This report summarizes work by U.S. Geological Survey’s Columbia River Research Laboratory (USGS-CRRL) in the Wind River subbasin, from November 2011 through October 2012. Funding was provided by Bonneville Power Administration (BPA) under contract 55275. The primary focus of USGS activities during this time was tagging of parr steelhead Oncorhynchus mykiss with Passive Integrated Transponder (PIT) tags, and establishing a network of instream PIT tag interrogation systems (PTIS). The PIT-tagged parr steelhead will provide movement and life history data through recapture events and detections at instream PTIS systems, will contribute to estimates of adult steelhead returning to the Wind River, and aid in the evaluation of the removal of Hemlock Dam on Trout Creek steelhead populations.
\nThe Wind River Watershed project (BPA Project Number 1998-019-00) is a collaborative effort to restore wild steelhead in the Wind River, WA. The four partner agencies are the U.S. Forest Service (USFS), Washington Department of Fish and Wildlife (WDFW), USGS-CRRL, and Underwood Conservation District (UCD). This partnership was established in the early 1990s with support from BPA, and has continued to conduct extensive habitat, research, monitoring, and coordination activities across the subbasin. The project works at multiple levels to identify and characterize key limiting habitat factors in the Wind River; restore degraded habitats and watershed processes; document fish populations, life histories, and interactions; investigate efficacy of restoration actions; and to share information across agency and non-agency boundaries. Long-term research in the Wind River has focused on assessments of steelhead/rainbow trout populations, relationships with introduced populations of spring Chinook salmon O. tshawytscha and brook trout Salvelinus fontinalis, and effects of habitat variables and habitat restoration on fish productivity.
\nDuring the period covered by this report, we PIT tagged steelhead parr in headwater sections of the subbasin (Figure 1), maintained a PTIS in Trout Creek, installed a PTIS in the Wind River, and installed smaller scale PTISs in Trapper Creek, Paradise Creek, and the Wind River upstream of Paradise Creek (Figure 2). Additionally we maintained thermologgers to collect water temperature data near the PIT tagging sites.
\nA statement of work (SOW) was submitted to BPA in October 2011 that outlined work to be performed by USGS-CRRL. The SOW was organized by Work Element (WE), with each describing a research task. This report summarizes the progress completed under each WE.
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November 2011 through October 2012, 40 p.","productDescription":"40 p.","numberOfPages":"41","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2011-11-01","temporalEnd":"2012-10-31","ipdsId":"IP-045885","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":287615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280261,"type":{"id":11,"text":"Document"},"url":"https://pisces.bpa.gov/release/documents/documentviewer.aspx?doc=P133526","text":"Report","size":"648.14 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.982107,45.715023 ], [ -121.982107,45.88214 ], [ -121.787086,45.88214 ], [ -121.787086,45.715023 ], [ -121.982107,45.715023 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b408e4b09e18fc023ad9","contributors":{"authors":[{"text":"Jezorek, Ian G. 0000-0002-3842-3485 ijezorek@usgs.gov","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":3572,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","email":"ijezorek@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487296,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046702,"text":"ds774 - 2013 - National assessment of geologic carbon dioxide storage resources: data","interactions":[],"lastModifiedDate":"2013-10-30T13:32:13","indexId":"ds774","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"774","title":"National assessment of geologic carbon dioxide storage resources: data","docAbstract":"In 2012, the U.S. Geological Survey (USGS) completed the national assessment of geologic carbon dioxide storage resources. Its data and results are reported in three publications: the assessment data publication (this report), the assessment results publication (U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013a, USGS Circular 1386), and the assessment summary publication (U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013b, USGS Fact Sheet 2013–3020). This data publication supports the results publication and contains (1) individual storage assessment unit (SAU) input data forms with all input parameters and details on the allocation of the SAU surface land area by State and general land-ownership category; (2) figures representing the distribution of all storage classes for each SAU; (3) a table containing most input data and assessment result values for each SAU; and (4) a pairwise correlation matrix specifying geological and methodological dependencies between SAUs that are needed for aggregation of results.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds774","usgsCitation":"U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013, National assessment of geologic carbon dioxide storage resources: data (Version 1: Originally posted June 2013; Version 1.1: September 2013): U.S. Geological Survey Data Series 774, Report: viii, 13 p.; 2 Appendices; 2 Tables, https://doi.org/10.3133/ds774.","productDescription":"Report: viii, 13 p.; 2 Appendices; 2 Tables","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":274233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds774.gif"},{"id":278266,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/774/pdf/DS774_508.pdf"},{"id":278267,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/774/pdf/Appendix_1.pdf"},{"id":278268,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/774/pdf/Appendix_2.pdf"},{"id":278269,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/774/tables/Table_1.xlsx"},{"id":278270,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/774/tables/Table_2.xlsx"},{"id":274230,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/774/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916667 ], [ 173.0,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173.0,16.916667 ] ] ] } } ] }","edition":"Version 1: Originally posted June 2013; Version 1.1: September 2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff56e4b052f2a453987f","contributors":{"authors":[{"text":"U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team","contributorId":128059,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team","id":535563,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193597,"text":"70193597 - 2013 - Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements","interactions":[],"lastModifiedDate":"2019-12-21T08:50:42","indexId":"70193597","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements","docAbstract":"Direct and remote measurements of volcanic gas composition, SO2 flux, and eruptive SO2 mass from Bezymianny Volcano were acquired between July 2007 and July 2010. Chemical composition of fumarolic gases, plume SO2 flux from ground and air-based ultraviolet remote sensing (FLYSPEC), and eruptive SO2 mass from Ozone Monitoring Instrument (OMI) satellite observations were used along with eruption timing to elucidate magma processes and subsurface conditions, and to constrain total volatile flux. Bezymianny Volcano had five explosive magmatic eruptions between May 2007 and June 2010. The most complete volcanic gas datasets were acquired for the October 2007, December 2009, and May 2010 eruptions. Gas measurements collected prior to the October 2007 eruption have a relatively high ratio of H2O/CO2 (81.2), a moderate ratio of CO2/S (5.47), and a low ratio of S/HCl (0.338), along with moderate SO2 and CO2 fluxes of 280 and 980 t/d, respectively, and high H2O and HCl fluxes of ~ 45,000 and ~ 440 t/d, respectively. These results suggest degassing of shallow magma (consistent with observations of lava extrusion) along with potential minor degassing of a deeper magma source. Gas measurements collected prior to the December 2009 eruption are characterized by relatively low H2O/CO2 (4.13), moderate CO2/S (6.84), and high S/HCl (18.7) ratios, along with moderate SO2 and CO2 fluxes of ~ 220 and ~ 1000 t/d, respectively, and low H2O and HCl fluxes of ~ 1700 and ~ 7 t/d, respectively. These trends are consistent with degassing of a deeper magma source. Fumarole samples collected ~ 1.5 months following the May 2010 eruption are characterized by high H2O/CO2 (63.0), low CO2/S (0.986), and moderate S/HCl (6.09) ratios. These data are consistent with degassing of a shallow, volatile-rich magma source, likely related to the May eruption. Passive and eruptive SO2 measurements are used to calculate a total annual SO2 mass of 109 kt emitted in 2007, with passive emissions comprising ~ 87–95% of the total. Total annual volatile masses for the study period are estimated to range from 1.1 × 106 to 18 × 106 t/year. Annual CO2 masses are ~ 8 to 40 times larger than can be explained by degassing of dissolved CO2 within eruptive magma, suggesting that the eruptive magma contained a significant quantity of exsolved volatiles sourced either from the eruptive melt or unerupted magma at depth. Variable total volatile fluxes ranging from ~ 3000 t/d in 2009 to ~ 49,000 t/d in 2007 are attributed to variations in the depth of gas exsolution and separation from the melt under open-system degassing conditions. We propose that exsolved volatiles are quickly transported to the surface from ascending magma via permeable flow through a bubble and/or fracture network within the conduit and thus retain their equilibrium composition at the time of segregation from melt. The composition of surface CO2 and H2O emissions from 2007 to 2009 are compared with modeled exsolved fluid compositions for a magma body ascending from entrapment depths to estimate depth of fluid exsolution and separation from the melt. We find that at the time of sample collection magma had already begun ascent from the mid-crustal storage region and was located at maximum depths of ~ 3.7 km in August 2007, approximately 2 months prior to the next magmatic eruption, and ~ 4.6 km in July of 2009 approximately five months prior to the next magmatic eruption. These findings suggest that the exsolved gas composition at Bezymianny Volcano may be used to detect magma ascent prior to eruption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.10.015","usgsCitation":"Lopez, T., Ushakov, S., Izbekov, P., Tassi, F., Cahill, C., Neill, O., and Werner, C.A., 2013, Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements: Journal of Volcanology and Geothermal Research, v. 263, p. 92-107, https://doi.org/10.1016/j.jvolgeores.2012.10.015.","productDescription":"16 p.","startPage":"92","endPage":"107","ipdsId":"IP-042711","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473629,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.openaccessrepository.it/record/25641","text":"Publisher Index Page"},{"id":348148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Bezymianny Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 159.521484375,\n 55.178867663281984\n ],\n [\n 161.60888671875,\n 55.178867663281984\n ],\n [\n 161.60888671875,\n 57.028773851491124\n ],\n [\n 159.521484375,\n 57.028773851491124\n ],\n [\n 159.521484375,\n 55.178867663281984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"263","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eace4b0531197b27fbb","contributors":{"authors":[{"text":"Lopez, Taryn","contributorId":146828,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":16753,"text":"University of Alaska Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":719977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ushakov, Sergey","contributorId":12135,"corporation":false,"usgs":true,"family":"Ushakov","given":"Sergey","email":"","affiliations":[],"preferred":false,"id":719978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Izbekov, Pavel","contributorId":85950,"corporation":false,"usgs":true,"family":"Izbekov","given":"Pavel","affiliations":[],"preferred":false,"id":719979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tassi, Franco","contributorId":95776,"corporation":false,"usgs":true,"family":"Tassi","given":"Franco","email":"","affiliations":[],"preferred":false,"id":719980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahill, Cathy","contributorId":199768,"corporation":false,"usgs":false,"family":"Cahill","given":"Cathy","email":"","affiliations":[],"preferred":false,"id":719981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neill, Owen","contributorId":199769,"corporation":false,"usgs":false,"family":"Neill","given":"Owen","affiliations":[],"preferred":false,"id":719982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719983,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046371,"text":"70046371 - 2013 - Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging","interactions":[],"lastModifiedDate":"2018-06-16T17:48:39","indexId":"70046371","displayToPublicDate":"2013-07-31T21:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging","docAbstract":"During Arctic summers, sea ice provides resting habitat for Pacific walruses as it drifts over foraging areas in the eastern Chukchi Sea. Climate-driven reductions in sea ice have recently created ice-free conditions in the Chukchi Sea by late summer causing walruses to rest at coastal haulouts along the Chukotka and Alaska coasts, which provides an opportunity to study walruses at relatively accessible locations. Walrus age can be determined from the ratio of tusk length to snout dimensions. We evaluated use of images obtained from a gyro-stabilized video system mounted on a helicopter flying at high altitudes (to avoid disturbance) to classify the sex and age of walruses hauled out on Alaska beaches in 2010–2011. We were able to classify 95% of randomly selected individuals to either an 8- or 3-category age class, and we found measurement-based age classifications were more repeatable than visual classifications when using images presenting the correct head profile. Herd density at coastal haulouts averaged 0.88 walruses/m2 (std. err. = 0.02), herd size ranged from 8,300 to 19,400 (CV 0.03–0.06) and we documented ~30,000 animals along ~1 km of beach in 2011. Within the herds, dependent walruses (0–2 yr-olds) tended to be located closer to water, and this tendency became more pronounced as the herd spent more time on the beach. Therefore, unbiased estimation of herd age-ratios will require a sampling design that allows for spatial and temporal structuring. In addition, randomly sampling walruses available at the edge of the herd for other purposes (e.g., tagging, biopsying) will not sample walruses with an age structure representative of the herd. Sea ice losses are projected to continue, and population age structure data collected with aerial videography at coastal haulouts may provide demographic information vital to ongoing efforts to understand effects of climate change on this species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0069806","usgsCitation":"Monson, D., Udevitz, M.S., and Jay, C.V., 2013, Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging: PLoS ONE, v. 8, no. 7, https://doi.org/10.1371/journal.pone.0069806.","ipdsId":"IP-045689","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0069806","text":"Publisher Index Page"},{"id":277155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277133,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0069806"}],"country":"United States","volume":"8","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-07-31","publicationStatus":"PW","scienceBaseUri":"52206d61e4b0645fc25e8c2d","contributors":{"authors":[{"text":"Monson, Daniel H. 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":140480,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel H.","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":479564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":479562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":479563,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047325,"text":"fs20133066 - 2013 - Relationships between the health of Alaska Native communities and our environment -- phase 1, exploring and communicating","interactions":[],"lastModifiedDate":"2013-07-31T15:48:37","indexId":"fs20133066","displayToPublicDate":"2013-07-31T15:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3066","title":"Relationships between the health of Alaska Native communities and our environment -- phase 1, exploring and communicating","docAbstract":"Alaska Natives depend on local natural resources for nutritional and, for many, spiritual health. As a result, public health in Alaska is strongly influenced by the relationship between people and their surrounding physical, chemical, and biological environments. Alaska is vast with diverse wildlife and plant communities that are valued as subsistence foods (fig. 1). These resources are supported by equally diverse ecosystems and their underpinning landforms and geologies. The U.S. Geological Survey (USGS) is attempting to integrate physical, chemical, and biological information to better describe current (2013) environments and project scenarios for the future. Integrating ecological data into the public health dialogue is challenging for the more than 280 rural communities of Alaska. This fact sheet reviews a recent USGS effort, the Geographic Information System (GIS) Native Health Project, to better incorporate scientific information into such dialogue.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133066","usgsCitation":"Smith, D., 2013, Relationships between the health of Alaska Native communities and our environment -- phase 1, exploring and communicating: U.S. Geological Survey Fact Sheet 2013-3066, 4 p., https://doi.org/10.3133/fs20133066.","productDescription":"4 p.","numberOfPages":"4","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":275646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133066.bmp"},{"id":275645,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3066/"},{"id":275644,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3066/pdf/fs20133066.pdf"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.45,51.21 ], [ 172.45,71.39 ], [ -129.99,71.39 ], [ -129.99,51.21 ], [ 172.45,51.21 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fa2c80e4b076c3a8d82623","contributors":{"authors":[{"text":"Smith, Durelle","contributorId":24258,"corporation":false,"usgs":true,"family":"Smith","given":"Durelle","email":"","affiliations":[],"preferred":false,"id":481712,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047254,"text":"ofr20131178 - 2013 - Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park","interactions":[],"lastModifiedDate":"2013-07-31T15:50:02","indexId":"ofr20131178","displayToPublicDate":"2013-07-31T15:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1178","title":"Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park","docAbstract":"Shenandoah National Park has been monitoring water chemistry and benthic macroinvertebrates in stream ecosystems since 1979. These monitoring efforts were designed to assess the status and trends in stream condition associated with atmospheric deposition (acid rain) and changes in forest health due to gypsy moth infestations. The primary objective of the present research was to determine whether the current long-term macroinvertebrate and water-quality monitoring program in Shenandoah National Park was failing to capture important information on the status and trends in stream condition by not sufficiently representing smaller, headwater streams. The current benthic-macroinvertebrate and water-chemistry sampling designs do not include routine collection of data from streams with contributing watershed areas smaller than 100 hectares, even though these small streams represent the overwhelming proportion of total stream length in the park. In this study, we sampled headwater sites, including headwater stream reaches (contributing watershed area approximately 100 hectares (ha) and perennial springs, in the park for aquatic macroinvertebrates and water chemistry and compared the results with current and historical data collected at long-term ecological monitoring (LTEM) sites on larger streams routinely sampled as part of ongoing monitoring efforts. The larger purpose of the study was to inform ongoing efforts by park managers to evaluate the effectiveness and efficiency of the current aquatic monitoring program in light of other potential stressors (for example, climate change) and limited resources. Our results revealed several important findings that could influence management decisions regarding long-term monitoring of park streams. First, we found that biological indicators of stream condition at headwater sites and perennial springs generally were more indicative of lower habitat quality and were more spatially variable than those observed at sites on routinely monitored larger streams. We hypothesized that poorer stream condition observed in smaller streams was due to stream drying that occurs more frequently in headwater areas. We also found that biological and water-chemistry measures responded differently to landscape drivers. Variation in most biological endpoints was driven primarily by stream size and was only secondarily associated with bedrock geology. In contrast, water chemistry showed essentially the opposite pattern, with underlying geology explaining much of the variation and stream size being of secondary importance. Therefore, expanding the LTEM program to include headwater areas would yield substantially different biological information, whereas broad inferences regarding spatial patterns in water chemistry would probably not change. Although significant differences in community composition were observed among streams of different sizes, no taxa were unique to headwater sites. All taxa collected at the 45 headwater sites also had been collected at one or more LTEM sites during one or more years. This observation indicates that headwater sites in the park may be structured by biotic nestedness; consequently, focusing management efforts on preserving the species pool at the larger LTEM sites would likely result in the protection of most taxa parkwide. Finally, linkages (correlations) between water chemistry and biological measures of stream condition were signficantly stronger when assessed at the LTEM sites than when assessed at the springs or headwater sites, indicating that conditions at downstream sites may be better indicators of water-quality trends.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131178","collaboration":"Prepared in Cooperation with the National Park Service","usgsCitation":"Snyder, C.D., Webb, J., Young, J.A., and Johnson, Z.B., 2013, Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park: U.S. Geological Survey Open-File Report 2013-1178, v, 46 p., https://doi.org/10.3133/ofr20131178.","productDescription":"v, 46 p.","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049033","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":275649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131178.gif"},{"id":275648,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1178/pdf/ofr2013-1178.pdf"},{"id":275647,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1178/"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79,8.333333333333334E-4 ], [ -79,8.333333333333334E-4 ], [ -78,8.333333333333334E-4 ], [ -78,8.333333333333334E-4 ], [ -79,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fa2c80e4b076c3a8d8262f","contributors":{"authors":[{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":481529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, James R.","contributorId":74431,"corporation":false,"usgs":true,"family":"Webb","given":"James R.","affiliations":[],"preferred":false,"id":481532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":481530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Zane B.","contributorId":21441,"corporation":false,"usgs":true,"family":"Johnson","given":"Zane","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":481531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199861,"text":"70199861 - 2013 - Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","interactions":[],"lastModifiedDate":"2018-10-01T15:22:10","indexId":"70199861","displayToPublicDate":"2013-07-31T15:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","docAbstract":"Introduction
Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.
Methods
The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region.
Results
As a result of calibration, predicted basin discharge closely matches measured data for validation watersheds. The CA-BCM recharge and runoff estimates, combined with estimates of snowpack and timing of snowmelt, provide a basis for assessing variations in water availability. Another important output variable, climatic water deficit, integrates the combined effects of temperature and rainfall on site-specific soil moisture, a factor that plants may respond to more directly than air temperature and precipitation alone. Model outputs are calculated for each grid cell, allowing results to be summarized for a variety of planning units including hillslopes, watersheds, ecoregions, or political boundaries.
Conclusions
The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes, such as projections of changes in water availability, environmental demand, or distribution of plants and habitats. Here we present the framework of the CA-BCM model for the California hydrologic region, a test of model performance on 159 watersheds, summary results for the region for the 1981–2010 time period, and changes since the 1951–1980 time period.
Reliable knowledge of the status and trend of carnivore populations is critical to their conservation and management. Methods for monitoring carnivores, however, are challenging to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost-efficient method for monitoring gray wolf (Canis lupus) populations. Montana Fish, Wildlife and Parks (MFWP) conducts annual telephone surveys of >50,000 deer and elk hunters. We explored how survey data on hunters' sightings of wolves could be used to estimate the occupancy and distribution of wolf packs and predict their abundance in Montana for 2007–2009. We assessed model utility by comparing our predictions to MFWP minimum known number of wolf packs. We minimized false positive detections by identifying a patch as occupied if 2–25 wolves were detected by ≥3 hunters. Overall, estimates of the occupancy and distribution of wolf packs were generally consistent with known distributions. Our predictions of the total area occupied increased from 2007 to 2009 and predicted numbers of wolf packs were approximately 1.34–1.46 times the MFWP minimum counts for each year of the survey. Our results indicate that multi-season occupancy models based on public sightings can be used to monitor populations and changes in the spatial distribution of territorial carnivores across large areas where alternative methods may be limited by personnel, time, accessibility, and budget constraints.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.562","usgsCitation":"Rich, L.N., Russell, R.E., Glenn, E., Mitchell, M.S., Gude, J., Podruzny, K.M., Sime, C.A., Laudon, K., Ausband, D., and Nichols, J., 2013, Estimating occupancy and predicting numbers of gray wolf packs in Montana using hunter surveys: Journal of Wildlife Management, v. 77, no. 6, p. 1280-1289, https://doi.org/10.1002/jwmg.562.","productDescription":"10 p.","startPage":"1280","endPage":"1289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028210","costCenters":[{"id":399,"text":"Montana Cooperative Wildlife Research Unit","active":false,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":275554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.05,44.36 ], [ -116.05,49.0 ], [ -104.04,49.0 ], [ -104.04,44.36 ], [ -116.05,44.36 ] ] ] } } ] }","volume":"77","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-26","publicationStatus":"PW","scienceBaseUri":"51f8d257e4b0cecbe8fa9814","contributors":{"authors":[{"text":"Rich, Lindsey N.","contributorId":42119,"corporation":false,"usgs":true,"family":"Rich","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":348233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":348231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Elizabeth M.","contributorId":96568,"corporation":false,"usgs":true,"family":"Glenn","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":348238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":348230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":348237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Podruzny, Kevin M.","contributorId":85865,"corporation":false,"usgs":true,"family":"Podruzny","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":348236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sime, Carolyn A.","contributorId":76627,"corporation":false,"usgs":true,"family":"Sime","given":"Carolyn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":348235,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Laudon, Kent","contributorId":16298,"corporation":false,"usgs":true,"family":"Laudon","given":"Kent","email":"","affiliations":[],"preferred":false,"id":348232,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":348234,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":348229,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70047284,"text":"dsDS709CC - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-07-30T09:40:27","indexId":"dsDS709CC","displayToPublicDate":"2013-07-29T20:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"CC","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits.\n\nALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.\n\nelevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Parwan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dsDS709CC","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey; This report is Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme Text; 4 Index Maps; 4 Image Files; 4 Metadata Files; Shapefiles, https://doi.org/10.3133/dsDS709CC.","productDescription":"HTML Document; Readme Text; 4 Index Maps; 4 Image Files; 4 Metadata Files; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049057","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":275537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/dsds709cc.PNG"},{"id":275531,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/cc/"},{"id":275536,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/cc/shapefiles/shapefiles.html"},{"id":275532,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/cc/1_readme.txt"},{"id":275533,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/cc/index_maps/index_maps.html"},{"id":275534,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/cc/image_files/image_files.html"},{"id":275535,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/cc/metadata/metadata.html"}],"country":"Afghanistan","otherGeospatial":"Parwan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 58.0,28.0 ], [ 58.0,40.0 ], [ 78.0,40.0 ], [ 78.0,28.0 ], [ 58.0,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f780d6e4b02e26443a9329","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":481610,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70044756,"text":"70044756 - 2013 - Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data","interactions":[],"lastModifiedDate":"2013-08-12T09:42:50","indexId":"70044756","displayToPublicDate":"2013-07-29T13:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data","docAbstract":"Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Arctic, Antarctic, and Alpine Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Arctic and Alpine Research (INSTAAR)","doi":"10.1657/1938-4246-45.1.64","usgsCitation":"Kolden, C.A., and Rogan, J., 2013, Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data: Arctic, Antarctic, and Alpine Research, v. 45, no. 1, p. 64-76, https://doi.org/10.1657/1938-4246-45.1.64.","productDescription":"13 p.","startPage":"64","endPage":"76","ipdsId":"IP-018916","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":473641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1657/1938-4246-45.1.64","text":"Publisher Index Page"},{"id":275517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275509,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1657/1938-4246-45.1.64"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -151.3861,68.8704 ], [ -151.3861,69.311 ], [ -149.7285,69.311 ], [ -149.7285,68.8704 ], [ -151.3861,68.8704 ] ] ] } } ] }","volume":"45","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"51f780d6e4b02e26443a932d","contributors":{"authors":[{"text":"Kolden, Crystal A.","contributorId":98610,"corporation":false,"usgs":true,"family":"Kolden","given":"Crystal","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogan, John","contributorId":83008,"corporation":false,"usgs":true,"family":"Rogan","given":"John","email":"","affiliations":[],"preferred":false,"id":476286,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044614,"text":"70044614 - 2013 - Intercontinental migratory connectivity and population structuring of Dunlins from western Alaska","interactions":[],"lastModifiedDate":"2018-05-20T11:30:37","indexId":"70044614","displayToPublicDate":"2013-07-29T12:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Intercontinental migratory connectivity and population structuring of Dunlins from western Alaska","docAbstract":"The Dunlin (Calidris alpina) is a polytypic shorebird with complex patterns of distribution and migration throughout its holarctic range. We analyzed mark-re sighting data obtained between 1977 and 2010 from birds captured at two major staging areas in western Alaska to test the hypothesis that the migration patterns of Alaskan populations are a mixture of parallel and chain, similar to those of Dunlin populations in the western Palearctic. Birds marked on the Yukon—Kuskokwim Delta were found wintering in both Asia and North America, which documented the unexpected mixing of C. a. arcticola from northern Alaska and C. a. pacifica from western Alaska and contradicted our initial prediction of parallel migration pathways for these two subspecies. In its North American winter range C. a. pacifica segregated according to location of marking, confirming our prediction of a chain migration pattern within this population. Individuals of C. a. pacifica marked on the delta were resighted significantly farther north, mostly in southern British Columbia and Washington, than birds marked on the second, more southerly staging area on the Alaska Peninsula, which were resighted primarily in the San Francisco Bay area of northern California. We recommend additional studies use a combination of intrinsic and extrinsic markers to quantify the strength of migratory connectivity between breeding, staging, and wintering areas. Such information is needed to guide conservation efforts because the Dunlin and other waterbirds are losing intertidal habitats at an unprecedented rate and scale, particularly in the Yellow Sea and other parts of Asia.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1525/cond.2013.120127","usgsCitation":"Gill, R., Handel, C.M., and Ruthrauff, D.R., 2013, Intercontinental migratory connectivity and population structuring of Dunlins from western Alaska: The Condor, v. 115, no. 3, p. 525-534, https://doi.org/10.1525/cond.2013.120127.","productDescription":"10 p.","startPage":"525","endPage":"534","numberOfPages":"10","ipdsId":"IP-041725","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":280757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280758,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1525/cond.2013.120127"}],"country":"United States","state":"Alaska","otherGeospatial":"Angyoyaravak Bay;Egegik Bay;Izembek Lagoon;Kigigak Bay;Nelson Lagoon;Ugashik Bay;Yukon-kuskokwim Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -169.53,51.21 ], [ -169.53,66.59 ], [ -152.93,66.59 ], [ -152.93,51.21 ], [ -169.53,51.21 ] ] ] } } ] }","volume":"115","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd62cbe4b0b290850fe696","contributors":{"authors":[{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":476012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":476011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruthrauff, Daniel R. 0000-0003-1355-9156 druthrauff@usgs.gov","orcid":"https://orcid.org/0000-0003-1355-9156","contributorId":4181,"corporation":false,"usgs":true,"family":"Ruthrauff","given":"Daniel","email":"druthrauff@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":476013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047264,"text":"sir20135041 - 2013 - Hydrogeology, groundwater seepage, nitrate distribution, and flux at the Raleigh hydrologic research station, Wake County, North Carolina, 2005-2007","interactions":[],"lastModifiedDate":"2017-02-07T10:21:11","indexId":"sir20135041","displayToPublicDate":"2013-07-29T09:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5041","title":"Hydrogeology, groundwater seepage, nitrate distribution, and flux at the Raleigh hydrologic research station, Wake County, North Carolina, 2005-2007","docAbstract":"rom 2005 to 2007, the U.S. Geological Survey and the North Carolina Department of Environment and Natural Resources, Division of Water Quality, conducted a study to describe the geologic framework, measure groundwater quality, characterize the groundwater-flow system, and describe the groundwater/surface-water interaction at the 60-acre Raleigh hydrogeologic research station (RHRS) located at the Neuse River Waste Water Treatment Plant in eastern Wake County, North Carolina. Previous studies have shown that the local groundwater quality of the surficial and bedrock aquifers at the RHRS had been affected by high levels of nutrients. Geologic, hydrologic, and water-quality data were collected from 3 coreholes, 12 wells, and 4 piezometers at 3 well clusters, as well as from 2 surface-water sites, 2 multiport piezometers, and 80 discrete locations in the streambed of the Neuse River. Data collected were used to evaluate the three primary zones of the Piedmont aquifer (regolith, transition zone, and fractured bedrock) and characterize the interaction of groundwater and surface water as a mechanism of nutrient transport to the Neuse River. A conceptual hydrogeologic cross section across the RHRS was constructed using new and existing data. Two previously unmapped north striking, nearly vertical diabase dikes intrude the granite beneath the site. Groundwater within the diabase dike appeared to be hydraulically isolated from the surrounding granite bedrock and regolith. A correlation exists between foliation and fracture orientation, with most fractures striking parallel to foliation. Flowmeter logging in two of the bedrock wells indicated that not all of the water-bearing fractures labeled as water bearing were hydraulically active, even when stressed by pumping. Groundwater levels measured in wells at the RHRS displayed climatic and seasonal trends, with elevated groundwater levels occurring during the late spring and declining to a low in the late fall. Vertical gradients in the groundwater discharge area near the Neuse River were complex and were affected by fluctuations in river stage, with the exception of a well completed in a diabase dike. Water-quality data from the wells and surface-water sites at the RHRS were collected continuously as well as during periodic sampling events. Surface-water samples collected from a tributary were most similar in chemical composition to groundwater found in the regolith and transition zone. Nitrate (measured as nitrite plus nitrate, as nitrogen) concentrations in the sampled wells and tributary ranged from about 5 to more than 120 milligrams per liter as nitrogen. Waterborne continuous resistivity profiling conducted on the Neuse River in the area of the RHRS measured areas of low apparent resistivity that likely represent groundwater contaminated by high concentrations of nitrate. These areas were located on either side of a diabase dike and at the outfall of two unnamed tributaries. The diabase dike preferentially directed the discharge of groundwater to the Neuse River and may isolate groundwater movement laterally. Discrete temperature measurements made within the pore water beneath the Neuse River revealed seeps of colder groundwater discharging into warmer surface water near a diabase dike. Water-quality samples collected from the pore water beneath the Neuse River indicated that nitrate was present at concentrations as high as 80 milligrams per liter as nitrogen on the RHRS side of the river. The highest concentrations of nitrate were located within pore water collected from an area near a diabase dike that was identified as a suspected seepage area. Hydraulic head was measured and pore water samples were collected from two 140-centimeter-deep (55.1-inch-deep) multiport piezometers that were installed in bed sediments on opposite sides of a diabase dike. The concentration of nitrate in pore water at a suspected seepage area ranged from 42 to 82 milligrams per liter as nitrogen with a median concentration of 79 milligrams per liter as nitrogen. On the opposite side of the dike, concentrations of nitrate in pore water samples ranged from 3 to 91 milligrams per liter as nitrogen with a median concentration of 52 milligrams per liter. At one of the multiport piezometers the vertical gradient of hydraulic head between the Neuse River and the groundwater was too small to measure. At the multiport piezometer located in the suspected seepage area, an upward gradient of about 0.1 was present and explains the occurrence of higher concentrations of nitrate near the sediment/water interface. Horizontal seepage flux from the surficial aquifer to the edge of the Neuse River was estimated for 2006. Along a 130-foot flow path, the estimated seepage flux ranged from –0.52 to 0.2 foot per day with a median of 0.09 foot per day. The estimated advective horizontal mass flux of nitrate along a 300-foot reach of the Neuse River ranged from –10.9 to 5 pounds per day with a median of 2.2 pounds per day. The total horizontal mass flux of nitrate from the surficial aquifer to the Neuse River along the 130-foot flow path was estimated to be about 750 pounds for all of 2006. Seepage meters were deployed on the bed of the Neuse River in the areas of the multiport piezometers on either side of the diabase dike to estimate rates of vertical groundwater discharge and flux of nitrate. The average estimated daily seepage flux differed by two orders of magnitude between seepage areas. The potential vertical flux of nitrate from groundwater to the Neuse River was estimated at an average of 2.5 grams per day near one of the multiport piezometers and an average of 784 grams per day at the other. These approximations suggest that under some hydrologic conditions there is the potential for substantial quantities of nitrate to discharge from the groundwater to the Neuse River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135041","collaboration":"Prepared In Cooperation With The North Carolina Department Of Environment And Natural Resources Division Of Water Quality","usgsCitation":"McSwain, K., Bolich, R.E., and Chapman, M.J., 2013, Hydrogeology, groundwater seepage, nitrate distribution, and flux at the Raleigh hydrologic research station, Wake County, North Carolina, 2005-2007: U.S. Geological Survey Scientific Investigations Report 2013-5041, viii, 54 p., https://doi.org/10.3133/sir20135041.","productDescription":"viii, 54 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":275495,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5041/"},{"id":275496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135041.gif"},{"id":275494,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5041/pdf/sir2013-5041.pdf"}],"country":"United States","state":"North Carolina","otherGeospatial":"Neuse River Waste Water Treatment Plant","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.32,33.84 ], [ -84.32,36.59 ], [ -78.04,36.59 ], [ -78.04,33.84 ], [ -84.32,33.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f780d6e4b02e26443a9325","contributors":{"authors":[{"text":"McSwain, Kristen Bukowski","contributorId":104458,"corporation":false,"usgs":true,"family":"McSwain","given":"Kristen Bukowski","affiliations":[],"preferred":false,"id":481565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bolich, Richard E.","contributorId":89615,"corporation":false,"usgs":true,"family":"Bolich","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":481564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Melinda J. 0000-0003-4021-0320 mjchap@usgs.gov","orcid":"https://orcid.org/0000-0003-4021-0320","contributorId":1597,"corporation":false,"usgs":true,"family":"Chapman","given":"Melinda","email":"mjchap@usgs.gov","middleInitial":"J.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481563,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70118239,"text":"70118239 - 2013 - cBathy: A robust algorithm for estimating nearshore bathymetry","interactions":[],"lastModifiedDate":"2014-07-28T09:42:35","indexId":"70118239","displayToPublicDate":"2013-07-28T09:38:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"cBathy: A robust algorithm for estimating nearshore bathymetry","docAbstract":"A three-part algorithm is described and tested to provide robust bathymetry maps based solely on long time series observations of surface wave motions. The first phase consists of frequency-dependent characterization of the wave field in which dominant frequencies are estimated by Fourier transform while corresponding wave numbers are derived from spatial gradients in cross-spectral phase over analysis tiles that can be small, allowing high-spatial resolution. Coherent spatial structures at each frequency are extracted by frequency-dependent empirical orthogonal function (EOF). In phase two, depths are found that best fit weighted sets of frequency-wave number pairs. These are subsequently smoothed in time in phase 3 using a Kalman filter that fills gaps in coverage and objectively averages new estimates of variable quality with prior estimates. Objective confidence intervals are returned. Tests at Duck, NC, using 16 surveys collected over 2 years showed a bias and root-mean-square (RMS) error of 0.19 and 0.51 m, respectively but were largest near the offshore limits of analysis (roughly 500 m from the camera) and near the steep shoreline where analysis tiles mix information from waves, swash and static dry sand. Performance was excellent for small waves but degraded somewhat with increasing wave height. Sand bars and their small-scale alongshore variability were well resolved. A single ground truth survey from a dissipative, low-sloping beach (Agate Beach, OR) showed similar errors over a region that extended several kilometers from the camera and reached depths of 14 m. Vector wave number estimates can also be incorporated into data assimilation models of nearshore dynamics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research C: Oceans","largerWorkSubtype":{"id":10,"text":"Journal Article"},"publisher":"Journal of Geophysical Research: Oceans","doi":"10.1002/jgrc.20199","usgsCitation":"Plant, N.G., Holman, R., and Holland, K.T., 2013, cBathy: A robust algorithm for estimating nearshore bathymetry: Journal of Geophysical Research C: Oceans, v. 118, no. 5, p. 2595-2609, https://doi.org/10.1002/jgrc.20199.","productDescription":"15 p.","startPage":"2595","endPage":"2609","ipdsId":"IP-040687","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":291099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291078,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrc.20199"}],"country":"United States","state":"North Carolina","city":"Duck","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.776116,36.150973 ], [ -75.776116,36.231587 ], [ -75.736833,36.231587 ], [ -75.736833,36.150973 ], [ -75.776116,36.150973 ] ] ] } } ] }","volume":"118","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-05-22","publicationStatus":"PW","scienceBaseUri":"57f7f287e4b0bc0bec0a0434","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":496487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holman, Rob","contributorId":46432,"corporation":false,"usgs":true,"family":"Holman","given":"Rob","affiliations":[],"preferred":false,"id":496488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":496489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047262,"text":"ofr20131144 - 2013 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012","interactions":[],"lastModifiedDate":"2013-07-27T11:45:43","indexId":"ofr20131144","displayToPublicDate":"2013-07-27T11:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1144","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012","docAbstract":"Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January to December 2012. These data serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.\n\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and in M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2012, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported for previous time periods. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se were generally similar in timing and magnitude as those for Ag and Cu. In 2012, metal concentrations in both sediments and clam tissue were among the lowest concentrations on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.\n\nAnalyses of the benthic community structure of a mudflat in South San Francisco Bay over a 39-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of the M. petalum community shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2012), with almost all animals initiating reproduction in the fall and spawning the following spring. The community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for those deep-dwelling animals like Macoma petalum. Animals immediately returned to the mudflat in 2008, which was the first indication that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2012 is reflective of the species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2012 benthic community data, which show that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of animals that consume the sediment, filter feed, have pelagic larvae that must survive landing on the sediment, and brood their young. USGS scientists continue to observe the community’s response to the 2008 defaunation event because it allows them to examine the response of the community to a natural disturbance (possible causes include sediment accretion or freshwater inundation) and compare this recovery to the long-term recovery observed in the 1970s when the decline in sediment pollutants was the dominating factor.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131144","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Dyke, J., Thompson, J.K., Cain, D.J., Kleckner, A.E., Parcheso, F., Luoma, S.N., and Hornberger, M.I., 2013, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012: U.S. Geological Survey Open-File Report 2013-1144, vi, 109 p.; Tables; Appendixes, https://doi.org/10.3133/ofr20131144.","productDescription":"vi, 109 p.; Tables; Appendixes","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":275491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131144.gif"},{"id":275489,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_tables.xlsx"},{"id":275490,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_appendixes.xlsx"},{"id":275487,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1144/"},{"id":275488,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_text.pdf"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.75,36.75 ], [ -122.75,38.5 ], [ -121.5,38.5 ], [ -121.5,36.75 ], [ -122.75,36.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f4ddd9e4b0838938b28033","contributors":{"authors":[{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":481556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":481555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":481558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleckner, Amy E. kleckner@usgs.gov","contributorId":4258,"corporation":false,"usgs":true,"family":"Kleckner","given":"Amy","email":"kleckner@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parcheso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":2590,"corporation":false,"usgs":true,"family":"Parcheso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":481560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":481557,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047261,"text":"ofr20131150 - 2013 - Abundance, distribution, and population trends of the iconic Hawaiian Honeycreeper, the ʻIʻiwi (Vestiaria coccinea) throughout the Hawaiian Islands","interactions":[],"lastModifiedDate":"2013-07-27T11:27:51","indexId":"ofr20131150","displayToPublicDate":"2013-07-27T11:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1150","title":"Abundance, distribution, and population trends of the iconic Hawaiian Honeycreeper, the ʻIʻiwi (Vestiaria coccinea) throughout the Hawaiian Islands","docAbstract":"Naturalists in the 1800s described the ʻIʻiwi (Vestiaria coccinea) as one of the most abundant forest birds, detected in forested areas from sea level to tree line across all the major Hawaiian Islands. However, in the late 1800s, ʻIʻiwi began to disappear from low elevation forests, and by the mid-1900s, the species was largely absent from low- and mid-elevation areas. Today, ʻIʻiwi are restricted to high-elevation forests on the islands of Hawaiʻi, east Maui, and Kauaʻi, with a few birds apparently persisting on Oʻahu, Molokaʻi, and west Maui. ʻIʻiwi are highly vulnerable to introduced disease, and the prevalence of avian malaria in low and mid-elevations is believed to be the cause of ʻIʻiwi being restricted to high elevations where temperatures are too cold for the development of the disease and its mosquito vector. With global warming, it is feared that the disease will move quickly into the high-elevation forests where the last ʻIʻiwi reside, threatening their viability. The U.S. Fish and Wildlife Service was petitioned to list the ʻIʻiwi as an Endangered Species in 2010, and this report provides a comprehensive review of the abundance, distribution, and trends using historical survey data as well as the most recently available survey information (up to 2012). We estimate the total population size of ‘I‘iwi at 550,972–659,864 (mean = 605,418) individuals. Of these, 90 percent are on the island of Hawaiʻi, followed by east Maui (about 10 percent), with less than 1 percent on Kauaʻi. ʻIʻiwi population trends vary across the islands. ʻIʻiwi population in Kauaʻi has experienced sharp declines, with a projected trend of 92 percent decline over a 25 year period based on the 2000–2012 surveys. On East Maui, the northeastern region has experienced declines (34 percent over a 25 year period), while the southeastern region has been stable to moderately increasing. On the island of Hawaiʻi, population trends are mixed. On the windward side, populations are largely declining, although the northern section (Hakalau Forest) has stable populations. On the leeward side, results suggest a strongly increasing population, with estimates of as much as a 147 percent increase over a 25 year period from the Puʻu Waʻawaʻa region. However, it is unclear how much these results from the leeward side of Hawaiʻi show a population trend contrary to population trends in all other areas or are an artifact of a sparsely sampled area. Trends by elevation suggest a large decrease in numbers of ʻIʻiwi at elevations below 1,200 meters on Kauaʻi and northeast Maui. Low elevation ʻIʻiwi populations also appear to have decreased in other regions, although low-elevation areas are not surveyed as often as other areas because of their lack of native forest birds. An exception to this pattern was the lower portions of the Hakalau Forest National Wildlife Refuge Kona Unit in the central leeward part of the island of Hawaiʻi, where populations appeared stable at the lower elevations. Based on the most recent surveys (up to 2012), approximately 50 percent of ʻIʻiwi live in a narrow, 500-meter band at elevations of 1,200–1,700 meters, suggesting that ʻIʻiwi are vulnerable to future shifts in climate.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131150","collaboration":"Prepared in cooperation with Hawai‘i Cooperative Studies Unit, University of Hawaiʻi Hilo","usgsCitation":"Paxton, E.H., Gorresen, P.M., and Camp, R., 2013, Abundance, distribution, and population trends of the iconic Hawaiian Honeycreeper, the ʻIʻiwi (Vestiaria coccinea) throughout the Hawaiian Islands: U.S. Geological Survey Open-File Report 2013-1150, iv, 59 p., https://doi.org/10.3133/ofr20131150.","productDescription":"iv, 59 p.","numberOfPages":"63","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":275486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131150.jpg"},{"id":275484,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1150/"},{"id":275485,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1150/pdf/ofr20131150.pdf"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.31,18.91 ], [ -178.31,28.4 ], [ -154.81,28.4 ], [ -154.81,18.91 ], [ -178.31,18.91 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f4ddd1e4b0838938b2802b","contributors":{"authors":[{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":481552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":37020,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":481554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":481553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047260,"text":"ofr20131129 - 2013 - Analytical approaches used in stream benthic macroinvertebrate biomonitoring programs of State agencies in the United States","interactions":[],"lastModifiedDate":"2013-07-27T11:15:32","indexId":"ofr20131129","displayToPublicDate":"2013-07-27T11:08:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1129","title":"Analytical approaches used in stream benthic macroinvertebrate biomonitoring programs of State agencies in the United States","docAbstract":"Biomonitoring programs based on benthic macroinvertebrates are well-established worldwide. Their value, however, depends on the appropriateness of the analytical techniques used. All United States State, benthic macroinvertebrate biomonitoring programs were surveyed regarding the purposes of their programs, quality-assurance and quality-control procedures used, habitat and water-chemistry data collected, treatment of macroinvertebrate data prior to analysis, statistical methods used, and data-storage considerations. State regulatory mandates (59 percent of programs), biotic index development (17 percent), and Federal requirements (15 percent) were the most frequently reported purposes of State programs, with the specific tasks of satisfying the requirements for 305b/303d reports (89 percent), establishment and monitoring of total maximum daily loads, and developing biocriteria being the purposes most often mentioned. Most states establish reference sites (81 percent), but classify them using State-specific methods. The most often used technique for determining the appropriateness of a reference site was Best Professional Judgment (86 percent of these states). Macroinvertebrate samples are almost always collected by using a D-frame net, and duplicate samples are collected from approximately 10 percent of sites for quality assurance and quality control purposes. Most programs have macroinvertebrate samples processed by contractors (53 percent) and have identifications confirmed by a second taxonomist (85 percent). All States collect habitat data, with most using the Rapid Bioassessment Protocol visual-assessment approach, which requires ~1 h/site. Dissolved oxygen, pH, and conductivity are measured in more than 90 percent of programs. Wide variation exists in which taxa are excluded from analyses and the level of taxonomic resolution used. Species traits, such as functional feeding groups, are commonly used (96 percent), as are tolerance values for organic pollution (87 percent). Less often used are tolerance values for metals (28 percent). Benthic data are infrequently modified (34 percent) prior to analysis. Fixed-count subsampling is used widely (83 percent), with the number of organisms sorted ranging from 100 to 600 specimens. Most programs include a step during sample processing to acquire rare taxa (79 percent). Programs calculate from 2 to more than100 different metrics (mean 20), and most formulate a multimetric index (87 percent). Eleven of the 112 metrics reported represent 50 percent of all metrics considered to be useful, and most of these are based on richness or percent composition. Biotic indices and tolerance metrics are most oftenused in the eastern U.S., and functional and habitat-type metrics are most often used in the western U.S. Sixty-nine percent of programs analyze their data in-house, typically performing correlations and regressions, and few use any form of data transformation (34 percent). Fifty-one percent of the programs use multivariate analyses, typically non-metric multi-dimensional scaling. All programs have electronic data storage. Most programs use the Integrated Taxonomic Information System (75 percent) for nomenclature and to update historical data (78 percent). State procedures represent a diversity of biomonitoring approaches which likely compromises comparability among programs. A national-state consensus is needed for: (1) developing methods for the identification of reference conditions and reference sites, (2) standardization in determining and reporting species richness, (3) testing and documenting both the theoretical and mechanistic basis of often-used metrics, (4) development of properly replicated point-source study designs, and (5) curation of benthic macroinvertebrate data, including reference and voucher collections, for successful evaluation of future environmental changes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131129","usgsCitation":"Carter, J.L., and Resh, V.H., 2013, Analytical approaches used in stream benthic macroinvertebrate biomonitoring programs of State agencies in the United States: U.S. Geological Survey Open-File Report 2013-1129, vi, 50 p., https://doi.org/10.3133/ofr20131129.","productDescription":"vi, 50 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":275483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131129.png"},{"id":275481,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1129/"},{"id":275482,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1129/pdf/ofr20131129.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f4ddd9e4b0838938b2802f","contributors":{"authors":[{"text":"Carter, James L. 0000-0002-0104-9776 jlcarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":3278,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"jlcarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Resh, Vincent H.","contributorId":12169,"corporation":false,"usgs":true,"family":"Resh","given":"Vincent","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":481551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046824,"text":"70046824 - 2013 - TerraSAR-X interferometry reveals small-scale deformation associated with the summit eruption of Kilauea Volcano, Hawai‘i","interactions":[],"lastModifiedDate":"2018-10-30T08:58:34","indexId":"70046824","displayToPublicDate":"2013-07-26T15:17:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"TerraSAR-X interferometry reveals small-scale deformation associated with the summit eruption of Kilauea Volcano, Hawai‘i","docAbstract":"On 19 March 2008, a small explosive eruption at the summit of Kīlauea Volcano, Hawai‘i, heralded the formation of a new vent along the east wall of Halema‘uma‘u Crater. In the ensuing years, the vent widened due to collapses of the unstable rim and conduit wall; some collapses impacted an actively circulating lava pond and resulted in small explosive events. We used synthetic aperture radar data collected by the TerraSAR-X satellite, a joint venture between the German Aerospace Center (DLR) and EADS Astrium, to identify and analyze small-scale surface deformation around the new vent during 2008-2012. Lidar data were used to construct a digital elevation model to correct for topographic phase, allowing us to generate differential interferograms with a spatial resolution of about 3 m in Kīlauea's summit area. These interferograms reveal subsidence within about 100 m of the rim of the vent. Small baseline subset time series analysis suggests that the subsidence rate is not constant and, over time, may provide an indication of vent stability and potential for rim and wall collapse -- information with obvious hazard implications. The deformation is not currently detectable by other space- or ground-based techniques.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/grl.50286","usgsCitation":"Richter, N., Poland, M., and Lundgren, P.R., 2013, TerraSAR-X interferometry reveals small-scale deformation associated with the summit eruption of Kilauea Volcano, Hawai‘i: Geophysical Research Letters, v. 40, no. 7, p. 1279-1283, https://doi.org/10.1002/grl.50286.","productDescription":"5 p.","startPage":"1279","endPage":"1283","numberOfPages":"5","ipdsId":"IP-042377","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":275474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275473,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50286"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.5,19.166667 ], [ -155.5,19.5 ], [ -154.833333,19.5 ], [ -154.833333,19.166667 ], [ -155.5,19.166667 ] ] ] } } ] }","volume":"40","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-04-12","publicationStatus":"PW","scienceBaseUri":"51f38c5fe4b0a32220222f47","contributors":{"authors":[{"text":"Richter, Nichole","contributorId":40495,"corporation":false,"usgs":true,"family":"Richter","given":"Nichole","email":"","affiliations":[],"preferred":false,"id":480370,"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":635,"corporation":false,"usgs":true,"family":"Poland","given":"Michael P.","email":"mpoland@usgs.gov","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":480369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundgren, Paul R.","contributorId":68199,"corporation":false,"usgs":true,"family":"Lundgren","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":480371,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046957,"text":"70046957 - 2013 - Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS","interactions":[],"lastModifiedDate":"2013-07-26T14:32:35","indexId":"70046957","displayToPublicDate":"2013-07-26T14:24:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS","docAbstract":"1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. \n