{"pageNumber":"928","pageRowStart":"23175","pageSize":"25","recordCount":184617,"records":[{"id":70193894,"text":"70193894 - 2017 - Management of arthropod pathogen vectors in North America: Minimizing adverse effects on pollinators","interactions":[],"lastModifiedDate":"2018-09-18T09:59:19","indexId":"70193894","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Management of arthropod pathogen vectors in North America: Minimizing adverse effects on pollinators","docAbstract":"Tick and mosquito management is important to public health protection. At the same time, growing concerns about declines of pollinator species raise the question of whether vector control practices might affect pollinator populations. We report the results of a task force of the North American Pollinator Protection Campaign (NAPPC) that examined potential effects of vector management practices on pollinators, and how these programs could be adjusted to minimize negative effects on pollinating species. The main types of vector control practices that might affect pollinators are landscape manipulation, biocontrol, and pesticide applications. Some current practices already minimize effects of vector control on pollinators (e.g., short-lived pesticides and application-targeting technologies). Nontarget effects can be further diminished by taking pollinator protection into account in the planning stages of vector management programs. Effects of vector control on pollinator species often depend on specific local conditions (e.g., proximity of locations with abundant vectors to concentrations of floral resources), so planning is most effective when it includes collaborations of local vector management professionals with local experts on pollinators. Interventions can then be designed to avoid pollinators (e.g., targeting applications to avoid blooming times and pollinator nesting habitats), while still optimizing public health protection. Research on efficient targeting of interventions, and on effects on pollinators of emerging technologies, will help mitigate potential deleterious effects on pollinators in future management programs. In particular, models that can predict effects of integrated pest management on vector-borne pathogen transmission, along with effects on pollinator populations, would be useful for collaborative decision-making.","language":"English","publisher":"Oxford University Press","doi":"10.1093/jme/tjx146","usgsCitation":"Ginsberg, H., Bargar, T.A., Hladik, M., and Lubelczyk, C., 2017, Management of arthropod pathogen vectors in North America: Minimizing adverse effects on pollinators: Journal of Medical Entomology, v. 54, no. 6, p. 1463-1475, https://doi.org/10.1093/jme/tjx146.","productDescription":"13 p.","startPage":"1463","endPage":"1475","ipdsId":"IP-083417","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469336,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjx146","text":"Publisher Index Page"},{"id":348442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-08","publicationStatus":"PW","scienceBaseUri":"5a0425ade4b0dc0b45b452ec","contributors":{"authors":[{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":721071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bargar, Timothy A. 0000-0001-8588-3436 tbargar@usgs.gov","orcid":"https://orcid.org/0000-0001-8588-3436","contributorId":2450,"corporation":false,"usgs":true,"family":"Bargar","given":"Timothy","email":"tbargar@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":721074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":189904,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle L.","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":721072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubelczyk, Charles","contributorId":200128,"corporation":false,"usgs":false,"family":"Lubelczyk","given":"Charles","email":"","affiliations":[{"id":35696,"text":"Maine Medical Center Research Institute","active":true,"usgs":false}],"preferred":false,"id":721073,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193828,"text":"70193828 - 2017 - Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act","interactions":[],"lastModifiedDate":"2017-11-10T10:01:47","indexId":"70193828","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act","docAbstract":"<p><span>Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2017.09.004","usgsCitation":"McGowan, C.P., Allan, N., Servoss, J., Hedwall, S.J., and Wooldridge, B., 2017, Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act: Global Ecology and Conservation, v. 12, p. 119-130, https://doi.org/10.1016/j.gecco.2017.09.004.","productDescription":"12 p.","startPage":"119","endPage":"130","ipdsId":"IP-084680","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469339,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2017.09.004","text":"Publisher Index Page"},{"id":348431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Sonoran Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.63037109375,\n              34.397844946449865\n            ],\n            [\n              -115.42236328124999,\n              30.240086360983426\n            ],\n            [\n              -111.73095703125,\n              31.55981453201843\n            ],\n            [\n              -114.78515624999999,\n              34.63320791137959\n            ],\n            [\n              -118.63037109375,\n              34.397844946449865\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425afe4b0dc0b45b452f7","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":720620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allan, Nathan","contributorId":187742,"corporation":false,"usgs":false,"family":"Allan","given":"Nathan","affiliations":[],"preferred":false,"id":721088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Servoss, Jeff","contributorId":200133,"corporation":false,"usgs":false,"family":"Servoss","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":721089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hedwall, Shaula J.","contributorId":82196,"corporation":false,"usgs":true,"family":"Hedwall","given":"Shaula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721090,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wooldridge, Brian","contributorId":200134,"corporation":false,"usgs":false,"family":"Wooldridge","given":"Brian","email":"","affiliations":[],"preferred":false,"id":721091,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192646,"text":"70192646 - 2017 - State-dependent behavior alters endocrine–energy relationship: Implications for conservation and management","interactions":[],"lastModifiedDate":"2017-12-19T16:39:42","indexId":"70192646","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"State-dependent behavior alters endocrine–energy relationship: Implications for conservation and management","docAbstract":"<p><span>Glucocorticoids (GC) and triiodothyronine (T3) are two endocrine markers commonly used to quantify resource limitation, yet the relationships between these markers and the energetic state of animals has been studied primarily in small-bodied species in captivity. Free-ranging animals, however, adjust energy intake in accordance with their energy reserves, a behavior known as state-dependent foraging. Further, links between life-history strategies and metabolic allometries cause energy intake and energy reserves to be more strongly coupled in small animals relative to large animals. Because GC and T3 may reflect energy intake or energy reserves, state-dependent foraging and body size may cause endocrine–energy relationships to vary among taxa and environments. To extend the utility of endocrine markers to large-bodied, free-ranging animals, we evaluated how state-dependent foraging, energy reserves, and energy intake influenced fecal GC and fecal T3 concentrations in free-ranging moose (</span><i>Alces alces</i><span>). Compared with individuals possessing abundant energy reserves, individuals with few energy reserves had higher energy intake and high fecal T3 concentrations, thereby supporting state-dependent foraging. Although fecal GC did not vary strongly with energy reserves, individuals with higher fecal GC tended to have fewer energy reserves and substantially greater energy intake than those with low fecal GC. Consequently, individuals with greater energy intake had both high fecal T3 and high fecal GC concentrations, a pattern inconsistent with previous documentation from captive animal studies. We posit that a positive relationship between GC and T3 may be expected in animals exhibiting state-dependent foraging if GC is associated with increased foraging and energy intake. Thus, we recommend that additional investigations of GC– and T3–energy relationships be conducted in free-ranging animals across a diversity of body size and life-history strategies before these endocrine markers are applied broadly to wildlife conservation and management.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1608","usgsCitation":"Jesmer, B.R., Goheen, J.R., Monteith, K.L., and Kauffman, M., 2017, State-dependent behavior alters endocrine–energy relationship: Implications for conservation and management: Ecological Applications, v. 27, no. 8, p. 2303-2312, https://doi.org/10.1002/eap.1608.","productDescription":"10 p.","startPage":"2303","endPage":"2312","ipdsId":"IP-068643","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Greater YellowstoneEcosystem","volume":"27","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-29","publicationStatus":"PW","scienceBaseUri":"5a0425b2e4b0dc0b45b45310","contributors":{"authors":[{"text":"Jesmer, Brett R.","contributorId":200192,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":721380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goheen, Jacob R.","contributorId":200193,"corporation":false,"usgs":false,"family":"Goheen","given":"Jacob","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":721381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monteith, Kevin L.","contributorId":198656,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":716653,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193825,"text":"70193825 - 2017 - Recruitment phenology and pelagic larval duration in Caribbean amphidromous fishes","interactions":[],"lastModifiedDate":"2017-11-29T16:07:21","indexId":"70193825","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Recruitment phenology and pelagic larval duration in Caribbean amphidromous fishes","docAbstract":"<p><span>Amphidromous fishes are major components of oceanic tropical island stream ecosystems, such as those of the Caribbean island, Puerto Rico. Fishes with this life history face threats related to the requirement for connectivity between freshwater and marine environments during early life stages. Pelagic larval duration and recruitment phenology are 2 early life-history processes that are crucial for the biology, ecology, conservation, and management of amphidromous fishes. However, these processes are understudied in the Caribbean in general and have never been quantified in Puerto Rico. We quantified recruit abundance, recruitment phenology, and pelagic larval duration of several Caribbean amphidromous fish species in multiple rivers in Puerto Rico and explored the effects of environmental variables on recruit abundances. Two fish taxa—sirajo goby (</span><i>Sicydium</i><span><span>&nbsp;</span>spp.) and River Goby (</span><i>Awaous banana</i><span>)—were exceptionally abundant as postlarvae and recruited to Caribbean rivers in pulsed migration episodes that were periodic at annual and lunar scales. Sirajo goby and River Goby recruit abundances varied among rivers, were greater at sunrise than at sunset, and were positively related to river discharge. The pelagic larval duration of 4 fish taxa ranged from a minimum of 28 d to a maximum of 103 d with means between 43 ± 7 d (SD) and 65 ± 11 d. We identified the last-quarter moon phase during the months of June through January as periods of maximum amphidromous fish recruitment to freshwater streams. The results and conclusions of our study can be applied to identify critical times to maintain river–ocean connectivity and stream flow for the benefit of the amphidromous fish population dynamics, stream ecology, and natural resources of the Caribbean.</span></p>","language":"English","publisher":"The Society for Freshwater Science","doi":"10.1086/694176","usgsCitation":"Engman, A.C., Kwak, T.J., and Fischer, J., 2017, Recruitment phenology and pelagic larval duration in Caribbean amphidromous fishes: Freshwater Science, v. 36, no. 4, p. 851-865, https://doi.org/10.1086/694176.","productDescription":"15 p.","startPage":"851","endPage":"865","ipdsId":"IP-086662","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -67.620849609375,\n              17.518344187852218\n            ],\n            [\n              -65.10498046875,\n              17.518344187852218\n            ],\n            [\n              -65.10498046875,\n              19.01019029439606\n            ],\n            [\n              -67.620849609375,\n              19.01019029439606\n            ],\n            [\n              -67.620849609375,\n              17.518344187852218\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425afe4b0dc0b45b452fa","contributors":{"authors":[{"text":"Engman, Augustin C.","contributorId":32145,"corporation":false,"usgs":false,"family":"Engman","given":"Augustin","email":"","middleInitial":"C.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":721350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, Jesse R.","contributorId":86618,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse R.","affiliations":[],"preferred":false,"id":721351,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193834,"text":"70193834 - 2017 - Free-ranging domestic cats (<i>Felis catus</i>) on public lands: estimating density, activity, and diet in the Florida Keys","interactions":[],"lastModifiedDate":"2018-02-28T09:51:24","indexId":"70193834","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Free-ranging domestic cats (<i>Felis catus</i>) on public lands: estimating density, activity, and diet in the Florida Keys","docAbstract":"<p><span>Feral and free-ranging domestic cats (</span><i class=\"EmphasisTypeItalic \">Felis catus</i><span>) can have strong negative effects on small mammals and birds, particularly in island ecosystems. We deployed camera traps to study free-ranging cats in national wildlife refuges and state parks on Big Pine Key and Key Largo in the Florida Keys, USA, and used spatial capture–recapture models to estimate cat abundance, movement, and activities. We also used stable isotope analyses to examine the diet of cats captured on public lands. Top population models separated cats based on differences in movement and detection with three and two latent groups on Big Pine Key and Key Largo, respectively. We hypothesize that these latent groups represent feral, semi-feral, and indoor/outdoor house cats based on the estimated movement parameters of each group. Estimated cat densities and activity varied between the two islands, with relatively high densities (~4&nbsp;cats/km</span><sup>2</sup><span>) exhibiting crepuscular diel patterns on Big Pine Key and lower densities (~1&nbsp;cat/km</span><sup>2</sup><span>) exhibiting nocturnal diel patterns on Key Largo. These differences are most likely related to the higher proportion of house cats on Big Pine relative to Key Largo. Carbon and nitrogen isotope ratios from hair samples of free-ranging cats (n&nbsp;=&nbsp;43) provided estimates of the proportion of wild and anthropogenic foods in cat diets. At the population level, cats on both islands consumed mostly anthropogenic foods (&gt;80% of the diet), but eight individuals were effective predators of wildlife (&gt;50% of the diet). We provide evidence that cat groups within a population move different distances, exhibit different activity patterns, and that individuals consume wildlife at different rates, which all have implications for managing this invasive predator.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-017-1534-x","usgsCitation":"Cove, M., Gardner, B., Simons, T.R., Kays, R., and O’Connell, A.F., 2017, Free-ranging domestic cats (<i>Felis catus</i>) on public lands: estimating density, activity, and diet in the Florida Keys: Biological Invasions, v. 20, no. 2, https://doi.org/10.1007/s10530-017-1534-x.","productDescription":"12 p.","startPage":"344","ipdsId":"IP-082053","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.991455078125,\n              25.522614647623293\n            ],\n            [\n              -80.035400390625,\n              25.596948323286135\n            ],\n            [\n              -80.15625,\n              25.596948323286135\n            ],\n            [\n              -80.2716064453125,\n              25.54244147012483\n            ],\n            [\n              -80.3814697265625,\n              25.35891851754525\n            ],\n            [\n              -80.70556640625,\n              25.110471486223346\n            ],\n            [\n              -81.34277343749999,\n              24.886436490787712\n            ],\n            [\n              -81.9854736328125,\n              24.701924833689933\n            ],\n            [\n              -82.144775390625,\n              24.716895455859337\n            ],\n            [\n              -82.3590087890625,\n              24.632038149596895\n            ],\n            [\n              -82.3370361328125,\n              24.52213723599524\n            ],\n            [\n              -82.0404052734375,\n              24.427145340082046\n            ],\n            [\n              -81.45263671875,\n              24.48214938647425\n            ],\n            [\n              -81.10107421874999,\n              24.577099744289427\n            ],\n            [\n              -80.76599121093749,\n              24.716895455859337\n            ],\n            [\n              -80.4034423828125,\n              24.946219074360084\n            ],\n            [\n              -80.255126953125,\n              25.140311914680755\n            ],\n            [\n              -79.991455078125,\n              25.522614647623293\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"2","edition":"333","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-05","publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452ef","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":721030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":721031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kays, Roland","contributorId":83815,"corporation":false,"usgs":true,"family":"Kays","given":"Roland","affiliations":[],"preferred":false,"id":721032,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":720628,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193832,"text":"70193832 - 2017 - Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model","interactions":[],"lastModifiedDate":"2017-11-08T10:51:36","indexId":"70193832","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Integrating the effects of salinity on the physiology of the eastern oyster, <i>Crassostrea virginica</i>, in the northern Gulf of Mexico through a Dynamic Energy Budget model","title":"Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model","docAbstract":"<p><span>We present a Dynamic Energy Budget (DEB) model for the eastern oyster,&nbsp;</span><i>Crassostrea virginica</i><span>, which enables the inclusion of salinity as a third environmental variable, on top of the standard foodr and temperature variables. Salinity changes have various effects on the physiology of oysters, potentially altering filtration and respiration rates, and ultimately impacting growth, reproduction and mortality. We tested different hypotheses as to how to include these effects in a DEB model for<span>&nbsp;</span></span><i>C. virginica</i><span>. Specifically, we tested two potential mechanisms to explain changes in oyster shell growth (cm), tissue dry weight (g) and gonad dry weight (g) when salinity moves away from the ideal range: 1) a negative effect on filtration rate and 2) an additional somatic maintenance cost. Comparative simulations of shell growth, dry tissue biomass and dry gonad weight in two monitored sites in coastal Louisiana experiencing salinity from 0 to 28 were statistically analyzed to determine the best hypothesis. Model parameters were estimated through the covariation method, using literature data and a set of specifically designed ecophysiological experiments. The model was validated through independent field studies in estuaries along the northern Gulf of Mexico. Our results suggest that salinity impacts<span>&nbsp;</span></span><i>C. virginica</i><span>’s energy budget predominantly through effects on filtration rate. With an overwhelming number of environmental factors impacting organisms, and increasing exposure to novel and extreme conditions, the mechanistic nature of the DEB model with its ability to incorporate more than the standard food and temperature variables provides a powerful tool to verify hypotheses and predict individual organism performance across a range of conditions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2017.09.003","usgsCitation":"Lavaud, R., LaPeyre, M.K., Casas, S.M., Bacher, C., and La Peyre, J.F., 2017, Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model: Ecological Modelling, v. 363, p. 221-233, https://doi.org/10.1016/j.ecolmodel.2017.09.003.","productDescription":"13 p.","startPage":"221","endPage":"233","ipdsId":"IP-086164","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.140625,\n              24.367113562651262\n            ],\n            [\n              -79.189453125,\n              24.367113562651262\n            ],\n            [\n              -79.189453125,\n              33.063924198120645\n            ],\n            [\n              -99.140625,\n              33.063924198120645\n            ],\n            [\n              -99.140625,\n              24.367113562651262\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"363","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f1","contributors":{"authors":[{"text":"Lavaud, Romain","contributorId":200114,"corporation":false,"usgs":false,"family":"Lavaud","given":"Romain","email":"","affiliations":[],"preferred":false,"id":721040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casas, Sandra M.","contributorId":145452,"corporation":false,"usgs":false,"family":"Casas","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacher, C.","contributorId":69742,"corporation":false,"usgs":true,"family":"Bacher","given":"C.","email":"","affiliations":[],"preferred":false,"id":721042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":721043,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193830,"text":"70193830 - 2017 - Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","interactions":[],"lastModifiedDate":"2017-11-08T11:16:08","indexId":"70193830","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","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":"Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird","docAbstract":"<p><span>Understanding how both quality and quantity of prey affect the population dynamics of marine predators is a crucial step toward predicting the effects of environmental perturbations on population-level processes. The Junk Food Hypothesis, which posits that energetic content of prey species may influence reproductive capacity of marine top predators regardless of prey availability, has been proposed as a mechanism by which changes in prey populations could affect predator populations in high latitude systems; however, support for this hypothesis has been inconsistent across studies, and further data are needed to elucidate variation in the relative importance of prey quantity and quality, both among predator species and across ecological systems. We tested the relative importance of prey quantity and quality to nestling survival in the eastern brown pelican&nbsp;</span><i>Pelecanus occidentalis carolinensis</i><span><span>&nbsp;</span>across 9 breeding colonies in the northern Gulf of Mexico that varied in underlying availability of a key prey resource, the Gulf menhaden<span>&nbsp;</span></span><i>Brevoortia patronus</i><span>. Both feeding frequency and meal mass were significantly correlated to energy provisioning rates and nestling survival, while energy density of meals had little effect on either metric. Compared to previous results from cold-water systems, we found lower and less variable energy densities (4.4 kJ g</span><sup>-1</sup><span>, vs. 5.2 to 6.5 kJ g</span><sup>-1</sup><span><span>&nbsp;</span>in other studies) and lipid content (9% dry mass, vs. 16 to 23% in other studies) of common prey items. While Gulf menhaden was the most common prey species at all colonies, the proportion of menhaden fed to nestlings varied and was not strongly correlated to fledging success. We conclude that quantity rather than quality of prey, particularly small schooling fish, is the main driver of brown pelican reproductive success in this system, and that environmental perturbations affecting biomass, distribution, and abundance of forage fish could substantially affect brown pelican reproductive success.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12301","usgsCitation":"Lamb, J.S., Jodice, P.G., and Satge, Y.G., 2017, Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird: Marine Ecology Progress Series, v. 581, p. 149-164, https://doi.org/10.3354/meps12301.","productDescription":"16 p.","startPage":"149","endPage":"164","ipdsId":"IP-083227","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469338,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps12301","text":"Publisher Index Page"},{"id":438155,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78D6J","text":"USGS data release","linkHelpText":"Composition of diet of juvenile Brown Pelican in the northern Gulf of Mexico (2013-2015)"},{"id":348429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.525390625,\n              25.403584973186703\n            ],\n            [\n              -81.38671875,\n              25.403584973186703\n            ],\n            [\n              -81.38671875,\n              30.826780904779774\n            ],\n            [\n              -98.525390625,\n              30.826780904779774\n            ],\n            [\n              -98.525390625,\n              25.403584973186703\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"581","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425aee4b0dc0b45b452f4","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":720623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":721087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70194125,"text":"70194125 - 2017 - Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?","interactions":[],"lastModifiedDate":"2017-11-16T13:17:38","indexId":"70194125","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?","docAbstract":"Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3403","usgsCitation":"Steen, V., Sofaer, H., Skagen, S., Ray, A.J., and Noon, B.R., 2017, Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?: Ecology and Evolution, v. 7, no. 21, p. 8841-8851, https://doi.org/10.1002/ece3.3403.","productDescription":"11 p.","startPage":"8841","endPage":"8851","ipdsId":"IP-073435","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469337,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3403","text":"Publisher Index Page"},{"id":348998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","volume":"7","issue":"21","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-20","publicationStatus":"PW","scienceBaseUri":"5a60fb15e4b06e28e9c22c17","contributors":{"authors":[{"text":"Steen, Valerie vsteen@usgs.gov","contributorId":5598,"corporation":false,"usgs":true,"family":"Steen","given":"Valerie","email":"vsteen@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":722250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":722252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":722251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Andrea J.","contributorId":196935,"corporation":false,"usgs":false,"family":"Ray","given":"Andrea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noon, Barry R.","contributorId":198981,"corporation":false,"usgs":false,"family":"Noon","given":"Barry","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":722254,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193726,"text":"ofr20171144 - 2017 - Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","interactions":[],"lastModifiedDate":"2017-11-08T17:33:23","indexId":"ofr20171144","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2017","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":"2017-1144","title":"Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11","docAbstract":"<p class=\"p1\">The Columbia River, in Washington and Oregon, and Coos Bay, in Oregon, are economically important shipping channels that are inhabited by several fishes protected under the Endangered Species Act (ESA). Maintenance of shipping channels involves dredge operations to maintain sufficient in-channel depths to allow large ships to navigate the waterways safely. Fishes entrained by dredge equipment often die or experience delayed mortality. Other potential negative effects of dredging include increased turbidity, reductions in prey resources, and the release of harmful contaminants from the dredged sediments. One species of concern is the ESA-listed green sturgeon (<i>Acipenser medirostris</i>; Southern Distinct Population Segment). In this study, we used acoustic telemetry to identify habitat use, arrival and departure timing, and the extent of upstream migration of green sturgeon in the Columbia River and Coos Bay to help inform dredge operations to minimize potential take of green sturgeon. Autonomous acoustic receivers were deployed in Coos Bay from the mouth to river kilometer (rkm) 21.6 from October 2009 through October 2010. In the Columbia River Estuary, receivers were deployed between the mouth and rkm 37.8 from April to November in 2010 and 2011. A total of 29 subadult and adult green sturgeon were tagged with temperature and pressure sensor tags and released during the study, primarily in Willapa Bay and Grays Harbor, Washington, and the Klamath River, Oregon. Green sturgeon detected during the study but released by other researchers also were included in the study.</p><p class=\"p1\">The number of tagged green sturgeon detected in the two estuaries differed markedly. In Coos Bay, only one green sturgeon was detected for about 2 hours near the estuary mouth. In the Columbia River Estuary, 9 green sturgeon were detected in 2010 and 10 fish were detected in 2011. Green sturgeon entered the Columbia River from May through October during both years, with the greatest numbers of fish being present in August and September. One green sturgeon was detected at the uppermost receiver station (rkm 37.8), but overall, the number of fish detected upriver decreased rapidly with distance from the estuary mouth. Residence times of fish that were only detected in the lower 4.8 rkm generally were less than 24 hours, but fish detected farther upriver had a median residence time greater than 10 days. Green sturgeon were widely dispersed among channel and&nbsp;non-channel habitats in the lower estuary in 2010. In 2011, the fish were more concentrated near the estuary mouth. The intensity of use, measured as the total number of fish detections at each station, generally was greatest from Point Ellice (rkm 20.1) to Rice Island (rkm 33.0) in channel and shallow shoal areas, and lowest at the stations west of Point Ellice with the exception of the area near the entrance to the Ilwaco Channel.</p><p class=\"p1\">Sensor tag data indicated that the deeper South and North Channel habitats (bottom depth ≥10 m) were used, as were the more shallow sandy shoal, shoreline, and bay habitats (bottom depth &lt;10 m). Median fish depths among fish and receiver locations ranged from 2.5 to 28.2 m below water surface (bws) and water temperatures ranged from 9.1 to 22.0 °C during late May through mid-October. In the deeper channel habitat, near the Ilwaco Channel, fish inhabited water with median temperatures ranging from 11.4 to 16.7 °C, whereas east of Point Ellice, predominantly in shallow non-channel habitats, fish inhabited water with median temperatures ranging from about 17.0 to 21.0 °C.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171144","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansel, H.C., Romine, J.G., and Perry, R.W., 2017, Acoustic tag detections of green sturgeon in the Columbia River and Coos Bay estuaries, Washington and Oregon, 2010–11: U.S. Geological Survey Open-File Report 2017-1144, 30 p., https://doi.org/10.3133/ofr20171144.","productDescription":"vi, 30 p.","onlineOnly":"Y","ipdsId":"IP-088817","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":348413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1144/ofr20171144.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1144"},{"id":348412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1144/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Astoria","otherGeospatial":"Coos Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.36283111572264,\n              43.33067209551502\n            ],\n            [\n              -124.12696838378908,\n              43.33067209551502\n            ],\n            [\n              -124.12696838378908,\n              43.476591264232674\n            ],\n            [\n              -124.36283111572264,\n              43.476591264232674\n            ],\n            [\n              -124.36283111572264,\n              43.33067209551502\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.09263610839842,\n              46.14416148780093\n            ],\n            [\n              -123.61129760742186,\n              46.14416148780093\n            ],\n            [\n              -123.61129760742186,\n              46.32559414426375\n            ],\n            [\n              -124.09263610839842,\n              46.32559414426375\n            ],\n            [\n              -124.09263610839842,\n              46.14416148780093\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://wfrc.usgs.gov/\" target=\"blank\" data-mce-href=\"https://wfrc.usgs.gov/\">Western Fisheries Research Center</a><br> U.S. Geological Survey<br> 6505 NE 65th Street<br>Seattle, Washington 98115</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Study Area<br></li><li>Methods<br></li><li>Results<br></li><li>Discussion<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendix A. Dates When Acoustic-Receiver Stations in the Detection Array Were Operational in the lower Columbia River Estuary, Washington and Oregon, 2010–11<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-08","noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"5a0425b0e4b0dc0b45b452fe","contributors":{"authors":[{"text":"Hansel, Hal C. 0000-0002-3537-8244 hhansel@usgs.gov","orcid":"https://orcid.org/0000-0002-3537-8244","contributorId":2887,"corporation":false,"usgs":true,"family":"Hansel","given":"Hal","email":"hhansel@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":720081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":720083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":720082,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70259477,"text":"70259477 - 2017 - Incremental heating of Bishop Tuff sanidine reveals preeruptive radiogenic Ar and rapid remobilization from cold storage","interactions":[],"lastModifiedDate":"2024-10-09T15:35:27.32171","indexId":"70259477","displayToPublicDate":"2017-11-07T10:28:32","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8936,"text":"Proceedings of the National Academy of Sciences (PNAS)","active":true,"publicationSubtype":{"id":10}},"title":"Incremental heating of Bishop Tuff sanidine reveals preeruptive radiogenic Ar and rapid remobilization from cold storage","docAbstract":"<p><span>Recent improvements in analytical and microsampling techniques for multiple geochronometers have resulted in datasets with unprecedented temporal and spatial resolution. These advances are accompanied by the discovery of crystal- and outcrop-scale complexities previously obscured by low analytical precision. Single-crystal incremental heating resolves subtle, intracrystal isotopic heterogeneity, allowing for more-accurate&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar eruption ages. The eruption ages of widespread volcanic ash deposits are critical for calibrating the geologic timescale, and thus their accuracy has substantial implications for the geologic, biologic, and global climate records. Complex distribution of&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar dates in the deposits of supervolcanic eruptions requires rethinking the magmatic processes and their effect on the&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar system, specifically the extent of cooling and remobilization during the decades to centuries preceding these events.</span></p>","language":"English","publisher":"National Academy of Sciences (NAS)","doi":"10.1073/pnas.1709581114","usgsCitation":"Andersen, N., R., J.B., Singer, B.S., and Hildreth, W., 2017, Incremental heating of Bishop Tuff sanidine reveals preeruptive radiogenic Ar and rapid remobilization from cold storage: Proceedings of the National Academy of Sciences (PNAS), v. 114, no. 47, p. 12407-12412, https://doi.org/10.1073/pnas.1709581114.","productDescription":"6 p.","startPage":"12407","endPage":"12412","ipdsId":"IP-087555","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469342,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1073/pnas.1709581114","text":"Publisher Index Page"},{"id":462749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.25,\n              38\n            ],\n            [\n              -119.25,\n              37.25\n            ],\n            [\n              -118.25,\n              37.25\n            ],\n            [\n              -118.25,\n              38\n            ],\n            [\n              -119.25,\n              38\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"114","issue":"47","noUsgsAuthors":false,"publicationDate":"2017-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, Nathan L.","contributorId":251802,"corporation":false,"usgs":false,"family":"Andersen","given":"Nathan L.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":915436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"R., Jicha. Brian","contributorId":345053,"corporation":false,"usgs":false,"family":"R.","given":"Jicha.","email":"","middleInitial":"Brian","affiliations":[{"id":82473,"text":"University of Wisconsin- Madison","active":true,"usgs":false}],"preferred":false,"id":915437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Brad S. 0000-0003-3595-5168","orcid":"https://orcid.org/0000-0003-3595-5168","contributorId":229592,"corporation":false,"usgs":false,"family":"Singer","given":"Brad","email":"","middleInitial":"S.","affiliations":[{"id":41688,"text":"Department of Geosciences, University of Wisconsin-Madison, Madison, WI 53716, USA","active":true,"usgs":false}],"preferred":false,"id":915438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192924,"text":"70192924 - 2017 - Patterns of distribution, abundance, and change over time in a subarctic marine bird community","interactions":[],"lastModifiedDate":"2018-02-28T09:45:56","indexId":"70192924","displayToPublicDate":"2017-11-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5536,"text":"Deep Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of distribution, abundance, and change over time in a subarctic marine bird community","docAbstract":"<p><span>Over recent decades, marine ecosystems of Prince William Sound (PWS), Alaska, have experienced concurrent effects of natural and anthropogenic perturbations, including variability in the climate system of the northeastern Pacific Ocean. We documented spatial and temporal patterns of variability in the summer marine bird community in relation to habitat and climate variability using boat-based surveys of marine birds conducted during the period 1989–2012. We hypothesized that a major factor structuring marine bird communities in PWS would be proximity to the shoreline, which is theorized to relate to aspects of food web structure. We also hypothesized that shifts in physical ecosystem drivers differentially affected nearshore-benthic and pelagic components of PWS food webs. We evaluated support for our hypotheses using an approach centered on community-level patterns of spatial and temporal variability. We found that an environmental gradient related to water depth and distance from shore was the dominant factor spatially structuring the marine bird community. Responses of marine birds to this onshore-offshore environmental gradient were related to dietary specialization, and separated marine bird taxa by prey type. The primary form of temporal variability over the study period was monotonic increases or decreases in abundance for 11 of 18 evaluated genera of marine birds; 8 genera had declined, whereas 3 had increased. The greatest declines occurred in genera associated with habitats that were deeper and farther from shore. Furthermore, most of the genera that declined primarily fed on pelagic prey resources, such as forage fish and mesozooplankton, and few were directly affected by the 1989&nbsp;</span><i>Exxon Valdez</i><span><span>&nbsp;</span>oil spill. Our observations of synchronous declines are indicative of a shift in pelagic components of PWS food webs. This pattern was correlated with climate variability at time-scales of several years to a decade.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2017.07.012","usgsCitation":"Cushing, D., Roby, D.D., and Irons, D.B., 2017, Patterns of distribution, abundance, and change over time in a subarctic marine bird community: Deep Sea Research Part II: Topical Studies in Oceanography, v. 147, p. 148-163, https://doi.org/10.1016/j.dsr2.2017.07.012.","productDescription":"16 p.","startPage":"148","endPage":"163","ipdsId":"IP-077534","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2017.07.012","text":"Publisher Index Page"},{"id":348386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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              -148.6505126953125,\n              59.72317714492064\n            ],\n            [\n              -146.2225341796875,\n              59.72317714492064\n            ],\n            [\n              -146.2225341796875,\n              61.0689165862774\n            ],\n            [\n              -148.6505126953125,\n              61.0689165862774\n            ],\n            [\n              -148.6505126953125,\n              59.72317714492064\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"147","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e843e4b09af898c8cb20","contributors":{"authors":[{"text":"Cushing, Daniel","contributorId":199323,"corporation":false,"usgs":false,"family":"Cushing","given":"Daniel","affiliations":[],"preferred":false,"id":720954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irons, David B.","contributorId":63658,"corporation":false,"usgs":true,"family":"Irons","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":720955,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196912,"text":"70196912 - 2017 - The blind men meet the elephant at the dam: Alternative spatial and taxonomic components reveal different insights about how low-head dams impact fish biodiversity","interactions":[],"lastModifiedDate":"2018-05-14T13:20:59","indexId":"70196912","displayToPublicDate":"2017-11-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The blind men meet the elephant at the dam: Alternative spatial and taxonomic components reveal different insights about how low-head dams impact fish biodiversity","docAbstract":"<p><span>Dams are ubiquitous environmental impacts that threaten aquatic ecosystems. The ability to compare across research studies is essential to conserve the native biodiversity that is impacted by the millions of low‐head dams that currently fragment streams and rivers. Here, we identify a previously unaddressed obstacle that impedes this generalization. Specifically, divergent spatial and taxonomic approaches that result from different conceptualizations of the dam‐biodiversity problem can produce conflicting science‐based conclusions about the same dam impact. In this research, using the same dammed and undammed sites, we evaluated the scientific generality of different conceptualizations of the dam‐biodiversity problem. We compared two different but commonly used spatial approaches—(1) above dam–below dam vs. (2)&nbsp;undammed–dammed comparisons—and 11 different, commonly used taxonomic approaches (three assemblage summaries, eight guilds). Sites above the dam structure had less diverse fish assemblages than sites below dams, whereas sites below the dam structure were similar to undammed sites. Thus, spatial approach 1 detected a large dam effect and spatial approach 2 detected a small dam effect. Similarly, some taxonomic responses (species richness, diversity, abundance, and number of guilds) detected large dam effects; other responses detected small (riffle specialist guild) or no dam effects (pool generalists). In summary, our results showed that how the problem was framed altered scientific conclusions and created different dam realities. The metaphor of how individual blind men disagree about the structure of an elephant, based on examinations of different body parts, reinforces the need for a coordinated, holistic perspective on dam research. Although no single approach is adequate for all problems, identifying the form, consequences of, and relationships among different research conceptualizations will set the stage for future syntheses of dam‐biodiversity research to advance science‐based conservation.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1973","usgsCitation":"Fencl, J.S., Mather, M.E., Smith, J.M., and Hitchman, S.M., 2017, The blind men meet the elephant at the dam: Alternative spatial and taxonomic components reveal different insights about how low-head dams impact fish biodiversity: Ecosphere, v. 8, no. 11, p. 1-17, https://doi.org/10.1002/ecs2.1973.","productDescription":"e01973; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-075537","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":461349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1973","text":"Publisher Index Page"},{"id":354063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","scienceBaseUri":"5afee7c6e4b0da30c1bfc368","contributors":{"authors":[{"text":"Fencl, Jane S.","contributorId":166699,"corporation":false,"usgs":false,"family":"Fencl","given":"Jane","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":735046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hitchman, Sean M.","contributorId":204805,"corporation":false,"usgs":false,"family":"Hitchman","given":"Sean","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735047,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209685,"text":"70209685 - 2017 - Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA","interactions":[],"lastModifiedDate":"2020-04-21T16:08:17.708545","indexId":"70209685","displayToPublicDate":"2017-11-06T11:01:32","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA","docAbstract":"<p><span>We present an electrical resistivity model of the crust and upper mantle from two‐dimensional (2‐D) anisotropic inversion of magnetotelluric data collected along a 450&nbsp;km transect of the Rio Grande rift, southern Rocky Mountains, and High Plains in Colorado, USA. Our model provides a window into the modern‐day lithosphere beneath the Rocky Mountain Front to depths in excess of 150&nbsp;km. Two key features of the 2‐D resistivity model are (1) a broad zone (~200&nbsp;km wide) of enhanced electrical conductivity (&lt;20&nbsp;Ωm) in the midcrust to lower crust that is centered beneath the highest elevations of the southern Rocky Mountains and (2) hydrated lithospheric mantle beneath the Great Plains with water content in excess of 100&nbsp;ppm. We interpret the high conductivity region of the lower crust as a zone of partially molten basalt and associated deep‐crustal fluids that is the result of recent (less than 10&nbsp;Ma) tectonic activity in the region. The recent supply of volatiles and/or heat to the base of the crust in the late Cenozoic implies that modern‐day tectonic activity in the western United States extends to at least the western margin of the Great Plains. The transition from conductive to resistive upper mantle is caused by a gradient in lithospheric modification, likely including hydration of nominally anhydrous minerals, with maximum hydration occurring beneath the Rocky Mountain Front. This lithospheric “hydration front” has implications for the tectonic evolution of the continental interior and the mechanisms by which water infiltrates the lithosphere.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014474","collaboration":"","usgsCitation":"Feucht, D., Sheehan, A.F., and Bedrosian, P.A., 2017, Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA: Journal of Geophysical Research B: Solid Earth, v. 122, no. 12, p. 9489-9510, https://doi.org/10.1002/2017JB014474.","productDescription":"22 p.","startPage":"9489","endPage":"9510","ipdsId":"IP-091898","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469344,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb014474","text":"Publisher Index Page"},{"id":374159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountains ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.061279296875,\n              37.01132594307015\n            ],\n            [\n              -102.052001953125,\n              37.01132594307015\n            ],\n            [\n              -102.052001953125,\n              40.98819156349393\n            ],\n            [\n              -109.061279296875,\n              40.98819156349393\n            ],\n            [\n              -109.061279296875,\n              37.01132594307015\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"122","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Feucht, D. W. 0000-0002-3672-4719","orcid":"https://orcid.org/0000-0002-3672-4719","contributorId":224277,"corporation":false,"usgs":false,"family":"Feucht","given":"D. W.","affiliations":[],"preferred":false,"id":787515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Anne F 0000-0002-9629-1687","orcid":"https://orcid.org/0000-0002-9629-1687","contributorId":224234,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","email":"","middleInitial":"F","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":787516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787517,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70220386,"text":"70220386 - 2017 - Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration","interactions":[],"lastModifiedDate":"2021-05-10T14:36:35.266187","indexId":"70220386","displayToPublicDate":"2017-11-06T09:29:26","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration","docAbstract":"<p><span>Large Mississippi River (MR) diversions (peak water flow &gt;1416&nbsp;m</span><sup>3</sup><span>/s and sediment loads &gt;165&nbsp;kg/s) have been proposed as part of a suite of coastal restoration projects and are expected to rehabilitate and rebuild wetlands to alleviate the significant historic wetland loss in coastal Louisiana. These coastal wetlands are undergoing increasing eustatic sea‐level rise, land subsidence, climate change, and anthropogenic disturbances. However, the effect of MR diversions on wetland soil organic carbon (SOC) sequestration in receiving basins remains unknown. The rate of SOC sequestration or carbon burial in wetlands is one of the variables used to assess the role of wetland soils in carbon cycling and also to construct wetland carbon budgets. In this study, we examined the effects of MR water and sediment diversions on landscape‐scale SOC sequestration rates that were estimated from vertical accretion for the next 50&nbsp;yr (2010–2060) under two environmental (moderate and less optimistic) scenarios. Our analyses were based on model simulations taken from the Wetland Morphology model developed for Louisiana's 2012 Coastal Master Plan. The master plan modeled a “future‐without‐action” scenario as well as eight individual MR diversion projects in two of the hydrologic basins (Barataria and Breton Sound). We examined the effects that discharge rates (peak flow) and locations of these individual diversion projects had on SOC sequestration rates. Modeling results indicate that large river diversions are capable of improving basin‐wide SOC sequestration capacity (162–222&nbsp;g&nbsp;C·m</span><sup>−2</sup><span>·yr</span><sup>−1</sup><span>) by up to 14% (30&nbsp;g&nbsp;C·m</span><sup>−2</sup><span>·yr</span><sup>−1</sup><span>) in Louisiana deltaic wetlands compared to the future‐without‐action scenario, especially under the less optimistic scenario. When large river diversions are placed in the upper receiving basin, SOC sequestration rates are 3.7–10.5% higher (6–24&nbsp;g&nbsp;C·m</span><sup>−2</sup><span>·yr</span><sup>−1</sup><span>) than when these structures are placed in the lower receiving basin. Modeling results also indicate that both diversion discharge and location have large effects on SOC sequestration in low‐salinity (freshwater and intermediate marshes) as compared to high‐salinity marshes (brackish and saline marshes).</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1984","usgsCitation":"Wang, H., Steyer, G.D., Couvillion, B., Beck, H.J., Rybczyk, J.M., Rivera-Monroy, V.H., Krauss, K.W., and Visser, J.M., 2017, Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration: Ecosphere, v. 8, no. 11, e01984, 15 p., https://doi.org/10.1002/ecs2.1984.","productDescription":"e01984, 15 p.","ipdsId":"IP-070521","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469345,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1984","text":"Publisher Index Page"},{"id":438156,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72R3PWW","text":"USGS data release","linkHelpText":"Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration"},{"id":385545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin, Breton Sound Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.3128662109375,\n              29.480252193344267\n            ],\n            [\n              -89.00,\n              29.480252193344267\n            ],\n            [\n              -89.00,\n              30.285159872426014\n            ],\n            [\n              -91.3128662109375,\n              30.285159872426014\n            ],\n            [\n              -91.3128662109375,\n              29.480252193344267\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"11","noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":815332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Couvillion, Brady 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":146832,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Holly J. 0000-0002-0567-9329 hbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-0567-9329","contributorId":257931,"corporation":false,"usgs":true,"family":"Beck","given":"Holly","email":"hbeck@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rybczyk, John M","contributorId":257932,"corporation":false,"usgs":false,"family":"Rybczyk","given":"John","email":"","middleInitial":"M","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":815335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":815336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815337,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Visser, Jenneke M.","contributorId":178417,"corporation":false,"usgs":false,"family":"Visser","given":"Jenneke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":815338,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70194126,"text":"70194126 - 2017 - Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges","interactions":[],"lastModifiedDate":"2018-01-04T08:24:43","indexId":"70194126","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges","docAbstract":"Hawaiian forest birds are imperiled, with fewer than half the original >40 species remaining extant. Recent studies document ongoing rapid population decline and pro- ject complete climate-based range losses for the critically endangered Kaua’i endemics ‘akeke’e (Loxops caeruleirostris) and ‘akikiki (Oreomystis bairdi) by end-of-century due to projected warming. Climate change facilitates the upward expansion of avian malaria into native high elevation forests where disease was historically absent. While intensi- fied conservation efforts attempt to safeguard these species and their habitats, the magnitude of potential loss and the urgency of this situation require all conservation options to be seriously considered. One option for Kaua’i endemics is translocation to islands with higher elevation habitats. We explored the feasibility of interisland translocation by projecting baseline and future climate-based ranges of ‘akeke’e and ‘akikiki across the Hawaiian archipelago. For islands where compatible climates for these spe- cies were projected to endure through end-of-century, an additional climatic niche overlap analysis compares the spatial overlap between Kaua’i endemics and current native species on prospective destination islands. Suitable climate-based ranges exist on Maui and Hawai’i for these Kaua’i endemics that offer climatically distinct areas compared to niche distributions of destination island endemics. While we recognize that any decision to translocate birds will include assessing numerous additional social, political, and biological factors, our focus on locations of enduring and ecologically compatible climate-based ranges represents the first step to evaluate this potential conservation option. Our approach considering baseline and future distributions of species with climatic niche overlap metrics to identify undesirable range overlap provides a method that can be utilized for other climate-vulnerable species with disjointed compatible environments beyond their native range.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3451","usgsCitation":"Fortini, L.B., Kaiser, L.R., Vorsino, A.E., Paxton, E., and Jacobi, J.D., 2017, Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges: Ecology and Evolution, v. 7, no. 21, p. 9119-9130, https://doi.org/10.1002/ece3.3451.","productDescription":"12 p.","startPage":"9119","endPage":"9130","ipdsId":"IP-079990","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":469346,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3451","text":"Publisher Index Page"},{"id":349006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","volume":"7","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-27","publicationStatus":"PW","scienceBaseUri":"5a60fb20e4b06e28e9c22cee","contributors":{"authors":[{"text":"Fortini, Lucas B. 0000-0002-5781-7295 lfortini@usgs.gov","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":4645,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas","email":"lfortini@usgs.gov","middleInitial":"B.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":722261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, Lauren R.","contributorId":200422,"corporation":false,"usgs":false,"family":"Kaiser","given":"Lauren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":722262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vorsino, Adam E.","contributorId":200423,"corporation":false,"usgs":false,"family":"Vorsino","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":722263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":722260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":722264,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193565,"text":"70193565 - 2017 - Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown ","interactions":[],"lastModifiedDate":"2017-11-06T11:40:48","indexId":"70193565","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown ","docAbstract":"The risk posed by intensification of North Atlantic hurricane activity remains controversial, in part due to a lack of available storm proxy records that extend beyond the relatively stable climates of the late Holocene. Here we present a record of storm-triggered turbidite deposition offshore the Dry Tortugas, south Florida, USA, that spans abrupt transitions in North Atlantic sea-surface temperature and Atlantic Meridional Overturning Circulation (AMOC) during the Younger Dryas (12.9–11.7 ka). Despite potentially hostile conditions for cyclogenesis in the tropical North Atlantic at that time, our record and numerical experiments suggest that strong hurricanes may have regularly affected Florida. Less severe surface cooling at mid-latitudes (∼20°–40°N) than across much of the tropical North Atlantic (∼10°–20°N) in response to AMOC reduction may best explain strong hurricane activity during the Younger Dryas near the Dry Tortugas and possibly along the entire southeastern coast of the United States.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G39270.1","usgsCitation":"Toomey, M., Korty, R.L., Donnelly, J.P., van Hengstum, P.J., and Curry, W.B., 2017, Increased hurricane frequency near Florida during Younger Dryas Atlantic Meridional Overturning Circulation slowdown : Geology, v. 45, no. 11, p. 1047-1050, https://doi.org/10.1130/G39270.1.","productDescription":"4 p.","startPage":"1047","endPage":"1050","ipdsId":"IP-089873","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469347,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/9392","text":"External Repository"},{"id":348262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas","volume":"45","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-05","publicationStatus":"PW","scienceBaseUri":"5a07e849e4b09af898c8cb36","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":719374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korty, Robert L.","contributorId":199535,"corporation":false,"usgs":false,"family":"Korty","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":719375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":719376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Hengstum, Peter J.","contributorId":199536,"corporation":false,"usgs":false,"family":"van Hengstum","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":719377,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curry, William B.","contributorId":199537,"corporation":false,"usgs":false,"family":"Curry","given":"William","email":"","middleInitial":"B.","affiliations":[{"id":16634,"text":"Bermuda Institute of Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":719378,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193630,"text":"ofr20171143 - 2017 - A concept for performance management for Federal science programs","interactions":[],"lastModifiedDate":"2017-11-07T09:53:00","indexId":"ofr20171143","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","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":"2017-1143","title":"A concept for performance management for Federal science programs","docAbstract":"<p class=\"p1\">The demonstration of clear linkages between planning, funding, outcomes, and performance management has created unique challenges for U.S. Federal science programs. An approach is presented here that characterizes science program strategic objectives by one of five “activity types”: (1) knowledge discovery, (2) knowledge development and delivery, (3) science support, (4) inventory and monitoring, and (5) knowledge synthesis and assessment. The activity types relate to performance measurement tools for tracking outcomes of research funded under the objective. The result is a multi-time scale, integrated performance measure that tracks individual performance metrics synthetically while also measuring progress toward long-term outcomes. Tracking performance on individual metrics provides explicit linkages to root causes of potentially suboptimal performance and captures both internal and external program drivers, such as customer relations and science support for managers. Functionally connecting strategic planning objectives with performance measurement tools is a practical approach for publicly funded science agencies that links planning, outcomes, and performance management—an enterprise that has created unique challenges for public-sector research and development programs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171143","usgsCitation":"Whalen, K.G., 2017, A concept for performance management for Federal science programs: U.S. Geological Survey Open-File Report 2017-1143, 16 p., https://doi.org/10.3133/ofr20171143.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-090006","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348313,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1143/coverthb.jpg"},{"id":348314,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1143/ofr20171143.pdf","text":"Report","size":"490 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1143"}],"contact":"<p>Western Region Unit Supervisor<br> <a href=\"https://www.coopunits.org/\" target=\"blank\" data-mce-href=\"https://www.coopunits.org/\">Cooperative Fish and Wildlife Research Unit Program</a><br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive, MS 303<br> Reston, Virginia 20192</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Section I.—Strategic Planning and Science Program Objective Synthesis<br></li><li>Section II—Integrated Performance Management<br></li><li>Discussion<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-06","noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","scienceBaseUri":"5a07e847e4b09af898c8cb30","contributors":{"authors":[{"text":"Whalen, Kevin G. kwhalen@usgs.gov","contributorId":200057,"corporation":false,"usgs":true,"family":"Whalen","given":"Kevin G.","email":"kwhalen@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":719676,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70190029,"text":"sim3384 - 2017 - Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington","interactions":[],"lastModifiedDate":"2022-04-19T19:05:52.520083","indexId":"sim3384","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3384","title":"Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington","docAbstract":"<p><span>This map is an interpretation of a modern lidar digital elevation model combined with the geology depicted on the Geologic Map of the Des Moines 7.5' Quadrangle, King County, Washington (Booth and Waldron, 2004). Booth and Waldron described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Des Moines 7.5' quadrangle. The base map that they used was originally compiled in 1943 and revised using 1990 aerial photographs; it has 25-ft contours, nominal horizontal resolution of about 40 ft (12 m), and nominal mean vertical accuracy of about 10 ft (3 m). Similar to many geologic maps, much of the geology in the Booth and Waldron (2004) map was interpreted from landforms portrayed on the topographic map. In 2001, the Puget Sound Lidar Consortium obtained a lidar-derived digital elevation model (DEM) for much of the Puget Sound area, including the entire Des Moines 7.5' quadrangle. This new DEM has a horizontal resolution of about 6 ft (2 m) and a mean vertical accuracy of about 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM compared to topography constructed from air-photo stereo models have much improved the interpretation of geology, even in this heavily developed area, especially the distribution and relative age of some surficial deposits. For a brief description of the light detection and ranging (lidar) remote sensing method and this data acquisition program, see Haugerud and others (2003).</span><span class=\"m_-5381376500837880811gmail-Apple-converted-space\">&nbsp;</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3384","usgsCitation":"Tabor, R.W., and Booth, D.B., 2017, Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington: U.S. Geological Survey Scientific Investigations Map 3384, 17 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3384.","productDescription":"Pamphlet: iii, 17 p.; 1 Sheet: 30.83 x 30.04 inches; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056389","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":399114,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_106502.htm"},{"id":348331,"rank":9,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3384/","text":"Shapefiles and CSV","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3384 shapefiles and CSV"},{"id":348329,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_gdb.zip","text":"Geodatabase","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3384 geodatabase"},{"id":348328,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_readme.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3384 readme"},{"id":348330,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_simple.zip","text":"Shapefiles","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3384 shapefiles"},{"id":348325,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3384 pamphlet"},{"id":348327,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_metadata.xml","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3384 metadata xml"},{"id":348326,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3384/sim3384_metadata.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3384 metadata txt"},{"id":348324,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3384/sim3384.pdf","text":"Map","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3384"},{"id":348323,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3384/coverthb.jpg"}],"scale":"24000","country":"United States","state":"Washington","county":"King County","otherGeospatial":"Des Moines 7.5' quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.375,\n              47.375\n            ],\n            [\n              -122.25,\n              47.375\n            ],\n            [\n              -122.25,\n              47.5\n            ],\n            [\n              -122.375,\n              47.5\n            ],\n            [\n              -122.375,\n              47.375\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://geomaps.wr.usgs.gov/gmeg/staff.htm\" target=\"blank\" data-mce-href=\"https://geomaps.wr.usgs.gov/gmeg/staff.htm\">Contact Information</a>, <a href=\"http://geomaps.wr.usgs.gov/\" target=\"blank\" data-mce-href=\"http://geomaps.wr.usgs.gov/\">Geology, Minerals, Energy, &amp; Geophysics Science Center—Menlo Park</a><br> U.S. Geological Survey<br> 345 Middlefield Road<br> Menlo Park, CA 94025-3591<br> FAX 650/329-4936</p>","tableOfContents":"<ul><li>Introduction<br></li><li>Geologic Summary<br></li><li>Stratigraphy and Geologic History<br></li><li>Description of Map Units<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-11-06","noUsgsAuthors":false,"publicationDate":"2017-11-06","publicationStatus":"PW","scienceBaseUri":"5a07e84ae4b09af898c8cb3a","contributors":{"authors":[{"text":"Tabor, Rowland W. rtabor@usgs.gov","contributorId":127390,"corporation":false,"usgs":true,"family":"Tabor","given":"Rowland W.","email":"rtabor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":707248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":707249,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192292,"text":"70192292 - 2017 - Marine infectious disease ecology","interactions":[],"lastModifiedDate":"2017-11-10T13:52:22","indexId":"70192292","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":808,"text":"Annual Review of Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Marine infectious disease ecology","docAbstract":"<p><span>To put marine disease impacts in context requires a broad perspective on the roles infectious agents have in the ocean. Parasites infect most marine vertebrate and invertebrate species, and parasites and predators can have comparable biomass density, suggesting they play comparable parts as consumers in marine food webs. Although some parasites might increase with disturbance, most probably decline as food webs unravel. There are several ways to adapt epidemiological theory to the marine environment. In particular, because the ocean represents a three-dimensional moving habitat for hosts and parasites, models should open up the spatial scales at which infective stages and host larvae travel. In addition to open recruitment and dimensionality, marine parasites are subject to fishing, filter feeders, dosedependent infection, environmental forcing, and death-based transmission. Adding such considerations to marine disease models will make it easier to predict which infectious diseases will increase or decrease in a changing ocean.</span></p>","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-ecolsys-121415-032147","usgsCitation":"Lafferty, K.D., 2017, Marine infectious disease ecology: Annual Review of Ecology, Evolution, and Systematics, v. 48, p. 473-496, https://doi.org/10.1146/annurev-ecolsys-121415-032147.","productDescription":"14 p.","startPage":"473","endPage":"496","ipdsId":"IP-083677","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488717,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-ecolsys-121415-032147","text":"Publisher Index Page"},{"id":348283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8c6e4b09af898c860df","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":715161,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193634,"text":"70193634 - 2017 - Examining the occupancy–density relationship for a low-density carnivore","interactions":[],"lastModifiedDate":"2017-11-29T16:09:23","indexId":"70193634","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Examining the occupancy–density relationship for a low-density carnivore","docAbstract":"<ol id=\"jpe12883-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li><p>The challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Non-invasive sampling techniques and advanced statistical approaches have&nbsp;alleviated some of these challenges and can even allow for spatially explicit estimates of density, one of the most valuable wildlife monitoring tools.</p></li><li><p>For some species, individual identification comes at no cost when unique attributes (e.g. pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive laboratory processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions.</p></li><li><p>Here, we used a large-scale monitoring study of fisher<span>&nbsp;</span><i>Pekania pennanti</i><span>&nbsp;</span>to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We combined remote cameras with baited hair snares during 2013–2015 to sample across a 70&nbsp;096-km<sup>2</sup><span>&nbsp;</span>region of western New York, USA. We fit occupancy and Royle–Nichols models to species detection–non-detection data collected by cameras, and spatial capture–recapture (SCR) models to individual encounter data obtained by genotyped hair samples. Variation in the state variables within 15-km<sup>2</sup><span>&nbsp;</span>grid cells was modelled as a function of landscape attributes known to influence fisher distribution.</p></li><li><p>We found a close relationship between grid cell estimates of fisher state variables from the models using detection–non-detection data and those from the SCR model, likely due to informative spatial covariates across a large landscape extent and a grid cell resolution that worked well with the movement ecology of the species. Fisher occupancy and density were both positively associated with the proportion of coniferous-mixed forest and negatively associated with road density. As a result, spatially explicit management recommendations for fisher were similar across models, though relative variation was dampened for the detection–non-detection data.</p></li><li><p><i>Synthesis and applications</i>. Our work provides empirical evidence that models using detection–non-detection data can make similar inferences regarding relative spatial variation of the focal population to models using more expensive individual encounters when the selected spatial grain approximates or is marginally smaller than home range size. When occupancy alone is chosen as a cost-effective state variable for monitoring, simulation and sensitivity analyses should be used to understand how inferences from detection–non-detection data will be affected by aspects of study design and species ecology.</p></li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.12883","usgsCitation":"Linden, D.W., Fuller, A.K., Royle, J., and Hare, M.P., 2017, Examining the occupancy–density relationship for a low-density carnivore: Journal of Applied Ecology, v. 54, no. 6, p. 2043-2052, https://doi.org/10.1111/1365-2664.12883.","productDescription":"10 p.","startPage":"2043","endPage":"2052","ipdsId":"IP-076765","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469348,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12883","text":"Publisher Index Page"},{"id":348255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-11","publicationStatus":"PW","scienceBaseUri":"5a07e847e4b09af898c8cb2e","contributors":{"authors":[{"text":"Linden, Daniel W.","contributorId":171466,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":720660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hare, Matthew P.","contributorId":171454,"corporation":false,"usgs":false,"family":"Hare","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":720661,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193674,"text":"70193674 - 2017 - Comparing measurement response and inverted results of electrical resistivity tomography instruments","interactions":[],"lastModifiedDate":"2017-11-06T11:19:36","indexId":"70193674","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Comparing measurement response and inverted results of electrical resistivity tomography instruments","docAbstract":"In this investigation, we compare the results of electrical resistivity measurements made by six commercially available instruments on the same line of electrodes to determine if there are differences in the measured data or inverted results. These comparisons are important to determine whether measurements made between different instruments are consistent. We also degraded contact resistance on one quarter of the electrodes to study how each instrument responds to different electrical connection with the ground. We find that each instrument produced statistically similar apparent resistivity results, and that any conservative assessment of the final inverted resistivity models would result in a similar interpretation for each. We also note that inversions, as expected, are affected by measurement error weights. Increased measurement errors were most closely associated with degraded contact resistance in this set of experiments. In a separate test we recorded the full measured waveform for a single four-electrode array to show how poor electrode contact and instrument-specific recording settings can lead to systematic measurement errors. We find that it would be acceptable to use more than one instrument during an investigation with the expectation that the results would be comparable assuming contact resistance remained consistent.","language":"English","publisher":"Environmental and Engineering Geophysical Society","doi":"10.2113/JEEG22.3.249","usgsCitation":"Parsekian, A.D., Claes, N., Singha, K., Minsley, B.J., Carr, B., Voytek, E., Harmon, R., Kass, A., Carey, A., Thayer, D., and Flinchum, B., 2017, Comparing measurement response and inverted results of electrical resistivity tomography instruments: Journal of Environmental & Engineering Geophysics, v. 22, no. 3, p. 249-266, https://doi.org/10.2113/JEEG22.3.249.","productDescription":"18 p.","startPage":"249","endPage":"266","ipdsId":"IP-080728","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":348258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-18","publicationStatus":"PW","scienceBaseUri":"5a07e846e4b09af898c8cb2c","contributors":{"authors":[{"text":"Parsekian, Andrew D.","contributorId":23829,"corporation":false,"usgs":false,"family":"Parsekian","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":719851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claes, Niels","contributorId":199728,"corporation":false,"usgs":false,"family":"Claes","given":"Niels","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":719852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":719853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":719850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carr, Bradley","contributorId":175482,"corporation":false,"usgs":false,"family":"Carr","given":"Bradley","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":719854,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Voytek, Emily","contributorId":199729,"corporation":false,"usgs":false,"family":"Voytek","given":"Emily","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":719855,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harmon, Ryan","contributorId":191252,"corporation":false,"usgs":false,"family":"Harmon","given":"Ryan","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":720662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kass, Andy","contributorId":191248,"corporation":false,"usgs":true,"family":"Kass","given":"Andy","email":"","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":720663,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carey, Austin","contributorId":149257,"corporation":false,"usgs":false,"family":"Carey","given":"Austin","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":720664,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thayer, Drew","contributorId":190722,"corporation":false,"usgs":false,"family":"Thayer","given":"Drew","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":720665,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Flinchum, Brady","contributorId":199732,"corporation":false,"usgs":false,"family":"Flinchum","given":"Brady","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":720666,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70193669,"text":"70193669 - 2017 - Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network","interactions":[],"lastModifiedDate":"2017-11-29T13:48:07","indexId":"70193669","displayToPublicDate":"2017-11-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network","docAbstract":"<p>Conservation areas, both public and private, are critical tools to protect biodiversity and deliver important ecosystem services (ES) to society. Although societal benefits from such ES are increasingly used to promote public support of conservation, the number of beneficiaries, their identity, and the magnitude of benefits are largely unknown for the vast majority of conservation areas in the United States public-private conservation network. The location of conservation areas in relation to people strongly influences the direction and magnitude of ES flows as well as the identity of beneficiaries. We analyzed benefit zones, the areas to which selected ES could be conveyed to beneficiaries, to assess who benefits from a typical conservation network. Better knowledge of ES flows and beneficiaries will help land conservationists make a stronger case for the broad collateral benefits of conservation and help to address issues of social-environmental justice. To evaluate who benefits the most from the current public-private conservation network, we delineated the benefit zones for local ES (within 16 km) that are conveyed along hydrological paths from public (federal and state) and private (easements) conservation lands in the states of North Carolina and Virginia, USA. We also discuss the challenges and demonstrate an approach for delineating nonhydrological benefits that are passively conveyed to beneficiaries. We mapped and compared the geographic distribution of benefit zones within and among conservation area types. We further compared beneficiary demographics across benefit zones of the conservation area types and found that hydrological benefit zones of federal protected areas encompass disproportionately fewer minority beneficiaries compared to statewide demographic patterns. In contrast, benefit zones of state protected areas and private easements encompassed a much greater proportion of minority beneficiaries (~22–25%). Benefit zones associated with private conservation lands included beneficiaries of significantly greater household income than benefit zones of other types of conservation areas. Our analysis of ES flows revealed significant socioeconomic gaps in how the current public-private conservation network benefits the public. These gaps warrant consideration in regional conservation plans and suggest that private conservation initiatives may be best suited for responding to the equity challenge. Enhancing the ecosystem benefits and the equity of benefit delivery from private conservation networks could build public and political support for long-term conservation strategies and ultimately enhance conservation efficacy. </p>","language":"English","doi":"10.5751/ES-09021-220136","usgsCitation":"Villamagna, A., Mogollon, B., and Angermeier, P.L., 2017, Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network: Ecology and Society, v. 22, no. 1, Article 36; 16 p., https://doi.org/10.5751/ES-09021-220136.","productDescription":"Article 36; 16 p.","ipdsId":"IP-071190","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-09021-220136","text":"Publisher Index 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Carolina\",\"nation\":\"USA  \"}}]}","volume":"22","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a00314de4b0531197b5a73c","contributors":{"authors":[{"text":"Villamagna, Amy M.","contributorId":166683,"corporation":false,"usgs":false,"family":"Villamagna","given":"Amy M.","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":719844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mogollon, Beatriz","contributorId":166682,"corporation":false,"usgs":false,"family":"Mogollon","given":"Beatriz","email":"","affiliations":[{"id":35590,"text":"USAID/USFS","active":true,"usgs":false}],"preferred":false,"id":719845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. biota@usgs.gov","contributorId":1432,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":613,"text":"Virginia Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":719843,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193699,"text":"70193699 - 2017 - Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics","interactions":[],"lastModifiedDate":"2018-09-26T14:59:45","indexId":"70193699","displayToPublicDate":"2017-11-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics","docAbstract":"<div id=\"en_main_abstract\" class=\"article-section__content mainAbstract\" lang=\"en\"><p>Current management of large carnivores is informed using a variety of parameters, methods, and metrics; however, these data are typically considered independently. Sharing information among data types based on the underlying ecological, and recognizing observation biases, can improve estimation of individual and global parameters. We present a general integrated population model (IPM), specifically designed for brown bears (<i>Ursus arctos</i>), using three common data types for bear (<i>U</i>. spp.) populations: repeated counts, capture–mark–recapture, and litter size. We considered factors affecting ecological and observation processes for these data. We assessed the practicality of this approach on a simulated population and compared estimates from our model to values used for simulation and results from count data only. We then present a practical application of this general approach adapted to the constraints of a case study using historical data available for brown bears on Kodiak Island, Alaska, USA. The IPM provided more accurate and precise estimates than models accounting for repeated count data only, with credible intervals including the true population 94% and 5% of the time, respectively. For the Kodiak population, we estimated annual average litter size (within one year after birth) to vary between 0.45 [95% credible interval: 0.43; 0.55] and 1.59 [1.55; 1.82]. We detected a positive relationship between salmon availability and adult survival, with survival probabilities greater for females than males. Survival probabilities increased from cubs to yearlings to dependent young ≥2&nbsp;years old and decreased with litter size. Linking multiple information sources based on ecological and observation mechanisms can provide more accurate and precise estimates, to better inform management. IPMs can also reduce data collection efforts by sharing information among agencies and management units. Our approach responds to an increasing need in bear populations’ management and can be readily adapted to other large carnivores.</p></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3469","usgsCitation":"Bled, F., Belant, J.L., Van Daele, L.J., Svoboda, N., Gustine, D.D., Hilderbrand, G., and Barnes, V.G., 2017, Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics: Ecology and Evolution, v. 7, no. 22, p. 9531-9543, https://doi.org/10.1002/ece3.3469.","productDescription":"13 p.","startPage":"9531","endPage":"9543","ipdsId":"IP-081752","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":461351,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3469","text":"Publisher Index Page"},{"id":348202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"22","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"5a00314ce4b0531197b5a738","contributors":{"authors":[{"text":"Bled, Florent","contributorId":199765,"corporation":false,"usgs":false,"family":"Bled","given":"Florent","email":"","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":719972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":719973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Daele, Lawrence J.","contributorId":199766,"corporation":false,"usgs":false,"family":"Van Daele","given":"Lawrence","email":"","middleInitial":"J.","affiliations":[{"id":35600,"text":"Kodiak Wildlife Services, Kodiak, AK","active":true,"usgs":false}],"preferred":false,"id":719974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Svoboda, Nathan","contributorId":199767,"corporation":false,"usgs":false,"family":"Svoboda","given":"Nathan","email":"","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":719975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":719970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hilderbrand, Grant V. 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":199764,"corporation":false,"usgs":true,"family":"Hilderbrand","given":"Grant V.","email":"ghilderbrand@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":719971,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnes, Victor G. Jr.","contributorId":95113,"corporation":false,"usgs":true,"family":"Barnes","given":"Victor","suffix":"Jr.","email":"","middleInitial":"G.","affiliations":[{"id":35655,"text":"Kodiak Brown Bear Trust, Westcliffe, CO","active":true,"usgs":false}],"preferred":false,"id":719976,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193692,"text":"70193692 - 2017 - Summer and winter space use and home range characteristics of Golden Eagles (Aquila chrysaetos) in eastern North America","interactions":[],"lastModifiedDate":"2017-11-22T16:41:15","indexId":"70193692","displayToPublicDate":"2017-11-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Summer and winter space use and home range characteristics of Golden Eagles (<i>Aquila chrysaetos</i>) in eastern North America","title":"Summer and winter space use and home range characteristics of Golden Eagles (Aquila chrysaetos) in eastern North America","docAbstract":"<p>Movement behavior and its relationship to habitat provide critical information toward understanding the effects of changing environments on birds. The eastern North American population of Golden Eagles (<i>Aquila chrysaetos</i>) is a genetically distinct and small population of conservation concern. To evaluate the potential responses of this population to changing landscapes, we calculated the home range and core area sizes of 52 eagles of 6 age–sex classes during the summer and winter seasons. Variability in range size was related to variation in topography and open cover, and to age and sex. In summer, eagle ranges that were smaller had higher proportions of ridge tops and open cover and had greater topographic roughness than did larger ranges. In winter, smaller ranges had higher proportions of ridge tops, hillsides and cliffs, and open cover than did larger ranges. All age and sex classes responded similarly to topography and open cover in both seasons. Not surprisingly, adult eagles occupied the smallest ranges in both seasons. Young birds used larger ranges than adults, and subadults in summer used the largest ranges (&gt;9,000 km<sup>2</sup>). Eastern adult home ranges in summer were 2–10 times larger than those reported for other populations in any season. Golden Eagles in eastern North America may need to compensate for generally lower-quality habitat in the region by using larger ranges that support access to adequate quantities of resources (prey, updrafts, and nesting, perching, and roosting sites) associated with open cover and diverse topography. Our results suggest that climate change–induced afforestation on the breeding grounds and ongoing land cover change from timber harvest and energy development on the wintering grounds may affect the amount of suitable habitat for Golden Eagles in eastern North America.</p>","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-16-154.1","usgsCitation":"Miller, T.A., Brooks, R.P., Lanzone, M.J., Cooper, J., O’Malley, K., Brandes, D., Duerr, A.E., and Katzner, T., 2017, Summer and winter space use and home range characteristics of Golden Eagles (Aquila chrysaetos) in eastern North America: The Condor, v. 119, no. 4, p. 697-719, https://doi.org/10.1650/CONDOR-16-154.1.","productDescription":"23 p.","startPage":"697","endPage":"719","ipdsId":"IP-079719","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-154.1","text":"Publisher Index Page"},{"id":348196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fedfb2e4b0531197b573be","contributors":{"authors":[{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Robert P.","contributorId":199749,"corporation":false,"usgs":false,"family":"Brooks","given":"Robert","email":"","middleInitial":"P.","affiliations":[{"id":24683,"text":"The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":719918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lanzone, Michael J.","contributorId":147851,"corporation":false,"usgs":false,"family":"Lanzone","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13392,"text":"Cellular Tracking Technologies","active":true,"usgs":false}],"preferred":false,"id":719919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":719920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Malley, Kieran","contributorId":199750,"corporation":false,"usgs":false,"family":"O’Malley","given":"Kieran","email":"","affiliations":[{"id":24498,"text":"West Virginia Division of Natural Resources, Point Pleasant, WV","active":true,"usgs":false}],"preferred":false,"id":719921,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandes, David","contributorId":138917,"corporation":false,"usgs":false,"family":"Brandes","given":"David","email":"","affiliations":[{"id":35653,"text":"Lafayette College, Easton, PA","active":true,"usgs":false}],"preferred":false,"id":719922,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719923,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":719916,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193710,"text":"70193710 - 2017 - Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","interactions":[],"lastModifiedDate":"2017-11-03T10:56:17","indexId":"70193710","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","docAbstract":"<p>Floodplain lakes are important wetlands on many lowland floodplains of the world but depressional floodplain lakes are rare in the Mississippi River Alluvial Valley. One of the largest is Catahoula Lake, which has existed with seasonally fluctuating water levels for several thousand years but is now in an increasingly hydrologically altered floodplain. Woody vegetation has been encroaching into the lake bed and the rate of this expansion has increased since major human hydrologic modifications, such as channelization, levee construction, and dredging for improvement of navigation, but it remains unknown what role those modifications may have played in altering lake sedimentation processes. Profiles of thirteen <sup>137</sup>Cs sediment cores indicate sedimentation has been about 0.26&nbsp;cm&nbsp;y<sup>−&nbsp;1</sup> over the past 60&nbsp;years and has been near this rate since land use changes began about 200&nbsp;years ago (<sup>210</sup>Pb, and <sup>14</sup>C in Tedford, 2009). Carbon sequestration was low (10.4&nbsp;g&nbsp;m<sup>−&nbsp;2</sup>&nbsp;y<sup>−&nbsp;1</sup>), likely because annual drying promotes mineralization and export. Elemental composition (high Zr and Ti and low Ca and K) and low pH of recent (&lt;~60&nbsp;y) or surface sediments suggest Gulf Coastal Plain origin, but below the recent sediment deposits, 51% of sediment profiles showed influence of Mississippi River alluvium, rich in base cations such as K<sup>+</sup>, Ca<sup>2&nbsp;+</sup>, and Mg<sup>2&nbsp;+</sup>. The recent shift to dominance of Coastal Plain sediments on the lake-bed surface suggests hydrologic modification has disconnected the lake from sediment-bearing flows from the Mississippi River. Compared to its condition prior to hydrologic alterations that intensified in the 1930s, Catahoula Lake is about 15&nbsp;cm shallower and surficial sediments are more acidic. Although these results are not sufficient to attribute ecological changes directly to sedimentological changes, it is likely the altered sedimentary and hydrologic environment is contributing to the increased dominance of woody vegetation.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2017.04.020","usgsCitation":"Latuso, K.D., Keim, R.F., King, S.L., Weindorf, D.C., and DeLaune, R.D., 2017, Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana: Catena, v. 156, p. 290-297, https://doi.org/10.1016/j.catena.2017.04.020.","productDescription":"8 p.","startPage":"290","endPage":"297","ipdsId":"IP-061448","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Catahoula Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.1697998046875,\n              31.42749129448044\n            ],\n            [\n              -92.04277038574219,\n              31.502458420817206\n            ],\n            [\n              -91.99607849121094,\n              31.552793227677334\n            ],\n            [\n              -91.99745178222656,\n              31.613626970322684\n            ],\n            [\n              -92.06748962402344,\n              31.610703179979982\n            ],\n            [\n              -92.12448120117188,\n              31.577950455417472\n            ],\n            [\n              -92.17666625976562,\n              31.52411741833466\n            ],\n            [\n              -92.22198486328125,\n              31.48313670206181\n            ],\n            [\n              -92.23915100097656,\n              31.454439514853256\n            ],\n            [\n              -92.22335815429688,\n              31.433350262414404\n            ],\n            [\n              -92.19863891601562,\n              31.42749129448044\n            ],\n            [\n              -92.1697998046875,\n              31.42749129448044\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"156","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fd8027e4b0531197b5013b","contributors":{"authors":[{"text":"Latuso, Karen D.","contributorId":113984,"corporation":false,"usgs":false,"family":"Latuso","given":"Karen","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keim, Richard F.","contributorId":117125,"corporation":false,"usgs":false,"family":"Keim","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weindorf, David C.","contributorId":140924,"corporation":false,"usgs":false,"family":"Weindorf","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":27688,"text":"Texas Tech University, Lubbock, TX 79409","active":true,"usgs":false}],"preferred":false,"id":720025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeLaune, Ronald D.","contributorId":61581,"corporation":false,"usgs":false,"family":"DeLaune","given":"Ronald","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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