This article synthesizes information from over a six-decade period of studies of White-tailed Deer (Odocoileus virginianus) use of a winter yard and subject to Gray Wolf (Canis lupus) predation in northeastern Minnesota. It also adds spring migration data from 35 adult female deer and fawns studied there during 1998, 1999, 2001, 2014, and 2017. Twenty-nine of these deer migrated in spring a mean distance of 29 km (SE = 4), a maximum distance of 78 km, and at a mean bearing of 83° (SE = 12; range 21–348). These findings are similar to those from 49 deer (both sexes) from the same yard studied during 1974–1984, that migrated a mean distance of 25 km (SE = 1.8) and a mean bearing of 77° ± 4 SE. Between the two periods, the wolf population fluctuated considerably, the winter range of deer in the area where these deer spent summer greatly diminished, and both derechos and fires disturbed the habitat. This study attests to the selective advantage of the migratory tradition of deer in this yard.
Batrachochytrium dendrobatidis (Bd), a fungal pathogen that causes amphibian chytridiomycosis, has been implicated in population declines globally. To better understand how Bd affects survival and how threats vary spatially and temporally, we conducted long-term (range: 9–13 yrs) capture-recapture studies of boreal toads (Anaxyrus boreas) from three similar communities in western Montana. We also estimated temporal and spatial variation in population-level Bd prevalence among populations and the potential role of co-occurring Columbia spotted frogs (Rana luteiventris) in driving infection dynamics. Hierarchical models that accounted for detection uncertainty revealed Bd reduced apparent survival in one population that declined, was unassociated with survival in one stationary population, and was associated with increased survival in one population that is near extirpation. Despite different effects of Bd on hosts, pathogen prevalence was similar and synchronous across the populations separated by 111–176 km. Variation in Bd prevalence was driven partly by seasonal temperatures, but opposite the direction expected. Bd prevalence also decreased sharply over time across all populations, unrelated to trends in temperature, boreal toad survival, or infection dynamics of co-occurring Columbia spotted frogs. Toad Bd prevalence increased when frog abundance was high, consistent with an amplification effect. However, Bd prevalence of toads decreased as Bd prevalence of spotted frogs increased, consistent with a dilution effect. Our results reveal surprising variation in responses to Bd and show pathogen prevalence is not predictive of survival or population risk, and they illustrate the complexity in understanding disease dynamics across multiple populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.108373","usgsCitation":"Hossack, B.R., Russell, R., and McCaffery, R.M., 2019, Contrasting demographic responses of toad populations to regionally synchronous pathogen (Batrachochytrium dendrobatidis) dynamics: Biological Conservation, v. 241, 108373, 10 p.; Data release, https://doi.org/10.1016/j.biocon.2019.108373.","productDescription":"108373, 10 p.; Data release","ipdsId":"IP-106168","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":372208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418324,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JMV5BT","text":"USGS data release","description":"USGS data release","linkHelpText":"Boreal toad survival data in relation to Bd status and community composition"}],"country":"United States","otherGeospatial":"Western Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.70800781249999,\n 47.45780853075031\n ],\n [\n -114.52148437499999,\n 46.5286346952717\n ],\n [\n -114.60937499999999,\n 45.521743896993634\n ],\n [\n -113.8623046875,\n 45.55252525134013\n ],\n [\n -112.8955078125,\n 44.37098696297173\n ],\n [\n -111.1376953125,\n 44.5278427984555\n ],\n [\n -110.9619140625,\n 45.058001435398275\n ],\n [\n -107.9296875,\n 44.933696389694674\n ],\n [\n -107.92968749999999,\n 48.980216985374966\n ],\n [\n -116.36718749999997,\n 48.980216985374966\n ],\n [\n -115.70800781249999,\n 47.45780853075031\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"241","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":781971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":781972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCaffery, Rebecca M. 0000-0002-0396-0387","orcid":"https://orcid.org/0000-0002-0396-0387","contributorId":211539,"corporation":false,"usgs":true,"family":"McCaffery","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":781973,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208239,"text":"70208239 - 2019 - Integrating the sociology of space with geospatial semantics relation properties for data graphs","interactions":[],"lastModifiedDate":"2024-09-16T14:21:18.545056","indexId":"70208239","displayToPublicDate":"2019-12-31T07:41:44","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrating the sociology of space with geospatial semantics relation properties for data graphs","docAbstract":"This research posits that socially constructed spatial relations address concepts of interactions instead of intersections, human/tool agents instead of physical processes, and broader ranges of geographical outcomes. The hypothesis is that social space can be represented by using patterns of logic relations between sets of entities. The data corpus of spatial relations was extracted from geographic term definitions. The relations were further analyzed as primitives using Case Grammar Matrix models. These findings are being related to Web Ontology Language (OWL) properties. This approach allows an extensive range of natural language terms to instantiate ontology sub-types, while supporting inferences to study their logical implications.","language":"English","publisher":"University of California-Santa Barbara","usgsCitation":"Varanka, D.E., 2019, Integrating the sociology of space with geospatial semantics relation properties for data graphs, 3 p.","productDescription":"3 p.","ipdsId":"IP-111976","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":371991,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":781130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70212988,"text":"70212988 - 2019 - Pedogenic evolution on the arid Bishop Creek moraines, eastern Sierra Nevada, California","interactions":[],"lastModifiedDate":"2020-09-08T14:00:19.599991","indexId":"70212988","displayToPublicDate":"2019-12-31T07:39:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Pedogenic evolution on the arid Bishop Creek moraines, eastern Sierra Nevada, California","docAbstract":"Soil chronosequences on alpine moraine complexes have been used to help unravel the glacial histories of the eastern Sierra Nevada. The moraine sequence along Bishop Creek includes well-preserved moraines that have been previously dated using cosmogenic 36Cl surface exposure ages. The goal of this study was to interpret pedogenesis within a soil geomorphic context on these quantitatively dated moraines. Soil development, surface clast cover, and moraine morphology were studied on seven of the moraines, ranging in age from 15 to 170 ka. Older moraines had gentler slopes, broader crests, and decreased surface rock cover. Soils showed weak development across the chronosequence of moraines. Pedogenesis involved slight increases in clay, the formation of clay lamellae, development of a vesicular horizon in a surface layer of aeolian dust, and weathering of surface and subsurface granitic clasts. Soil reddening and structure development were minimal. Soil formation was likely inhibited by the arid to semi-arid climate and intermittent wind and water erosion during the time span of the chronosequence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2019.104222","usgsCitation":"Rossi, A., Graham, R., and Kendrick, K.J., 2019, Pedogenic evolution on the arid Bishop Creek moraines, eastern Sierra Nevada, California: Catena, v. 183, 104222, 14 p., https://doi.org/10.1016/j.catena.2019.104222.","productDescription":"104222, 14 p.","ipdsId":"IP-102151","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":378160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.87207031250001,\n 37.69251435532741\n ],\n [\n -118.49304199218749,\n 37.69251435532741\n ],\n [\n -118.49304199218749,\n 37.84015683604136\n ],\n [\n -118.87207031250001,\n 37.84015683604136\n ],\n [\n -118.87207031250001,\n 37.69251435532741\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rossi, Annie 0000-0001-8955-0065","orcid":"https://orcid.org/0000-0001-8955-0065","contributorId":239863,"corporation":false,"usgs":false,"family":"Rossi","given":"Annie","email":"","affiliations":[{"id":48012,"text":"U.S.D.A. - NRCS","active":true,"usgs":false}],"preferred":false,"id":797908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Robert","contributorId":239864,"corporation":false,"usgs":false,"family":"Graham","given":"Robert","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":797909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendrick, Katherine J. 0000-0002-9839-6861","orcid":"https://orcid.org/0000-0002-9839-6861","contributorId":207907,"corporation":false,"usgs":true,"family":"Kendrick","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797910,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215595,"text":"70215595 - 2019 - Predation strategies of larval clownfish capturing evasive copepod prey","interactions":[],"lastModifiedDate":"2020-10-26T12:28:15.695811","indexId":"70215595","displayToPublicDate":"2019-12-31T07:24:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Predation strategies of larval clownfish capturing evasive copepod prey","docAbstract":"Fish larvae depend on finding and capturing enough prey for rapid growth during the planktonic phase. The diet of many fish larvae is dominated by copepods, small crustaceans that are highly sensitive to hydrodynamic disturbances and possess strong escape responses. We examined how fish larvae with immature jaws, musculature and fins capture such evasive prey. The kinematics of feeding attempts by larval clownfish Amphiprion ocellaris on 3 developmental stages of copepod Bestiolina similis were investigated using high-speed videography. A stealthy approach brought the fish larva within ~1 mm of the copepod; shortest distances were observed in early larvae (1 to 5 d post-hatch [dph]) attacking immature copepods. Peak speeds during strikes increased with fish age and copepod developmental stage (150 to 250 mm s-1), with time to capture <8 ms on average. Most successful captures (70%) were of copepods that failed to initiate an escape response during the strike. If a copepod initiated an escape, capture success decreased to ~50% for nauplii and copepodites and 25% for adults. Adult copepods were more likely to attempt an escape response than copepodites or nauplii. Prey stage and the interaction between strike distance and speed were the parameters that best fit a logistic regression model to the observed captures and escapes. The successful switch to larger and more evasive copepod prey by A. ocellaris larvae did not occur until 7 dph and coincided with ontogenetic changes (post-flexion) and a predatory strategy that included shorter approach phases and greater strike speeds.
","language":"English","publisher":"Inter Research","doi":"10.3354/meps12888","usgsCitation":"Robinson, H.E., Strickler, J.R., Henderson, M., Hartline, D.K., and Lenz, P.H., 2019, Predation strategies of larval clownfish capturing evasive copepod prey: Marine Ecology Progress Series, v. 614, p. 125-146, https://doi.org/10.3354/meps12888.","productDescription":"22 p.","startPage":"125","endPage":"146","ipdsId":"IP-102113","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"614","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, H. Eve","contributorId":243964,"corporation":false,"usgs":false,"family":"Robinson","given":"H.","email":"","middleInitial":"Eve","affiliations":[{"id":48777,"text":"Pacific Biosciences Research Center, HI","active":true,"usgs":false}],"preferred":false,"id":802894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strickler, J. Rudi","contributorId":243965,"corporation":false,"usgs":false,"family":"Strickler","given":"J.","email":"","middleInitial":"Rudi","affiliations":[{"id":48778,"text":"University of Wisconsin-Milwaukee, WI","active":true,"usgs":false}],"preferred":false,"id":802895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":802896,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartline, Daniel K.","contributorId":243966,"corporation":false,"usgs":false,"family":"Hartline","given":"Daniel","email":"","middleInitial":"K.","affiliations":[{"id":48777,"text":"Pacific Biosciences Research Center, HI","active":true,"usgs":false}],"preferred":false,"id":802897,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lenz, Petra H.","contributorId":243967,"corporation":false,"usgs":false,"family":"Lenz","given":"Petra","email":"","middleInitial":"H.","affiliations":[{"id":48777,"text":"Pacific Biosciences Research Center, HI","active":true,"usgs":false}],"preferred":false,"id":802898,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206051,"text":"sir20195115 - 2019 - A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention","interactions":[],"lastModifiedDate":"2022-04-25T18:38:51.233329","indexId":"sir20195115","displayToPublicDate":"2019-12-31T07:20:00","publicationYear":"2019","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":"2019-5115","displayTitle":"A Probabilistic Assessment Methodology for Carbon Dioxide Enhanced Oil Recovery and Associated Carbon Dioxide Retention","title":"A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention","docAbstract":"The U.S. Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of the potential volume of hydrocarbons recoverable by injection of carbon dioxide (CO2) into known oil reservoirs with historical production. The implementation of CO2 enhanced oil recovery (CO2-EOR) techniques could increase the U.S. recoverable hydrocarbon resource base. Use of anthropogenic CO2 in the CO2-EOR process could reduce the amount of CO2 released to the atmosphere by allowing a percentage of the injected CO2 to remain in reservoir pore space once occupied by produced oil and water or by CO2 dissolution in oil and water in the reservoir.
The USGS has developed a new methodology for the national assessment of technically recoverable oil resources that may be produced by using current CO2-EOR technologies. The methodology relies on a proprietary reservoir-level database, the comprehensive resource database (CRD). The CRD incorporates commercially available geologic and engineering data, and USGS-defined play averages or province averages of reservoir data were used to populate incomplete records. Values from the CRD are used to estimate the original oil in place (OOIP) for each reservoir. The inputs are reviewed by USGS geologists, particularly when play or province averages have been used. Monte Carlo simulation is used to produce a numerical probability distribution for the OOIP for each reservoir, with the mean defined as the value of the OOIP in the CRD. A reservoir model (CO2 Prophet, developed for the U.S. Department of Energy by Texaco, Inc.) is used to determine the incremental recovery factors for oil during the CO2-EOR process, on an individual reservoir basis. The model is also used to estimate the volume of CO2 remaining in the reservoir after the CO2-EOR process is complete. Empirical decline curve analysis and comparison with data from published papers and reports on CO2-EOR projects are utilized to substantiate the simulation results. Numerical distributions of recovery factors are prepared for variations in the reservoir lithology (clastic or carbonate). The distribution of incremental oil is computed by multiplying the appropriate probability distribution of recovery factors by the individual reservoir distribution of the OOIP. A way to estimate the CO2 remaining in the reservoir after the completion of the CO2-EOR process is also included in the methodology.
Assessment results will be aggregated to play, petroleum province, regional, and national scales. This assessment methodology has been tested on the Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian play in the Permian Basin Province in Texas; the play consists of 27 reservoirs having at least 2 billion barrels of OOIP that are amenable to the CO2-EOR process. The play was selected as a test case because CO2-EOR production data and published reports are available for several reservoirs within the play. Preliminary estimates of oil recoverable by implementation of miscible CO2-EOR are comparable to those reported in the literature and obtained by reservoir decline curve analysis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195115","usgsCitation":"Warwick, P.D., Attanasi, E.D., Olea, R.A., Blondes, M.S., Freeman, P.A., Brennan, S.T., Merrill, M.D., Verma, M.K., Karacan, C.Ö., Shelton, J.L., Lohr, C.D., Jahediesfanjani, H., and Roueché, J.N., 2019, A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention: U.S. Geological Survey Scientific Investigations Report 2019–5115, 51 p., https://doi.org/10.3133/sir20195115.","productDescription":"x, 51 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069832","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":399600,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109570.htm"},{"id":370863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5115/sir20195115.pdf","text":"Report","size":"8.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5115"},{"id":370862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5115/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
Laboratory experiments that simulate lava flows have been in use by volcanologists for many years. The behavior of flows in the lab, where “eruption” parameters, material properties, and environmental settings are tightly controlled, provides insight into the influence of various factors on flow evolution. A second benefit of laboratory lava flows is to provide a set of observations with which numerical models of flow emplacement can be tested. Models of lava flow emplacement vary in mathematical approach, physical assumptions, and computational cost. Nonetheless, all models require thorough testing and evaluation, and laboratory experiments produce an excellent test for models.
This paper provides a primer on modern analog laboratory lava flow experiments. It reviews scaling con- siderations and provides quantitative information meant to guide future experimentalists in designing their experiments to be relevant to natural processes. Traditional and novel laboratory techniques are described, including a discussion of current limitations. New insights from recent experiments highlight the impact of topographic conditions and highlight the importance of considering bed roughness, major obstacles, and slope breaks. The influence of episodic or non-uniform effusion rate is demonstrated through recent experi- mental works. Lastly, the paper discusses several open questions about lava flow emplacement and the ways in which future improvements in experimental methods, such as the ability to utilize three-phase suspensions and materials with complex rheologies and to image the interior of flows could help answer these.
","language":"English","publisher":"National Institute of Geophysics and Volcanology (INGV)","doi":"10.4401/ag-7843","usgsCitation":"Lev, E., Rumpf, M.E., and Dietterich, H., 2019, Analog experiments of lava flow emplacement: Annals of Geophysics, v. 62, no. 2, VO225, 21 p., https://doi.org/10.4401/ag-7843.","productDescription":"VO225, 21 p.","ipdsId":"IP-103534","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":458876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4401/ag-7843","text":"Publisher Index Page"},{"id":377875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":797292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumpf, M. Elise 0000-0001-7906-2623","orcid":"https://orcid.org/0000-0001-7906-2623","contributorId":217992,"corporation":false,"usgs":true,"family":"Rumpf","given":"M.","email":"","middleInitial":"Elise","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":797293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208836,"text":"70208836 - 2019 - Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","interactions":[],"lastModifiedDate":"2021-12-10T15:22:19.1894","indexId":"70208836","displayToPublicDate":"2019-12-31T06:51:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5938,"text":"Chelonian Research Monographs","printIssn":"1088-7105","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","title":"Gopherus agassizii (Cooper 1861) – Agassiz’s Desert Tortoise, Mojave Desert Tortoise","docAbstract":"In keeping with our national mission, the USGS in Alaska provides timely and objective scientific information to help the Nation address issues and solve problems in five major topical areas (listed alphabetically):
The USGS in Alaska engages about 400 scientists and support staff working in three major science centers, Cooperative Research Units, and USGS centers outside Alaska, with a combined annual science budget of about $60 million. In just the last 5 years, the USGS in Alaska has produced scientific benefits resulting from more than 1,000 publications and about 250 technical reports. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.er.usgs.gov/search?q=Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191141","usgsCitation":"Williams, D.M., and Powers, E.M., eds., 2019, U.S. Geological Survey — Department of the Interior Region 11, Alaska—2019 annual science report: U.S. Geological Survey Open-File Report 2019–1141, 79 p., https://doi.org/10.3133/ofr20191141.","productDescription":"xi, 79 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-111992","costCenters":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"links":[{"id":399429,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109573.htm"},{"id":370887,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1141/ofr20191141.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Beach erosion is a persistent problem along most open-ocean shores of the United States. Along the Arctic coast of Alaska, coastal erosion is widespread and threatens communities, defense and energy-related infrastructure, and coastal habitat. As coastal populations continue to expand and infrastructure and habitat are increasingly threatened by erosion, there is increased demand for accurate information regarding past and present trends and rates of shoreline movement.
Shoreline change was evaluated by comparing three to four historical shoreline positions derived from 1950s-era topographic surveys and black and white aerial photography, 1980s-era color-infrared Alaska High-Altitude Aerial Photography, 2003 natural color aerial photography, and 2010s-era natural color aerial photography. Long-term (1950s–2010s) and short-term (1980s–2010s) shoreline change rates were calculated using linear-regression and end-point methods, respectively, at transects spaced approximately every 50 meters along both the mainland and barrier island coasts.
Shoreline change rates calculated on more than 24,000 individual transects indicate that between 1948 and 2016 the northern coast of Alaska between Icy Cape and Cape Prince of Wales was slightly erosional, with 68 percent of the total transects showing shoreline retreat over the long term and 63 percent over the short term. However, only 9 percent of the total transects showed shoreline retreat greater than 1 meter per year (m/yr) over the long and short term, respectively. Mean rates of shoreline change of −0.2±0.1 and −0.2±0.3 m/yr, were calculated for the long and short term, respectively. Many rates measured were near the limit of our shoreline change uncertainty estimates. Erosion and accretion rates on individual transects ranged from −8.3 to +9.6 m/yr over the long term and −16.0 to +20.0 m/yr over the short-term analysis periods. The highest rates of erosion and accretion were associated with the formation and migration of inlets along barrier island coasts. The highest erosional rates of change were measured in the southern part of the study area between Sullivan Lake and Cape Prince of Wales. The highest accretional rates of change were measured in the northern part of the study area on the open-ocean coast of barrier islands fronting Kasegaluk Lagoon.
Open-ocean exposed shorelines compose 85 percent of all transects and 70 percent were erosional over the long term. Sheltered mainland-lagoon shorelines compose 15 percent of all transects in the study area and 58 percent were erosional over the long term. Although mean shoreline change rates were quite low along all coasts, exposed shorelines retreated at twice the rate (−0.2±0.1 m/yr) of sheltered shorelines (−0.1±0.1 m/yr). Barrier shoreline transects (includes barrier islands, spits, and beaches) compose 49 percent of the total transects and 56 percent of all exposed shoreline transects. Mean shoreline change rates on exposed barrier shorelines were only slightly greater than exposed mainland shorelines (−0.3±0.1 and −0.2±0.1 m/yr, respectively). Mean shoreline change rates on sheltered barrier shorelines were similar to sheltered mainland shorelines (−0.1±0.3 m/yr).
In contrast to the majority of the Nation’s shorelines, for all but three months of the year (July–September), the north coast of Alaska has historically been protected by landfast sea ice from processes such as waves, winds, and currents that typically drive coastal change on beaches in more temperate regions of the world. Projected and observed increases in periods of sea-ice-free conditions, as sea ice melts earlier and forms later in the year, particularly in the autumn, when large storms are more common in the Arctic, suggest that Arctic coasts will be more vulnerable to storm surge and wave energy, potentially resulting in accelerated shoreline erosion and terrestrial habitat loss in the future. Increases in air and sea water temperatures may also increase erosion of the ice-rich, coastal permafrost bluffs present along much of Alaska’s Arctic coast. More frequent shoreline change data collection and analysis in this rapidly changing environment should be considered in order to evaluate shoreline change trends in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191146","usgsCitation":"Gibbs, A.E., Snyder, A.G., and Richmond, B.M., 2019, National assessment of shoreline change — Historical shoreline change along the north coast of Alaska, Icy Cape to Cape Prince of Wales: U.S. Geological Survey Open-File Report 2019–1146, 52 p., https://doi.org/10.3133/ofr20191146.","productDescription":"Report: vi, 52 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-111408","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399433,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109572.htm"},{"id":370888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1146/coverthb.jpg"},{"id":370889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1146/ofr20191146.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1146"},{"id":370890,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1S1PV","linkHelpText":"National assessment of shoreline change—A GIS compilation of updated vector shorelines and associated shoreline change data for the north coast of Alaska, Icy Cape to Cape Prince of Wales"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.1194,\n 65.5739\n ],\n [\n -160.9839,\n 65.5739\n ],\n [\n -160.9839,\n 70.3322\n ],\n [\n -168.1194,\n 70.3322\n ],\n [\n -168.1194,\n 65.5739\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Stream stability, flood frequency, and streambed scour potential were evaluated at 20 Alaskan river- and stream-spanning bridges lacking a quantitative scour analysis or having unknown foundation details. Three of the bridges had been assessed shortly before the study described in this report but were re-assessed using different methods or data. Channel instability related to mining may affect scour at one site, while channel instability related to flow distribution changes can be seen at one site. One bridge was closed because of abutment scour prior to the study. Otherwise, channels generally showed stable bed elevations.
Contraction and abutment scour were calculated for all 20 bridges, and pier scour was calculated for the 2 bridges that had piers. Vertical contraction (pressure flow) scour was calculated for one site at which the modeled water surface was higher than the superstructure of the bridge. Hydraulic variables for the scour calculations were derived from one-dimensional and two-dimensional hydraulic models of the 1- and 0.2-percent annual exceedance probability floods (also known as the 100- and 500-year floods, respectively). Scour also was calculated for large recorded floods at two sites.
At many sites, overflow of road approaches relieves the bridge during floods and lessens the potential for scour. Two-dimensional hydraulic models are superior to one-dimensional hydraulic models at distributing flow between bridges, road approaches, and floodplains, and therefore likely produce more reasonable scour values at sites with substantial floodplain flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195110","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities","usgsCitation":"Beebee, R.A., Dworsky, K.L., and Knopp, S.J., 2019, Streambed scour evaluations and conditions at selected bridge Sites in Alaska, 2016–17 (version 1.1, April 2023): U.S. Geological Survey Scientific Investigations Report 2019-5110, 32 p., https://doi.org/10.3133/sir20195110.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099321","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":399597,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109571.htm"},{"id":370872,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5110/coverthb2.jpg"},{"id":370873,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5110"},{"id":415671,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5110/sir20195110_RevisionHistory.txt","description":"SIR 2019-5110 Version History"},{"id":370874,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LUTFHZ","linkHelpText":"Tabular input/output data and model files for 19 hydraulic models for streambed scour evaluations at selected bridge sites, Alaska, 2016–17"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.41259765625,\n 59.01794033995248\n ],\n [\n -144.77783203125,\n 59.01794033995248\n ],\n [\n -144.77783203125,\n 64.97006438589436\n ],\n [\n -155.41259765625,\n 64.97006438589436\n ],\n [\n -155.41259765625,\n 59.01794033995248\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: April 2023; Version 1.0: December 2019","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Throughout the western United States, efforts are underway to better understand and preserve migration and movement corridors for mule deer and other big game and to minimize the impacts of development and other land-use change on populations. San Diego County is home to a unique non-migratory subspecies of mule deer, the Southern mule deer (Odocoileus hemionus fuliginatus; herein referred to as “mule deer”). Because it is the only large herbivorous mammal in San Diego, connectivity among mule deer groups is an important indicator of functional connectivity throughout San Diego County urban preserves and has therefore been monitored within central and eastern San Diego County using DNA fingerprinting since 2005. To continue this effort and to assess genetic connectivity in north San Diego County (herein “North County”), we genotyped scat samples from preserves in the area and tissue samples from Marine Corps Base Camp Pendleton (MCBCP). We used non-invasive capture/recapture analyses and pedigree analyses for assessing short-term movement and population clustering analyses to assess gene flow in North County. Additionally, we performed similar analyses on the combined San Diego County dataset, which was composed of the North County dataset collected for this study and a previously collected dataset from central and eastern San Diego County. Using recapture data, we found multiple instances of mule deer crossing roads in urban North County preserves, with several of these events occurring in areas where there are underpasses and culverts known to be used by mule deer. Corroborating previous studies in the region and statewide, pedigree and population structure analyses support the presence of two genetic clusters for mule deer in San Diego County—the “Coastal” and “Inland/Mountain” clusters. Low estimates of effective population size, especially in the Coastal cluster, suggest that to further understand potential vulnerabilities of mule deer in this region, it is important to continue to monitor connectivity, in particular, at the boundary between these two clusters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191138","usgsCitation":"Mitelberg, A., Smith, J.G., and Vandergast, A.G., 2019, DNA Fingerprinting of Southern mule deer (Odocoileus hemionus fuliginatus) in north San Diego County, California (2018–19): U.S. Geological Survey Open-File Report 2019–1138, 25 p., https://doi.org/10.3133/ofr20191138.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-112707","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437245,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YXWXA9","text":"USGS data release","linkHelpText":"Microsatellite Genetic Marker Genotypes from Southern Mule Deer (Odocoileus hemionus fuliginatus) Sampled in San Diego County, California"},{"id":370869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1138/ofr20191138.pdf","text":"Report","size":"31 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":370868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1138/coverthb.jpg"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.31201171875001,\n 32.713355353177555\n ],\n [\n -116.05957031249999,\n 32.713355353177555\n ],\n [\n -116.05957031249999,\n 33.25706340236547\n ],\n [\n -117.31201171875001,\n 33.25706340236547\n ],\n [\n -117.31201171875001,\n 32.713355353177555\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Investments in landscape-scale restoration and fuels management projects can protect publicly managed trusts, enhance public health and safety, and help to preserve the many environmental goods and services enjoyed by the public. These investments can also support jobs and generate business sales activities within nearby local economies. This report investigates how investments made by the Rio Grande Water Fund (RGWF) on wildfire risk reduction and source water protection projects in northern New Mexico and southern Colorado affect local economic activity. To implement these projects, the RGWF spent a total of $855,000 in 2018 on contractors located in the Western States regional economy. Including direct and secondary effects, these expenditures supported an estimated 22 jobs, $1,089,000 in labor income, $1,324,000 in value added, and $1,907,000 in economic output in the 17 Western States economy. The majority (73 percent or $623,000) of these expenditures were made by hiring local businesses operating within a 13-county region in northern New Mexico and southern Colorado that comprises the RGWF project area. Including direct and secondary effects, local expenditures support an estimate 15 jobs, $676,000 in labor income, $791,000 in value added, and $1,120,000 in economic output within the 13-county RGWF project area. These results demonstrate how investments in wildfire risk reduction and source water protection projects can support jobs and livelihoods, small businesses, and rural economies in the Mountain West.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191108","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Huber, C., Cullinane Thomas, C., Meldrum, J.R., Meier, R., and Bassett, S., 2019, Economic effects of wildfire risk reduction and source water protection projects in the Rio Grande River Basin in northern New Mexico and southern Colorado: U.S. Geological Survey Open-File Report 2019–1108, 8 p., https://doi.org/10.3133/ofr20191108.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":399416,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109581.htm"},{"id":370215,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1108/ofr20191108.pdf","text":"Report","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1108"},{"id":370214,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1108/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.6408,\n 34.2403\n ],\n [\n -103.6667,\n 34.2403\n ],\n [\n -103.6667,\n 37.3417\n ],\n [\n -107.6408,\n 37.3417\n ],\n [\n -107.6408,\n 34.2403\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Chief, Analysis and Prediction Branch
Integrated Modeling and Prediction Division
Water Resources Mission Area
U.S. Geological Survey, Mail Stop 415
12201 Sunrise Valley Drive
Reston, VA 20192
Otolith microanalysis is often used to assess population age structure and growth of fishes during their early stages. Shoal Bass Micropterus cataractae is a recently described species of conservation concern and little is known regarding factors affecting their recruitment. In 2004, Georgia Department of Natural Resources (GADNR) and the US National Park Service (NPS) stocked Shoal Bass marked with oxytetracycline (OTC) in the Chattahoochee River near Atlanta, Georgia in an effort to restore this population, creating known-age fish to examine the effect of environment on daily age accuracy. We obtained samples of stocked juvenile (<150 mm) Shoal Bass from standard monitoring that occurred approximately 30–60 days after stocking in the Chattahoochee River to 1) validate daily rings for estimating age, hatch dates, and growth rates for stocked age-0 Shoal Bass, and 2) evaluate the effect of habitat (location) on age bias. Shoal Bass otoliths were examined for OTC marks and daily rings were counted in reference to OTC marks to assess age estimation accuracy. Age estimation accuracy ranged from -2 to -25 days and was influenced by the environment where Shoal Bass were captured, with greater inaccuracy in colder water temperatures. Fish collected from locations with colder temperatures displayed closer spacing of daily rings, potentially leading to greater underestimation of age. Growth rates of stocked Shoal Bass, corrected for age estimation error, ranged from 0.5 mm/day to 0.8 mm/day. This study demonstrates the effect of environmental variability on age inaccuracy and subsequent interpretation of results. Incorporating methods to assess age estimation accuracy is needed to understand interspecific differences in recruitment among black bass species in the variety of natural and human-modified environments they inhabit.
Reliable estimates of life history parameters and their functional role in animal population trajectories are critical, yet often missing, components in conservation and management. We developed seasonal matrix population models of the Red-tailed Hawk Buteo jamaicensis jamaicensis in the upper and lower forests of the Luquillo Mountains, Puerto Rico, to describe the influence of early life stages (nestling and clutch survival) on population growth. Modelled populations exhibited positive discrete rates of growth in forests above 400 m (λ highlands = 1.05) and in forests below 400 m (λ lowlands = 1.27) of the Luquillo Mountains. Further, adult survival was the parameter with the highest proportional effect and direct contribution to growth of the population. Besides survival of adults, our results identified that nestling survival had the second greatest influence on λ, stressing the importance of this life stage for the population growth rate of Red-tailed Hawks in our study area. Seasonal matrices are not commonly used to describe population dynamics of birds. However, these may be a useful tool to analyse the influence of life stages in the annual cycle to better address conservation and management needs, especially for species inhabiting oceanic islands.
This report summarizes a national assessment of flowing waters conducted by the U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Project and addresses several pressing questions about the modification of natural flows in streams and rivers. The assessment is based on the integration, modeling, and synthesis of monitoring data collected by the USGS and the U.S. Environmental Protection Agency at more than 7,000 streams and rivers across the conterminous United States from 1980 to 2014. Key findings include the following. First, flow in many of the Nation’s streams and rivers is different from what it would be under natural conditions. In particular, low flows are more frequent, are of shorter duration, and vary less from one year to the next than they would naturally. In addition, high flows have been reduced in magnitude, are of shorter duration, are less frequent, and vary less from one year to the next than they would naturally. Other characteristics of natural flows also have been modified. Second, over the last 60 years (1955–2014), climatic trends have caused a change of 50 percent or more in one or more streamflow attributes at two-thirds of climate-sensitive streamgaging sites. However, these climate-induced changes have been less influential on streamflow modification than have land and water-management practices. Third, in every region assessed, streamflow modification was associated with reduced ecological health, as indicated by two biological communities—invertebrates and fish. Biological communities were increasingly likely to be impaired (defined as having lost a statistically significant number of species) in streams with flows most different from natural conditions. Finally, several case studies are presented that illustrate viable management strategies for balancing the water needs of people and ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1461","collaboration":"National Water-Quality ProgramNational Water-Quality Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192