstracts from the 11 previous conference proceedings. Collectively, the proceedings highlight approximately 25 years of natural- and cultural-resources research, promoting the integration of research with resource management across the Colorado Plateau. This volume is freely downloadable by the public, thereby further expanding the influence of this conference beyond the Colorado Plateau.
\nThe 12th Biennial Conference held in Flagstaff, Arizona, from September 16 to 19, 2013, covered a range of topics in the physical, biological, and socio-cultural sciences. The conference was organized and hosted by Northern Arizona University’s (NAU) Merriam-Powell Center for Environmental Research, the Colorado Plateau Cooperative Ecosystem Studies Unit, and the U.S. Geological Survey Southwest Biological Science Center. Financial and in-kind support was provided by a wide range of organizations including the U.S. Forest Service, National Park Service, Bureau of Land Management, Grand Canyon Trust, Colorado Plateau Research Station, and various NAU entities. NAU sponsors include the Landscape Conservation Initiative, School of Forestry, School of Earth Science and Environmental Sustainability, Office of the Provost, and Office of the Vice President of Research. Contributors to these proceedings include researchers and managers from Federal, State, and Tribal governments, universities, private entities, and non-profit organizations. In this regard, this conference has wide-ranging support and participation among private and public entities involved in the science and management of natural resources on the Colorado Plateau.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155180","usgsCitation":"Ralston, B.E., ed., 2016, Proceedings of the 12th Biennial Conference of Research on the Colorado River Plateau: U.S. Geological Survey Scientific Investigations Report 2015–5180, 128 p., https://dx.doi.org/10.3133/sir20155180.","productDescription":"128 p.","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070115","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":399526,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104245.htm"},{"id":321450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5180/coverthb.jpg"},{"id":321451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5180/sir20155180.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5180 Report PDF"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.40087890624999,\n 34.75\n ],\n [\n -113.40087890624999,\n 39.35129035526705\n ],\n [\n -106.76513671875,\n 39.35129035526705\n ],\n [\n -106.76513671875,\n 34.75\n ],\n [\n -113.40087890624999,\n 34.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
Graptemys ernsti, the Escambia Map Turtle, inhabits the Escambia/Conecuh River, the adjacent Yellow River, and the Pea River further to the east, all of which have been distinct drainage systems since the Pleistocene. We used continuous and meristic morphological and genetic data to compare populations of G. ernsti and found evidence of differences among the three drainages. Frequency of occurrence of a nasal trident differed among the three drainages. Yellow River specimens possessed unique mitochondrial haplotypes while the Conecuh and the Pea shared haplotypes. Five microsatellite loci identified the drainages as being distinct, with the strongest differentiation between the Yellow River and the other two drainages. While these differences do not appear great enough to warrant taxonomic recognition, they do suggest that each population has a distinct evolutionary and demographic history and that they should therefore be managed separately.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Ennen, J.R., Godwin, J., Lovich, J.E., Kreiser, B.R., Folt, B., and Hazard, S., 2016, Interdrainage morphological and genetic differentiation in the Escambia Map Turtle, Graptemys ernsti: Herpetological Conservation and Biology, v. 11, no. 1, p. 122-131.","productDescription":"10 p.","startPage":"122","endPage":"131","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063620","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321419,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol11_issue1.html"}],"volume":"11","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740271be4b07e28b65dcfdc","contributors":{"authors":[{"text":"Ennen, Joshua R.","contributorId":83858,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":629864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godwin, James","contributorId":81015,"corporation":false,"usgs":true,"family":"Godwin","given":"James","affiliations":[],"preferred":false,"id":629865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kreiser, Brian R.","contributorId":47691,"corporation":false,"usgs":true,"family":"Kreiser","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":629866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Folt, Brian","contributorId":127807,"corporation":false,"usgs":false,"family":"Folt","given":"Brian","affiliations":[{"id":7160,"text":"Department of Biological Sciences and Auburn University Museum of Natural History, 331 Funchess Hall, Auburn University, Auburn, Alabama 36849; E-mail: brian.folt@gmail.com.","active":true,"usgs":false}],"preferred":false,"id":629867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hazard, Sarah","contributorId":169519,"corporation":false,"usgs":false,"family":"Hazard","given":"Sarah","email":"","affiliations":[{"id":25549,"text":"Tennessee Aquarium Conservation Institute, 201 Chestnut Street, Chattanooga, TN 37402","active":true,"usgs":false}],"preferred":false,"id":629868,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171104,"text":"70171104 - 2016 - Waterfowl endozoochory: An overlooked long-distance dispersal mode for Cuscuta (dodder)","interactions":[],"lastModifiedDate":"2016-05-20T09:25:09","indexId":"70171104","displayToPublicDate":"2016-05-20T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl endozoochory: An overlooked long-distance dispersal mode for Cuscuta (dodder)","docAbstract":"REMISE OF THE STUDY: Dispersal of parasitic Cuscuta species (dodders) worldwide has been assumed to be largely anthropomorphic because their seeds do not match any previously known dispersal syndrome and no natural dispersal vectors have been reliably documented. However, the genus has a subcosmopolitan distribution and recent phylogeographic results have indicated that at least18 historical cases of long-distance dispersal (LDD) have occurred during its evolution. The objective of this study is to report the first LDD biological vector for Cuscuta seeds.
\nMETHODS: Twelve northern pintails (Anas acuta) were collected from Suisun Marsh, California and the contents of their lowest part of the large intestine (rectum) were extracted and analyzed. Seed identification was done both morphologically and using a molecular approach. Extracted seeds were tested for germination and compared to seeds not subjected to gut passage to determine the extent of structural changes caused to the seed coat by passing through the digestive tract.
\nKEY RESULTS: Four hundred and twenty dodder seeds were found in the rectum of four northern pintails. From these, 411 seeds were identified as Cuscuta campestris and nine as most likely C. pacifica. The germination rate of C. campestris seeds after gut passage was 55%. Structural changes caused by the gut passage in both species were similar to those caused by an acid scarification.
\nCONCLUSIONS: Endozoochory by waterbirds may explain the historical LDD cases in the evolution of Cuscuta. This also suggests that current border quarantine measures may be insufficient to stopping spreading of dodder pests along migratory flyways.
\nThe Semidi segment of the Alaska convergent margin appears capable of generating a giant tsunami like the one produced along the nearby Unimak segment in 1946. Reprocessed legacy seismic reflection data and a compilation of multibeam bathymetric surveys reveal structures that could generate such a tsunami. A 200 km long ridge or escarpment with crests >1 km high is the surface expression of an active out-of-sequence fault zone, recently referred to as a splay fault. Such faults are potentially tsunamigenic. This type of fault zone separates the relatively rigid rock of the margin framework from the anelastic accreted sediment prism. Seafloor relief of the ridge exceeds that of similar age accretionary prism ridges indicating preferential slip along the splay fault zone. The greater slip may derive from Quaternary subduction of the Patton Murray hot spot ridge that extends 200 km toward the east across the north Pacific. Estimates of tsunami repeat times from paleotsunami studies indicate that the Semidi segment could be near the end of its current inter-seismic cycle. GPS records from Chirikof Island at the shelf edge indicate 90% locking of plate interface faults. An earthquake in the shallow Semidi subduction zone could generate a tsunami that will inundate the US west coast more than the 1946 and 1964 earthquakes because the Semidi continental slope azimuth directs a tsunami southeastward.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015GC006147","usgsCitation":"von Huene, R.E., Miller, J.J., and Dartnell, P., 2016, A possible transoceanic tsunami directed toward the U.S. west coast from the Semidi segment, Alaska convergent margin: Geochemistry, Geophysics, Geosystems, v. 17, no. 3, p. 645-659, https://doi.org/10.1002/2015GC006147.","productDescription":"15 p.","startPage":"645","endPage":"659","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066716","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470974,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gc006147","text":"Publisher Index Page"},{"id":321440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-04","publicationStatus":"PW","scienceBaseUri":"5740271ae4b07e28b65dcfcc","contributors":{"authors":[{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":629884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, John J. 0000-0002-9098-0967 jmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-0967","contributorId":3785,"corporation":false,"usgs":true,"family":"Miller","given":"John","email":"jmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629883,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171108,"text":"70171108 - 2016 - Genomics reveals historic and contemporary transmission dynamics of a bacterial disease among wildlife and livestock","interactions":[],"lastModifiedDate":"2018-08-09T12:06:06","indexId":"70171108","displayToPublicDate":"2016-05-20T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Genomics reveals historic and contemporary transmission dynamics of a bacterial disease among wildlife and livestock","docAbstract":"Whole-genome sequencing has provided fundamental insights into infectious disease epidemiology, but has rarely been used for examining transmission dynamics of a bacterial pathogen in wildlife. In the Greater Yellowstone Ecosystem (GYE), outbreaks of brucellosis have increased in cattle along with rising seroprevalence in elk. Here we use a genomic approach to examine Brucella abortus evolution, cross-species transmission and spatial spread in the GYE. We find that brucellosis was introduced into wildlife in this region at least five times. The diffusion rate varies among Brucella lineages (B3 to 8 km per year) and over time. We also estimate 12 host transitions from bison to elk, and 5 from elk to bison. Our results support the notion that free-ranging elk are currently a self-sustaining brucellosis reservoir and the source of livestock infections, and that control measures in bison are unlikely to affect the dynamics of unrelated strains circulating in nearby elk populations.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/ncomms11448","usgsCitation":"Kamath, P.L., Foster, J., Drees, K., Luikart, G., Quance, C., Anderson, N.J., Clarke, P.R., Cole, E., Drew, M.L., Edwards, W.H., Rhyan, J.C., Treanor, J.J., Wallen, R.L., White, P.J., Robbe-Austerman, S., and Cross, P.C., 2016, Genomics reveals historic and contemporary transmission dynamics of a bacterial disease among wildlife and livestock: Nature Communications, v. 7, Article 11448, 10 p., https://doi.org/10.1038/ncomms11448.","productDescription":"Article 11448, 10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067034","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470976,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms11448","text":"Publisher Index Page"},{"id":321439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-11","publicationStatus":"PW","scienceBaseUri":"5740271be4b07e28b65dcfd8","contributors":{"authors":[{"text":"Kamath, Pauline L. pkamath@usgs.gov","contributorId":4517,"corporation":false,"usgs":true,"family":"Kamath","given":"Pauline","email":"pkamath@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":629890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Jeffrey T.","contributorId":8744,"corporation":false,"usgs":true,"family":"Foster","given":"Jeffrey T.","affiliations":[],"preferred":false,"id":629891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drees, Kevin P.","contributorId":81759,"corporation":false,"usgs":true,"family":"Drees","given":"Kevin P.","affiliations":[],"preferred":false,"id":629892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":629893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quance, Christine","contributorId":169525,"corporation":false,"usgs":false,"family":"Quance","given":"Christine","email":"","affiliations":[{"id":25553,"text":"USDA-APHIS, National Veterinary Services Laboratory","active":true,"usgs":false}],"preferred":false,"id":629894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Neil J.","contributorId":85870,"corporation":false,"usgs":true,"family":"Anderson","given":"Neil","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clarke, P. Ryan","contributorId":169526,"corporation":false,"usgs":false,"family":"Clarke","given":"P.","email":"","middleInitial":"Ryan","affiliations":[{"id":25554,"text":"USDA-APHIS, Veterinary Services","active":true,"usgs":false}],"preferred":false,"id":629896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cole, Eric K. 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":145755,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":629898,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Drew, Mark L.","contributorId":169527,"corporation":false,"usgs":false,"family":"Drew","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":25555,"text":"Idaho Dept. of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":629899,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Edwards, William H.","contributorId":9144,"corporation":false,"usgs":true,"family":"Edwards","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":629900,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rhyan, Jack C.","contributorId":11185,"corporation":false,"usgs":true,"family":"Rhyan","given":"Jack","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":629897,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Treanor, John J.","contributorId":169528,"corporation":false,"usgs":false,"family":"Treanor","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":629901,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wallen, Rick L.","contributorId":169529,"corporation":false,"usgs":false,"family":"Wallen","given":"Rick","email":"","middleInitial":"L.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":629902,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"White, Patrick J.","contributorId":169530,"corporation":false,"usgs":false,"family":"White","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":629903,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Robbe-Austerman, Suelee","contributorId":169531,"corporation":false,"usgs":false,"family":"Robbe-Austerman","given":"Suelee","email":"","affiliations":[{"id":25553,"text":"USDA-APHIS, National Veterinary Services Laboratory","active":true,"usgs":false}],"preferred":false,"id":629904,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":629905,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70171110,"text":"70171110 - 2016 - Toward improved simulation of river operations through integration with a hydrologic model","interactions":[],"lastModifiedDate":"2016-05-20T09:13:54","indexId":"70171110","displayToPublicDate":"2016-05-20T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Toward improved simulation of river operations through integration with a hydrologic model","docAbstract":"Advanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.04.018","usgsCitation":"Morway, E.D., Niswonger, R.G., and Triana, E., 2016, Toward improved simulation of river operations through integration with a hydrologic model: Environmental Modelling and Software, no. 82, p. 255-274, https://doi.org/10.1016/j.envsoft.2016.04.018.","productDescription":"20 p.","startPage":"255","endPage":"274","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070519","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":470977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2016.04.018","text":"Publisher Index Page"},{"id":321438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"82","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740271de4b07e28b65dcfea","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":629911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Triana, Enrique","contributorId":169532,"corporation":false,"usgs":false,"family":"Triana","given":"Enrique","email":"","affiliations":[{"id":25556,"text":"MWH Global, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":629912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171415,"text":"70171415 - 2016 - Forest disturbance interactions and successional pathways in the Southern Rocky Mountains","interactions":[],"lastModifiedDate":"2016-06-01T15:59:35","indexId":"70171415","displayToPublicDate":"2016-05-20T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Forest disturbance interactions and successional pathways in the Southern Rocky Mountains","docAbstract":"The pine forests in the southern portion of the Rocky Mountains are a heterogeneous mosaic of disturbance and recovery. The most extensive and intensive stress and mortality are received from human activity, fire, and mountain pine beetles (MPB;Dendroctonus ponderosae). Understanding disturbance interactions and disturbance-succession pathways are crucial for adapting management strategies to mitigate their impacts and anticipate future ecosystem change. Driven by this goal, we assessed the forest disturbance and recovery history in the Southern Rocky Mountains Ecoregion using a 13-year time series of Landsat image stacks. An automated classification workflow that integrates temporal segmentation techniques and a random forest classifier was used to examine disturbance patterns. To enhance efficiency in selecting representative samples at the ecoregion scale, a new sampling strategy that takes advantage of the scene-overlap among adjacent Landsat images was designed. The segment-based assessment revealed that the overall accuracy for all 14 scenes varied from 73.6% to 92.5%, with a mean of 83.1%. A design-based inference indicated the average producer’s and user’s accuracies for MPB mortality were 85.4% and 82.5% respectively. We found that burn severity was largely unrelated to the severity of pre-fire beetle outbreaks in this region, where the severity of post-fire beetle outbreaks generally decreased in relation to burn severity. Approximately half the clear-cut and burned areas were in various stages of recovery, but the regeneration rate was much slower for MPB-disturbed sites. Pre-fire beetle outbreaks and subsequent fire produced positive compound effects on seedling reestablishment in this ecoregion. Taken together, these results emphasize that although multiple disturbances do play a role in the resilience mechanism of the serotinous lodgepole pine, the overall recovery could be slow due to the vast area of beetle mortality.
","language":"English","publisher":"Elsevier Science Pub. Co.","doi":"10.1016/j.foreco.2016.05.010","usgsCitation":"Liang, L., Hawbaker, T., Zhu, Z., Li, X., and Gong, P., 2016, Forest disturbance interactions and successional pathways in the Southern Rocky Mountains: Forest Ecology and Management, no. 375, p. 35-45, https://doi.org/10.1016/j.foreco.2016.05.010.","productDescription":"11 p.","startPage":"35","endPage":"45","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066422","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470979,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.05.010","text":"Publisher Index Page"},{"id":322049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Wyoming","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111,\n 35\n ],\n [\n -111,\n 44\n ],\n [\n -103,\n 44\n ],\n [\n -103,\n 35\n ],\n [\n -111,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"375","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500763e4b0ee97d51bb5f9","chorus":{"doi":"10.1016/j.foreco.2016.05.010","url":"http://dx.doi.org/10.1016/j.foreco.2016.05.010","publisher":"Elsevier BV","authors":"Liang Lu, Hawbaker Todd J., Zhu Zhiliang, Li Xuecao, Gong Peng","journalName":"Forest Ecology and Management","publicationDate":"9/2016"},"contributors":{"authors":[{"text":"Liang, Lu","contributorId":169730,"corporation":false,"usgs":false,"family":"Liang","given":"Lu","email":"","affiliations":[{"id":25576,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA 94720","active":true,"usgs":false}],"preferred":false,"id":630922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":630921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":630923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Xuecao","contributorId":169731,"corporation":false,"usgs":false,"family":"Li","given":"Xuecao","email":"","affiliations":[{"id":25577,"text":"Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":630924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gong, Peng","contributorId":169732,"corporation":false,"usgs":false,"family":"Gong","given":"Peng","affiliations":[{"id":25576,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA 94720","active":true,"usgs":false}],"preferred":false,"id":630925,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170968,"text":"ofr20161075 - 2016 - Aquatic Trophic Productivity model: A decision support model for river restoration planning in the Methow River, Washington","interactions":[],"lastModifiedDate":"2017-11-22T15:48:44","indexId":"ofr20161075","displayToPublicDate":"2016-05-19T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1075","title":"Aquatic Trophic Productivity model: A decision support model for river restoration planning in the Methow River, Washington","docAbstract":"The U.S. Geological Survey (USGS) has developed a dynamic food-web simulation model to provide decision support for Bureau of Reclamation (Reclamation) river restoration projects in the Methow River, Washington. This modeling effort was done to contribute to Reasonable and Prudent Alternative actions 56 and 57of the 2014 Federal Columbia River Power System Biological Opinion (FCRPS BO), which calls for exploration of modeling as a means to help evaluate Endangered Species Act (ESA)-listed fish response to river restoration efforts. In the Methow River, these species of concern include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha) and UCR summer steelhead (Oncorhynchus mykiss). Additionally, the Independent Scientific Advisory Board (ISAB) for the Columbia River has identified the need for modeling (Independent Scientific Advisory Board, 2011a)—including models that incorporate food-web dynamics (Independent Scientific Advisory Board, 2011b)—to better understand how restoration and management strategies might enhance salmon and steelhead populations.
\nDynamic food-web models, even relatively simple ones, can be valuable tools for exploring responses to river restoration. Although these models have rarely been applied to rivers and streams (but see Mcintire and Colby, 1978; Power and others, 1995), they are commonly used for management decisions in terrestrial and ocean ecosystems (Christensen and Pauly, 1993; Evans and others, 2013). One of the main strengths of these models is that they are rooted in the fundamental laws of thermodynamics (that is, mass balance). Moreover, these models can be easily adapted to different contexts by adding or subtracting different species from the web and by mechanistically linking the dynamics of web members to local environmental conditions, such as water temperature, stream discharge, and channel hydraulics (Power and others, 1995; Doyle, 2006). Alternative management actions can then be evaluated by changing these environmental conditions to simulate potential outcomes following restoration.
\nIn this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., and Bellmore, J.R., 2016, Aquatic trophic productivity model: A decision support model for river restoration planning in the Methow River, Washington: U.S. Geological Survey Open-File Report 2016‒1075, 85 p., https://dx.doi.org/10.3133/ofr20161075.","productDescription":"vi, 85 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1075/coverthb.jpg"},{"id":321409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1075/ofr20161075.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1075 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
National Parks and other protected areas can be influenced by contamination from outside their boundaries. This is particularly true of smaller parks and those in riparian ecosystems, a habitat that in arid environments provides critical habitat for breeding, migratory, and wintering birds. Animals living in contaminated areas are susceptible to adverse health effects as a result of long-term exposure and bioaccumulation of heavy metals. We investigated the distribution and cascading extent of heavy metal accumulation in Song Sparrows (Melospiza melodia) at Tumacacori National Historic Park (TUMA) along the upper Santa Cruz River watershed in southern Arizona. This study had three goals: (1) quantify the concentrations and distributional patterns of heavy metals in blood and feathers of Song Sparrows at Tumacacori National Historic Park, (2) quantify hematocrit values, body conditions (that is, residual body mass), and immune conditions of Song Sparrows in the park (3) compare our findings with prior studies at the park to assess the extent of heavy metal accumulation in birds at downstream sites after the 2009 wastewater treatment plant upgrade, and (4) quantify concentrations and distributional patterns of heavy metals in blood and feathers of Song Sparrows among six study sites throughout the upper Santa Cruz River watershed. This study design would allow us to more accurately assess song sparrow condition and blood parameters among sites with differing potential sources of contamination exposure, and how each location could have contributed to heavy metal levels of birds in the park.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Engagement, education, and expectations - the future of parks and protected areas: Proceedings of the 2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites","language":"English","publisher":"George Wright Society","usgsCitation":"van Riper, C., and Lester, M.B., 2016, Changing levels of heavy metal accumulation in birds at Tumacacori National Historic Park along the Upper Santa Cruz River Watershed in southern Arizona, in Engagement, education, and expectations - the future of parks and protected areas: Proceedings of the 2015 George Wright Society Conference on Parks, Protected Areas, and Cultural Sites, p. 123-128.","productDescription":"6 p.","startPage":"123","endPage":"128","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065932","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321385,"type":{"id":15,"text":"Index Page"},"url":"https://www.georgewright.org/proceedings2015"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573ed59be4b04a3a6a2462cc","contributors":{"authors":[{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":629770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lester, Michael B.","contributorId":92170,"corporation":false,"usgs":true,"family":"Lester","given":"Michael","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":629771,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170967,"text":"ofr20161076 - 2016 - Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon","interactions":[],"lastModifiedDate":"2016-05-19T15:58:47","indexId":"ofr20161076","displayToPublicDate":"2016-05-19T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1076","title":"Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon","docAbstract":"During summer 2014, lake level, streamflow, and water temperature in and around Crystal Springs Lake in Portland, Oregon, were measured by the U.S. Geological Survey and the City of Portland Bureau of Environmental Services to better understand the effect of the lake on Crystal Springs Creek and Johnson Creek downstream. Johnson Creek is listed as an impaired water body for temperature by the Oregon Department of Environmental Quality (ODEQ), as required by section 303(d) of the Clean Water Act. A temperature total maximum daily load applies to all streams in the Johnson Creek watershed, including Crystal Springs Creek. Summer water temperatures downstream of Crystal Springs Lake and the Golf Pond regularly exceed the ODEQ numeric criterion of 64.4 °F (18.0 °C) for salmonid rearing and migration. To better understand temperature contributions of this system, the U.S. Geological Survey developed two-dimensional hydrodynamic water temperature models of Crystal Springs Lake and the Golf Pond. Model grids were developed to closely resemble the bathymetry of the lake and pond using data from a 2014 survey. The calibrated models simulated surface water elevations to within 0.06 foot (0.02 meter) and outflow water temperature to within 1.08 °F (0.60 °C). Streamflow, water temperature, and lake elevation data collected during summer 2014 supplied the boundary and reference conditions for the model. Measured discrepancies between outflow and inflow from the lake, assumed to be mostly from unknown and diffuse springs under the lake, accounted for about 46 percent of the total inflow to the lake.
\nModel simulations (scenarios) were run with lower water surface elevations in Crystal Springs Lake and increased shading to the lake to assess the relative effect the lake and pond characteristics have on water temperature. The Golf Pond was unaltered in all scenarios. The models estimated that lower lake elevations would result in cooler water downstream of the Golf Pond and shorter residence times in the lake. Increased shading to the lake would also provide substantial cooling. Most management scenarios resulted in a decrease in 7-day average of daily maximum values by about 2.0– 4.7 °F (1.1 –2.6 °C) for outflow from Crystal Springs Lake during the period of interest. Outflows from the Golf Pond showed a net temperature reduction of 0.5–2.7 °F (0.3–1.5 °C) compared to measured values in 2014 because of solar heating and downstream warming in the Golf Pond resulting from mixing with inflow from Reed Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161076","collaboration":"Prepared in cooperation with City of Portland Bureau of Environmental Services","usgsCitation":"Buccola, N.L., and Stonewall, A.J., 2016, Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon: U.S. Geological Survey Open-File Report 2016‒1076, 26 p.,\nhttps://dx.doi.org/10.3133/ofr20161076.","productDescription":"Report: vi, 26 p.; Tables 1-9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060388","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321392,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076_tables1-9.xlsx","text":"Tables 1-9","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1076 Tables 1-9"},{"id":321390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1076/coverthb.jpg"},{"id":321391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1076"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63982295989989,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.47522429601816\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Insecticide use in urban areas results in the detection of these compounds in streams following stormwater runoff at concentrations likely to cause toxicity for stream invertebrates. In this 2013 study, stormwater runoff and streambed sediments were analyzed for 91 pesticides dissolved in water and 118 pesticides on sediment. Detections included 33 pesticides, including insecticides, fungicides, herbicides, degradates, and a synergist. Patterns in pesticide occurrence reveal transport of dissolved and sediment-bound pesticides, including pyrethroids, from upland areas through stormwater outfalls to receiving streams. Nearly all streams contained at least one insecticide at levels exceeding an aquatic-life benchmark, most often for bifenthrin and (or) fipronil. Multiple U.S. EPA benchmark or criterion exceedances occurred in 40 % of urban streams sampled. Bed sediment concentrations of bifenthrin were highly correlated (p < 0.001) with benthic invertebrate assemblages. Non-insects and tolerant invertebrates such as amphipods, flatworms, nematodes, and oligochaetes dominated streams with relatively high concentrations of bifenthrin in bed sediments, whereas insects, sensitive invertebrates, and mayflies were much more abundant at sites with no or low bifenthrin concentrations. The abundance of sensitive invertebrates, % EPT, and select mayfly taxa were strongly negatively correlated with organic-carbon normalized bifenthrin concentrations in streambed sediments. Our findings from western Clackamas County, Oregon (USA), expand upon previous research demonstrating the transport of pesticides from urban landscapes and linking impaired benthic invertebrate assemblages in urban streams with exposure to pyrethroid insecticides.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-016-5215-5","usgsCitation":"Carpenter, K.D., Kuivila, K., Hladik, M., Haluska, T., and Cole, M.B., 2016, Storm-event-transport of urban-use pesticides to streams likely impairs invertebrate assemblages: Environmental Monitoring and Assessment, v. 188, art345: 18 p., https://doi.org/10.1007/s10661-016-5215-5.","productDescription":"art345: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063257","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-016-5215-5","text":"Publisher Index 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global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13208","usgsCitation":"Foster, J.R., Finley, A.O., D’Amato, A.W., Bradford, J.B., and Banerjee, S., 2016, Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?: Global Change Biology, v. 22, no. 6, p. 2138-2151, https://doi.org/10.1111/gcb.13208.","productDescription":"14 p.","startPage":"2138","endPage":"2151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069743","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Superior National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.48291015625,\n 47.76517619125415\n ],\n [\n -92.48291015625,\n 48.38361810886624\n ],\n [\n -90.02471923828125,\n 48.38361810886624\n ],\n [\n -90.02471923828125,\n 47.76517619125415\n ],\n [\n -92.48291015625,\n 47.76517619125415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-03","publicationStatus":"PW","scienceBaseUri":"573ed59ce4b04a3a6a2462e0","chorus":{"doi":"10.1111/gcb.13208","url":"http://dx.doi.org/10.1111/gcb.13208","publisher":"Wiley-Blackwell","authors":"Foster Jane R., Finley Andrew O., D'Amato Anthony W., Bradford John B., Banerjee Sudipto","journalName":"Global Change Biology","publicationDate":"3/3/2016","auditedOn":"6/21/2016"},"contributors":{"authors":[{"text":"Foster, Jane R.","contributorId":27792,"corporation":false,"usgs":true,"family":"Foster","given":"Jane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":629806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finley, Andrew O.","contributorId":39310,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":629807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false},{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false}],"preferred":false,"id":629808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banerjee, Sudipto","contributorId":73894,"corporation":false,"usgs":true,"family":"Banerjee","given":"Sudipto","email":"","affiliations":[],"preferred":false,"id":629809,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174950,"text":"70174950 - 2016 - A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells","interactions":[],"lastModifiedDate":"2018-08-07T11:51:36","indexId":"70174950","displayToPublicDate":"2016-05-19T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells","docAbstract":"A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.
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A, p. 109-126, https://doi.org/10.1016/j.jhydrol.2016.05.011.","productDescription":"18 p.","startPage":"109","endPage":"126","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":325571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.9\n ],\n [\n -122,\n 37.2\n ],\n [\n -120.2,\n 37.2\n ],\n [\n -120.2,\n 37.9\n ],\n [\n -122,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"543","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57934440e4b0eb1ce79e8bd2","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, John Karl 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":127841,"corporation":false,"usgs":true,"family":"Bohlke","given":"John","email":"jkbohlke@usgs.gov","middleInitial":"Karl","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":643298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":643301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174955,"text":"70174955 - 2016 - Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation","interactions":[],"lastModifiedDate":"2016-07-22T16:11:29","indexId":"70174955","displayToPublicDate":"2016-05-19T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation","docAbstract":"General circulation model (GCM) simulations of the mid-Pliocene Warm Period (mPWP, 3.264 to 3.025 Myr ago) do not reproduce the magnitude of Northern Hemisphere high latitude surface air and sea surface temperature (SAT and SST) warming that proxy data indicate. There is also large uncertainty regarding the state of sea ice cover in the mPWP. Evidence for both perennial and seasonal mPWP Arctic sea ice is found through analyses of marine sediments, whilst in a multi-model ensemble of mPWP climate simulations, half of the ensemble simulated ice-free summer Arctic conditions. Given the strong influence that sea ice exerts on high latitude temperatures, an understanding of the nature of mPWP Arctic sea ice would be highly beneficial.
\nUsing the HadCM3 GCM, this paper explores the impact of various combinations of potential mPWP orbital forcing, atmospheric CO2 concentrations and minimum sea ice albedo on sea ice extent and high latitude warming. The focus is on the Northern Hemisphere, due to availability of proxy data, and the large data–model discrepancies in this region. Changes in orbital forcings are demonstrated to be sufficient to alter the Arctic sea ice simulated by HadCM3 from perennial to seasonal. However, this occurs only when atmospheric CO2 concentrations exceed 300 ppm. Reduction of the minimum sea ice albedo from 0.5 to 0.2 is also sufficient to simulate seasonal sea ice, with any of the combinations of atmospheric CO2 and orbital forcing. Compared to a mPWP control simulation, monthly mean increases north of 60°N of up to 4.2 °C (SST) and 9.8 °C (SAT) are simulated.
\nWith varying CO2, orbit and sea ice albedo values we are able to reproduce proxy temperature records that lean towards modest levels of high latitude warming, but other proxy data showing greater warming remain beyond the reach of our model. This highlights the importance of additional proxy records at high latitudes and ongoing efforts to compare proxy signals between sites.
","language":"English","publisher":"North-Holland Pub. Co.","doi":"10.1016/j.epsl.2016.02.036","usgsCitation":"Howell, F.W., Haywood, A.M., Dowsett, H.J., and Pickering, S.J., 2016, Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation: Earth and Planetary Science Letters, v. 441, p. 133-142, https://doi.org/10.1016/j.epsl.2016.02.036.","productDescription":"10 p.","startPage":"133","endPage":"142","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073169","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.02.036","text":"Publisher Index Page"},{"id":325567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"441","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5793444ae4b0eb1ce79e8c10","chorus":{"doi":"10.1016/j.epsl.2016.02.036","url":"http://dx.doi.org/10.1016/j.epsl.2016.02.036","publisher":"Elsevier BV","authors":"Howell Fergus W., Haywood Alan M., Dowsett Harry J., Pickering Steven J.","journalName":"Earth and Planetary Science Letters","publicationDate":"5/2016"},"contributors":{"authors":[{"text":"Howell, Fergus W.","contributorId":173110,"corporation":false,"usgs":false,"family":"Howell","given":"Fergus","email":"","middleInitial":"W.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":643333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haywood, Alan M.","contributorId":86663,"corporation":false,"usgs":true,"family":"Haywood","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pickering, Steven J.","contributorId":147378,"corporation":false,"usgs":false,"family":"Pickering","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":643335,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171437,"text":"70171437 - 2016 - Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012","interactions":[],"lastModifiedDate":"2016-06-01T16:09:56","indexId":"70171437","displayToPublicDate":"2016-05-19T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012","docAbstract":"Estimating rates of magma supply to the world's volcanoes remains one of the most fundamental aims of volcanology. Yet, supply rates can be difficult to estimate even at well-monitored volcanoes, in part because observations are noisy and are usually considered independently rather than as part of a holistic system. In this work we demonstrate a technique for probabilistically estimating time-variable rates of magma supply to a volcano through probabilistic constraint on storage and eruption rates. This approach utilizes Bayesian joint inversion of diverse datasets using predictions from a multiphysical volcano model, and independent prior information derived from previous geophysical, geochemical, and geological studies. The solution to the inverse problem takes the form of a probability density function which takes into account uncertainties in observations and prior information, and which we sample using a Markov chain Monte Carlo algorithm. Applying the technique to Kīlauea Volcano, we develop a model which relates magma flow rates with deformation of the volcano's surface, sulfur dioxide emission rates, lava flow field volumes, and composition of the volcano's basaltic magma. This model accounts for effects and processes mostly neglected in previous supply rate estimates at Kīlauea, including magma compressibility, loss of sulfur to the hydrothermal system, and potential magma storage in the volcano's deep rift zones. We jointly invert data and prior information to estimate rates of supply, storage, and eruption during three recent quasi-steady-state periods at the volcano. Results shed new light on the time-variability of magma supply to Kīlauea, which we find to have increased by 35–100% between 2001 and 2006 (from 0.11–0.17 to 0.18–0.28 km3/yr), before subsequently decreasing to 0.08–0.12 km3/yr by 2012. Changes in supply rate directly impact hazard at the volcano, and were largely responsible for an increase in eruption rate of 60–150% between 2001 and 2006, and subsequent decline by as much as 60% by 2012. We also demonstrate the occurrence of temporal changes in the proportion of Kīlauea's magma supply that is stored versus erupted, with the supply “surge” in 2006 associated with increased accumulation of magma at the summit. Finally, we are able to place some constraints on sulfur concentrations in Kīlauea magma and the scrubbing of sulfur by the volcano's hydrothermal system. Multiphysical, Bayesian constraint on magma flow rates may be used to monitor evolving volcanic hazard not just at Kīlauea but at other volcanoes around the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.04.029","usgsCitation":"Anderson, K.R., and Poland, M.P., 2016, Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012: Earth and Planetary Science Letters, v. 447, p. 161-171, https://doi.org/10.1016/j.epsl.2016.04.029.","productDescription":"11 p.","startPage":"161","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071533","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.04.029","text":"Publisher Index Page"},{"id":322056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.31784057617188,\n 19.374636239520235\n ],\n [\n -155.31784057617188,\n 19.44652177370614\n ],\n [\n -155.21896362304688,\n 19.44652177370614\n ],\n [\n -155.21896362304688,\n 19.374636239520235\n ],\n [\n -155.31784057617188,\n 19.374636239520235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"447","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500734e4b0ee97d51bb3c8","chorus":{"doi":"10.1016/j.epsl.2016.04.029","url":"http://dx.doi.org/10.1016/j.epsl.2016.04.029","publisher":"Elsevier BV","authors":"Anderson Kyle R., Poland Michael P.","journalName":"Earth and Planetary Science Letters","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":630979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":630980,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}