Coastal marsh plants are increasingly subject to physicochemical stressors under rising sea levels, and the maintenance of marsh ecological functions can depend on the ability of individual species and communities to tolerate or adapt to altered conditions. We conducted a greenhouse experiment to identify hydrology and salinity effects on growth of three common brackish marsh macrophytes of coastal Florida, USA: Distichlis spicata, Juncus roemerianus, and Spartina bakeri. The species were potted as monocultures and exposed to three salinities (0, 15, or 28 psu) and two hydrologic conditions (saturated, tidal) over 22 months. Final stem density of J. roemerianus and S. bakeri did not differ among treatments. In D. spicata, however, stem density was lowest at 28 psu and lower in tidal compared to saturated conditions. Mean stem height of all species was lowest at 28 psu. Aboveground biomass of J. roemerianus was not affected by the treatments, but in D. spicata andS. bakeri it was lowest at 28 psu. Results indicated that J. roemerianus was the most adaptable species and may, therefore, be more resilient to climate-change driven stressors. However, plant-plant interactions such as interspecific competition and facilitation can alter the response of individual species to environmental factors.
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"Lawrence, KS","doi":"10.1007/s13157-015-0711-x","usgsCitation":"Howard, R.J., Biagas, J.M., and Allain, L.K., 2016, Growth of common brackish marsh macrophytes under altered hydrology and salinity regimes: Wetlands, v. 36, no. 1, p. 11-20, https://doi.org/10.1007/s13157-015-0711-x.","productDescription":"10 p.","startPage":"11","endPage":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064073","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":312235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Ten Thousand Islands National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.5,\n 25.9\n ],\n [\n -81.5,\n 26\n ],\n [\n -81.6,\n 26\n ],\n [\n -81.6,\n 25.9\n ],\n [\n -81.5,\n 25.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-12","publicationStatus":"PW","scienceBaseUri":"566ff651e4b09cfe53ca79a0","contributors":{"authors":[{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","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":582055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biagas, Janelda M. 0000-0001-5548-1970 biagasj@usgs.gov","orcid":"https://orcid.org/0000-0001-5548-1970","contributorId":4613,"corporation":false,"usgs":true,"family":"Biagas","given":"Janelda","email":"biagasj@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":582056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allain, Larry K. 0000-0002-7717-9761 allainl@usgs.gov","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":2414,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","email":"allainl@usgs.gov","middleInitial":"K.","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":582057,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160795,"text":"70160795 - 2016 - Evidence that sea lampreys (Petromyzon marinus) complete their life cycle within a tributary of the Laurentian Great Lakes by parasitizing fishes in inland lakes","interactions":[],"lastModifiedDate":"2016-12-14T12:47:27","indexId":"70160795","displayToPublicDate":"2015-11-11T17:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Evidence that sea lampreys (Petromyzon marinus) complete their life cycle within a tributary of the Laurentian Great Lakes by parasitizing fishes in inland lakes","docAbstract":"The sea lamprey (Petromyzon marinus) invaded the upper Laurentian Great Lakes and feeds on valued fish. The Cheboygan River, Michigan, USA, is a large sea lamprey producing tributary to Lake Huron and despite having a renovated dam 2 km from the river mouth that presumably blocks sea lamprey spawning migrations, the watershed upstream of the dam remains infested with larval sea lamprey. A navigational lock near the dam has been hypothesized as the means of escapement of adult sea lampreys from Lake Huron and source of the upper river population (H1). However, an alternative hypothesis (H2) is that some sea lampreys complete their life cycle upstream of the dam, without entering Lake Huron. To evaluate the alternative hypothesis, we gathered angler reports of lamprey wounds on game fishes upstream of the dam, and captured adult sea lampreys downstream and upstream of the dam to contrast abundance, run timing, size, and statolith microchemistry. Results indicate that a small population of adult sea lampreys (n < 200) completed their life cycle upstream of the dam during 2013 and 2014. This is the most comprehensive evidence that sea lampreys complete their life history within a tributary of the upper Great Lakes, and indicates that similar landlocked populations could occur in other watersheds. Because the adult sea lamprey population upstream of the dam is small, complete elimination of the already low adult escapement from Lake Huron might allow multiple control tactics such as lampricides, trapping, and sterile male release to eradicate the population.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2015.10.011","usgsCitation":"Johnson, N., Twohey, M.B., Miehls, S.M., Cwalinski, T.A., Godby, N.A., Lochet, A., Slade, J.W., Jubar, A.K., and Siefkes, M.J., 2016, Evidence that sea lampreys (Petromyzon marinus) complete their life cycle within a tributary of the Laurentian Great Lakes by parasitizing fishes in inland lakes: Journal of Great Lakes Research, v. 42, no. 1, p. 90-98, https://doi.org/10.1016/j.jglr.2015.10.011.","productDescription":"9 p.","startPage":"90","endPage":"98","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067017","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Cheboygan River 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Unit","active":true,"usgs":false}],"preferred":false,"id":583930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godby, Neal A","contributorId":150997,"corporation":false,"usgs":false,"family":"Godby","given":"Neal","email":"","middleInitial":"A","affiliations":[{"id":18159,"text":"Michigan Department of Natural Resources, Northern Lake Huron Management Unit","active":true,"usgs":false}],"preferred":false,"id":583931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lochet, Aude","contributorId":150998,"corporation":false,"usgs":false,"family":"Lochet","given":"Aude","email":"","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":583932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slade, Jeffrey W.","contributorId":126760,"corporation":false,"usgs":false,"family":"Slade","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[{"id":6597,"text":"U.S. Fish and Wildlife Service, Ludington Biological Station","active":true,"usgs":false}],"preferred":false,"id":583933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jubar, Aaron K.","contributorId":150999,"corporation":false,"usgs":false,"family":"Jubar","given":"Aaron","email":"","middleInitial":"K.","affiliations":[{"id":18161,"text":"US Fish and Wildlife Service, Lundington Biological Station","active":true,"usgs":false}],"preferred":false,"id":583934,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Siefkes, Michael J.","contributorId":36905,"corporation":false,"usgs":true,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":583935,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159576,"text":"70159576 - 2016 - Flexible risk metrics for identifying and monitoring conservation-priority species","interactions":[],"lastModifiedDate":"2015-12-14T13:51:40","indexId":"70159576","displayToPublicDate":"2015-11-10T16:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Flexible risk metrics for identifying and monitoring conservation-priority species","docAbstract":"Region-specific conservation programs should have objective, reliable metrics for species prioritization and progress evaluation that are customizable to the goals of a program, easy to comprehend and communicate, and standardized across time. Regional programs may have vastly different goals, spatial coverage, or management agendas, and one-size-fits-all schemes may not always be the best approach. We propose a quantitative and objective framework for generating metrics for prioritizing species that is straightforward to implement and update, customizable to different spatial resolutions, and based on readily available time-series data. This framework is also well-suited to handling missing-data and observer error. We demonstrate this approach using North American Breeding Bird Survey (NABBS) data to identify conservation priority species from a list of over 300 landbirds across 33 bird conservation regions (BCRs). To highlight the flexibility of the framework for different management goals and timeframes we calculate two different metrics. The first identifies species that may be inadequately monitored by NABBS protocols in the near future (TMT, time to monitoring threshold), and the other identifies species likely to decline significantly in the near future based on recent trends (TPD, time to percent decline). Within the individual BCRs we found up to 45% (mean 28%) of the species analyzed had overall declining population trajectories, which could result in up to 37 species declining below a minimum NABBS monitoring threshold in at least one currently occupied BCR within the next 50 years. Additionally, up to 26% (mean 8%) of the species analyzed within the individual BCRs may decline by 30% within the next decade. Conservation workers interested in conserving avian diversity and abundance within these BCRs can use these metrics to plan alternative monitoring schemes or highlight the urgency of those populations experiencing the fastest declines. However, this framework is adaptable to many taxa besides birds where abundance time-series data are available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.10.020","usgsCitation":"Stanton, J.C., Semmens, B.X., McKann, P.C., Will, T., and Thogmartin, W.E., 2016, Flexible risk metrics for identifying and monitoring conservation-priority species: Ecological Indicators, v. 61, no. 2, p. 683-692, https://doi.org/10.1016/j.ecolind.2015.10.020.","productDescription":"10 p.","startPage":"683","endPage":"692","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066945","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2015.10.020","text":"Publisher Index Page"},{"id":311180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","volume":"61","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa4","chorus":{"doi":"10.1016/j.ecolind.2015.10.020","url":"http://dx.doi.org/10.1016/j.ecolind.2015.10.020","publisher":"Elsevier BV","authors":"Stanton Jessica C., Semmens Brice X., McKann Patrick C., Will Tom, Thogmartin Wayne E.","journalName":"Ecological Indicators","publicationDate":"2/2016"},"contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":579535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKann, Patrick C.","contributorId":149776,"corporation":false,"usgs":false,"family":"McKann","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6733,"text":"former UMESC employee, USGS","active":true,"usgs":false}],"preferred":false,"id":579536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Will, Tom","contributorId":149777,"corporation":false,"usgs":false,"family":"Will","given":"Tom","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":579537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159584,"text":"70159584 - 2016 - Density dependence, whitebark pine, and vital rates of grizzly bears","interactions":[],"lastModifiedDate":"2016-04-13T12:09:01","indexId":"70159584","displayToPublicDate":"2015-11-10T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence, whitebark pine, and vital rates of grizzly bears","docAbstract":"Understanding factors influencing changes in population trajectory is important for effective wildlife management, particularly for populations of conservation concern. Annual population growth of the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem, USA has slowed from 4.2–7.6% during 1983–2001 to 0.3–2.2% during 2002–2011. Substantial changes in availability of a key food source and bear population density have occurred. Whitebark pine (Pinus albicaulis), the seeds of which are a valuable but variable fall food for grizzly bears, has experienced substantial mortality primarily due to a mountain pine beetle (Dendroctonus ponderosae) outbreak that started in the early 2000s. Positive growth rates of grizzly bears have resulted in populations reaching high densities in some areas and have contributed to continued range expansion. We tested research hypotheses to examine if changes in vital rates detected during the past decade were more associated with whitebark pine decline or, alternatively, increasing grizzly bear density. We focused our assessment on known-fate data to estimate survival of cubs-of-the-year (cubs), yearlings, and independent bears (≥2 yrs), and reproductive transition of females from having no offspring to having cubs. We used spatially and temporally explicit indices for grizzly bear density and whitebark pine mortality as individual covariates. Models indicated moderate support for an increase in survival of independent male bears over 1983–2012, whereas independent female survival did not change. Cub survival, yearling survival, and reproductive transition from no offspring to cubs all changed during the 30-year study period, with lower rates evident during the last 10–15 years. Cub survival and reproductive transition were negatively associated with an index of grizzly bear density, indicating greater declines where bear densities were higher. Our analyses did not support a similar relationship for the index of whitebark pine mortality. The results of our study support the interpretation that slowing of population growth during the last decade was associated more with increasing grizzly bear density than the decline in whitebark pine. Grizzly bear density and its potential effect on vital rates and population trajectory warrant consideration for management of the grizzly bear population in the Greater Yellowstone Ecosystem.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.1005","usgsCitation":"van Manen, F.T., Haroldson, M.A., Bjornlie, D., Ebinger, M.R., Thompson, D.J., Costello, C., and White, G.C., 2016, Density dependence, whitebark pine, and vital rates of grizzly bears: Journal of Wildlife Management, v. 80, no. 2, p. 300-313, https://doi.org/10.1002/jwmg.1005.","productDescription":"14 p.","startPage":"300","endPage":"313","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059669","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.1005","text":"Publisher Index Page"},{"id":311170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Grand Teton National Park, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.181396484375,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 42.44778143462245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa0","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":579582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, Gary C.","contributorId":26256,"corporation":false,"usgs":true,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":579583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70162412,"text":"70162412 - 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The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b04094","collaboration":"University of Illinois","usgsCitation":"Quijano, J.C., Jackson, P., Santacruz, S., Morales, V.M., and Garcia, M., 2016, Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois: Environmental Science & Technology, v. 50, no. 1, p. 478-488, https://doi.org/10.1021/acs.est.5b04094.","productDescription":"11 p.","startPage":"478","endPage":"488","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068749","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":314749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Clinton Lake","geographicExtents":"{\n \"type\": 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Ryan pjackson@usgs.gov","contributorId":2960,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","email":"pjackson@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":589483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santacruz, Santiago","contributorId":152485,"corporation":false,"usgs":false,"family":"Santacruz","given":"Santiago","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":589485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morales, Viviana M","contributorId":152486,"corporation":false,"usgs":false,"family":"Morales","given":"Viviana","email":"","middleInitial":"M","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":589486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":589487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159579,"text":"70159579 - 2016 - Towards understanding resprouting at the global scale","interactions":[],"lastModifiedDate":"2016-01-18T09:38:10","indexId":"70159579","displayToPublicDate":"2015-11-10T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Towards understanding resprouting at the global scale","docAbstract":"Understanding and predicting plant response to disturbance is of paramount importance in our changing world. Resprouting ability is often considered a simple qualitative trait and used in many ecological studies. Our aim is to show some of the complexities of resprouting while highlighting cautions that need be taken in using resprouting ability to predict vegetation responses across disturbance types and biomes. There are marked differences in resprouting depending on the disturbance type, and fire is often the most severe disturbance because it includes both defoliation and lethal temperatures. In the Mediterranean biome, there are differences in functional strategies to cope with water deficit between resprouters (dehydration avoiders) and nonresprouters (dehydration tolerators); however, there is little research to unambiguously extrapolate these results to other biomes. Furthermore, predictions of vegetation responses to changes in disturbance regimes require consideration not only of resprouting, but also other relevant traits (e.g. seeding, bark thickness) and the different correlations among traits observed in different biomes; models lacking these details would behave poorly at the global scale. Overall, the lessons learned from a given disturbance regime and biome (e.g. crown-fire Mediterranean ecosystems) can guide research in other ecosystems but should not be extrapolated at the global scale.
","language":"English","publisher":"Wiley","doi":"10.1111/nph.13644","usgsCitation":"Pausas, J.G., Pratt, R., Keeley, J.E., Jacobsen, A.L., Ramirez, A.R., Vilagrosa, A., Paula, S., Kanekua-Pia, I.N., and Davis, S.D., 2016, Towards understanding resprouting at the global scale: New Phytologist, v. 209, no. 3, p. 945-954, https://doi.org/10.1111/nph.13644.","productDescription":"10 p.","startPage":"945","endPage":"954","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066488","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.13644","text":"Publisher Index Page"},{"id":311153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-07","publicationStatus":"PW","scienceBaseUri":"56431535e4b0aafbcd017fb8","contributors":{"authors":[{"text":"Pausas, Juli G.","contributorId":91347,"corporation":false,"usgs":true,"family":"Pausas","given":"Juli","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":579550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, R. Brandon","contributorId":149778,"corporation":false,"usgs":false,"family":"Pratt","given":"R. Brandon","affiliations":[{"id":17822,"text":"CA State U., Bakersfield, CA","active":true,"usgs":false}],"preferred":false,"id":579551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":579549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobsen, Anna L.","contributorId":149779,"corporation":false,"usgs":false,"family":"Jacobsen","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":17823,"text":"CA State U, Bakersfield, CA","active":true,"usgs":false}],"preferred":false,"id":579552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramirez, Aaron R.","contributorId":149780,"corporation":false,"usgs":false,"family":"Ramirez","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":17824,"text":"UC Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":579553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vilagrosa, Alberto","contributorId":149781,"corporation":false,"usgs":false,"family":"Vilagrosa","given":"Alberto","email":"","affiliations":[{"id":17825,"text":"CEAM-Universitat d'Alacant, Alacant, Spain","active":true,"usgs":false}],"preferred":false,"id":579554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paula, Susana","contributorId":149782,"corporation":false,"usgs":false,"family":"Paula","given":"Susana","email":"","affiliations":[{"id":17826,"text":"ICAE, Universidad Austral de Chile, Valdivia, Chile","active":true,"usgs":false}],"preferred":false,"id":579555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanekua-Pia, Iolana N.","contributorId":149783,"corporation":false,"usgs":false,"family":"Kanekua-Pia","given":"Iolana","email":"","middleInitial":"N.","affiliations":[{"id":17827,"text":"Pepperdine U, Malibu, CA","active":true,"usgs":false}],"preferred":false,"id":579556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davis, Stephen D.","contributorId":149784,"corporation":false,"usgs":false,"family":"Davis","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":17827,"text":"Pepperdine U, Malibu, CA","active":true,"usgs":false}],"preferred":false,"id":579557,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70158684,"text":"ofr20151195 - 2016 - Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States","interactions":[],"lastModifiedDate":"2018-07-31T10:13:13","indexId":"ofr20151195","displayToPublicDate":"2015-11-05T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1195","title":"Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States","docAbstract":"Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States were developed to characterize the database to be used for a potential assessment by the U.S. Geological Survey (USGS) of oil that would be technically recoverable by the application of enhanced oil recovery methods using injection of carbon dioxide (CO2-EOR). The USGS assessment methodology may require reservoir-level data for the purposes of screening conventional oil reservoirs and projecting CO2-EOR performance in terms of the incremental recoverable oil. The information used in this report is based on reservoir properties from the “Significant Oil and Gas Fields of the United States Database” prepared by Nehring Associates, Inc. (2012). As described by Nehring Associates, Inc., the database “covers all producing provinces (basins) in the United States except the Appalachian Basin and the Cincinnati Arch.”
\nUnder contract to the USGS, INTEK, Inc., developed and applied algorithms to estimate variables useful in projecting EOR performance at the reservoir level and to complete some partial reservoir records of the “Significant Oil and Gas Fields of the United States Database” (Nehring Associates, Inc., 2012). The augmented database is referred to here as the “Comprehensive Resource Database” (CRD).
\nThe CRD play and province classification scheme corresponds to the definitions used in the 1995 USGS National Oil and Gas Assessment (NOGA). The profiles in this report consist of a resource table and a six-part figure showing the variation of reservoir parameters selected because of their importance in the choice of a miscible or immiscible method for CO2-EOR and in the assessment of potential oil recovery using the EOR processes. A subset of these reservoirs may be available for either miscible- or immiscible-type flooding for CO2-EOR. Plays with fewer than 10 oil reservoirs were not graphed and were omitted from the province profiles. For this report and for the purposes of screening reservoirs as candidates for the application of CO2-EOR methods, oil reservoirs must have no more than 10,000 standard cubic feet of natural gas per barrel of oil at surface conditions. Oil-bearing plays presented in this report must contain at least one oil reservoir so defined.
\nThe profile plots allow geologists to evaluate the range of empirical and default values of the oil reservoir characteristics within a play and across plays that belong to the same province in the CRD. For most plays, the default estimates can be identified by the stacking of points at a single value on strip charts in the profiles. Reasonable default values should be within the range of the reservoir parameter values assigned by Nehring Associates, Inc. (2012), to reservoirs of that particular play.
\nEach province profile figure consists of five strip charts and a boxplot. The five strip charts display for individual plays the following reservoir-fluid and reservoir properties: A, oil density (American Petroleum Institute [API] gravity in degrees); B, computed pseudo-Dykstra-Parsons coefficient; C, reservoir porosity (in percent); D, reservoir permeability (in millidarcies); and E, estimates of the original oil in place (OOIP) per unit volume of reservoir rock (in barrels per acre-foot). The OOIP per unit volume of reservoir rock is an indicator of the relative richness of the oil reservoir and is derived from estimates in the CRD of OOIP, reservoir acreage, and net pay. The net pay is the interval of productive reservoir rock. The same data for OOIP per unit volume are graphed as a strip chart (E) and a boxplot (F).
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\"}}]}","edition":"Version 1: Originally posted November 5, 2015: Version 1.1: February 2016","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
MS 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Condit Dam is one of the largest hydroelectric dams ever removed in the USA. Breached in a single explosive event in October 2011, hundreds-of-thousands of cubic metres of sediment washed down the White Salmon River onto spawning grounds of a threatened species, Columbia River tule fall Chinook salmon Oncorhynchus tshawytscha. We investigated over a 3-year period (2010–2012) how dam breaching affected channel morphology, river hydraulics, sediment composition and tule fall Chinook salmon (hereafter ‘tule salmon’) spawning habitat in the lower 1.7 km of the White Salmon River (project area). As expected, dam breaching dramatically affected channel morphology and spawning habitat due to a large load of sediment released from Northwestern Lake. Forty-two per cent of the project area that was previously covered in water was converted into islands or new shoreline, while a large pool near the mouth filled with sediments and a delta formed at the mouth. A two-dimensional hydrodynamic model revealed that pool area decreased 68.7% in the project area, while glides and riffles increased 659% and 530%, respectively. A spatially explicit habitat model found the mean probability of spawning habitat increased 46.2% after dam breaching due to an increase in glides and riffles. Shifting channels and bank instability continue to negatively affect some spawning habitat as sediments continue to wash downstream from former Northwestern Lake, but 300 m of new spawning habitat (river kilometre 0.6 to 0.9) that formed immediately post-breach has persisted into 2015. Less than 10% of tule salmon have spawned upstream of the former dam site to date, but the run sizes appear healthy and stable. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1002/rra.2982","usgsCitation":"Hatten, J.R., Batt, T.R., Skalicky, J., Engle, R., Barton, G., Fosness, R.L., and Warren, J., 2016, Effects of dam removal on Tule Fall Chinook salmon spawning habitat in the White Salmon River, Washington: River Research and Applications, v. 32, no. 7, p. 1481-1492, https://doi.org/10.1002/rra.2982.","productDescription":"12 p.","startPage":"1481","endPage":"1492","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061792","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Condit Dam, Lower White Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.4916229248047,\n 45.931572625309286\n ],\n [\n -121.47033691406249,\n 45.92488619186047\n ],\n [\n -121.49642944335938,\n 45.891919851282076\n ],\n [\n -121.48475646972656,\n 45.84362946735877\n ],\n [\n -121.47994995117188,\n 45.821621922335794\n ],\n [\n -121.50054931640625,\n 45.821621922335794\n ],\n [\n -121.52595520019531,\n 45.86132487333675\n ],\n [\n -121.52595520019531,\n 45.897654534346884\n ],\n [\n -121.49642944335938,\n 45.924408558629004\n ],\n [\n -121.4916229248047,\n 45.931572625309286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-04","publicationStatus":"PW","scienceBaseUri":"5641d1bde4b0831b7d62e737","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batt, Thomas R. tbatt@usgs.gov","contributorId":3432,"corporation":false,"usgs":true,"family":"Batt","given":"Thomas","email":"tbatt@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joseph J.","contributorId":91386,"corporation":false,"usgs":true,"family":"Skalicky","given":"Joseph J.","affiliations":[],"preferred":false,"id":579454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engle, Rod","contributorId":149763,"corporation":false,"usgs":false,"family":"Engle","given":"Rod","affiliations":[{"id":17818,"text":"USFWS, Columbia River Fisheries Program Office","active":true,"usgs":false}],"preferred":false,"id":579455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barton, Gary J. gbarton@usgs.gov","contributorId":1147,"corporation":false,"usgs":true,"family":"Barton","given":"Gary J.","email":"gbarton@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warren, Joe jwarren@usgs.gov","contributorId":149764,"corporation":false,"usgs":true,"family":"Warren","given":"Joe","email":"jwarren@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579458,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159600,"text":"70159600 - 2016 - A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management","interactions":[],"lastModifiedDate":"2016-06-22T12:01:51","indexId":"70159600","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management","docAbstract":"Chytridiomycosis is an emerging disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) that poses a serious threat to frog populations worldwide. Several studies have shown that inoculation of bacterial species Janthinobacterium lividum (Jl) can mitigate the impact of the disease. However, there are many questions regarding this interaction. A mathematical model of a frog population infected with chytridiomycosis is developed to investigate how the inoculation of Jl could reduce the impact of Bd disease on frogs. The model also illustrates the important role of temperature in disease dynamics. The model simulation results suggest possible control strategies for Jl to limit the impact of Bd in various scenarios. However, a better knowledge of Jl life cycle is needed to fully understand the interaction of Jl, Bd, temperature and frogs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2015.09.015","usgsCitation":"Ackleh, A.S., Carter, J., Chellamuthu, V.K., and Ma, B., 2016, A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management: Ecological Modelling, v. 320, p. 158-169, https://doi.org/10.1016/j.ecolmodel.2015.09.015.","productDescription":"12 p.","startPage":"158","endPage":"169","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066659","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471435,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2015.09.015","text":"Publisher Index Page"},{"id":311197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"320","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5645b87ae4b0e2669b30f1c4","contributors":{"authors":[{"text":"Ackleh, Azmy S.","contributorId":119949,"corporation":false,"usgs":true,"family":"Ackleh","given":"Azmy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":579653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chellamuthu, Vinodh K.","contributorId":149806,"corporation":false,"usgs":false,"family":"Chellamuthu","given":"Vinodh","email":"","middleInitial":"K.","affiliations":[{"id":17830,"text":"Department of Mathematics, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":579655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Baoling","contributorId":149807,"corporation":false,"usgs":false,"family":"Ma","given":"Baoling","email":"","affiliations":[{"id":17830,"text":"Department of Mathematics, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":579656,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168420,"text":"70168420 - 2016 - Multi-decadal trends in spring arrival of avian migrants to the central Arctic coast of Alaska: Effects of environmental and ecological factors","interactions":[],"lastModifiedDate":"2018-08-21T15:27:18","indexId":"70168420","displayToPublicDate":"2015-10-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decadal trends in spring arrival of avian migrants to the central Arctic coast of Alaska: Effects of environmental and ecological factors","docAbstract":"Warming in the Arctic has caused the transition from winter to summer to occur weeks earlier over the last half century, yet little is known about whether avian migrants have altered their timing of arrival on breeding areas to match this earlier seasonal transition. Over a 50-yr period, we examined trends in the timing of the first arrival for 16 avian migrant species at the terminus of their northward migration along the central Arctic coast of Alaska and compared these trends to factors potentially influencing migration phenology. Date of first arrival occurred an average of 0.12 d yr−1 or 6 d (range = 3–10 d) earlier across all species and did not differ significantly among species between 1964 and 2013. Local climatic variables, particularly temperature, had a greater effect on a species first arrival date than did large-scale climatic predictors. First arrival date was 1.03 d earlier for every 1°C annual change in temperature, but there was nearly a 2-fold difference in the range of responses across species (0.69–1.33 d °C−1), implying that some species did better than others at timing their arrival with changing temperature. There was weak support for an influence of foraging strategy, migration distance, and flight path on timing of first arrival. Our findings, like others from temperate latitudes, indicate that avian migrants are responsive to changing environmental conditions, though some species appear to be more adaptive than others.
","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/jav.00774","usgsCitation":"Ward, D.H., Helmericks, J., Hupp, J.W., McManus, L., Budde, M., Douglas, D.C., and Tape, K., 2016, Multi-decadal trends in spring arrival of avian migrants to the central Arctic coast of Alaska: Effects of environmental and ecological factors: Journal of Avian Biology, v. 47, no. 2, p. 197-207, https://doi.org/10.1111/jav.00774.","productDescription":"11 p.","startPage":"197","endPage":"207","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064692","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":318026,"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 -152,\n 70\n ],\n [\n -152,\n 71\n ],\n [\n -148,\n 71\n ],\n [\n -148,\n 70\n ],\n [\n -152,\n 70\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-30","publicationStatus":"PW","scienceBaseUri":"56c304cae4b0946c652087b1","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","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":620010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helmericks, J.","contributorId":166882,"corporation":false,"usgs":false,"family":"Helmericks","given":"J.","affiliations":[],"preferred":false,"id":620272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","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":620011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McManus, L.","contributorId":166883,"corporation":false,"usgs":false,"family":"McManus","given":"L.","email":"","affiliations":[{"id":6660,"text":"Western EcoSystems Technology, Inc","active":true,"usgs":false}],"preferred":false,"id":620273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Budde, Michael 0000-0002-9098-2751 mbudde@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":166756,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","email":"mbudde@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":620012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":620013,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tape, K.D.","contributorId":37526,"corporation":false,"usgs":true,"family":"Tape","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":620274,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159440,"text":"70159440 - 2016 - Response of Schoenoplectus acutus and Schoenoplectus californicus at different life-history stages to hydrologic regime","interactions":[],"lastModifiedDate":"2016-02-11T10:32:58","indexId":"70159440","displayToPublicDate":"2015-10-29T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Response of Schoenoplectus acutus and Schoenoplectus californicus at different life-history stages to hydrologic regime","docAbstract":"For wetland restoration success to be maximized, restoration managers need better information regarding how the frequency, depth, and duration of flooding affect soil chemistry and the survival, growth, and morphology of targeted plant species. In a greenhouse study we investigated the impact of four different flooding durations (0 %, 40 %, 60 %, and 100 %) on soil physicochemistry and the responses of seedlings and adults of two species of emergent wetland macrophytes commonly used in restoration efforts (Schoenoplectus acutus and Schoenoplectus californicus). The longest flooding duration, which created more reducing soil conditions, resulted in significantly reduced survival of S. acutus adults (34 ± 21 % survival) and complete mortality of seedlings of both species. Schoenoplectus californicus adults exhibited higher flooding tolerance, showing little impact of flooding on morphology and physiology. A companion field study indicated that S. californicus maintained stem strength regardless of flooding duration or depth, supporting the greenhouse study results. This information serves to improve our understanding of the ecological differences between these species as well as provide restoration managers with better guidelines for targeted elevation and hydrologic regimes for these species in order to enhance the success of restoration plantings and better predict restoration site development.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-015-0713-8","usgsCitation":"Sloey, T.M., Howard, R.J., and Hester, M.W., 2016, Response of Schoenoplectus acutus and Schoenoplectus californicus at different life-history stages to hydrologic regime: Wetlands, v. 36, no. 1, p. 37-46, https://doi.org/10.1007/s13157-015-0713-8.","productDescription":"10 p.","startPage":"37","endPage":"46","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065149","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":310765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-28","publicationStatus":"PW","scienceBaseUri":"56333586e4b048076347eea3","contributors":{"authors":[{"text":"Sloey, Taylor M","contributorId":149516,"corporation":false,"usgs":false,"family":"Sloey","given":"Taylor","email":"","middleInitial":"M","affiliations":[{"id":17763,"text":"University of Louisiana, Lafayette","active":true,"usgs":false}],"preferred":false,"id":578667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":578666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Mark W.","contributorId":9566,"corporation":false,"usgs":true,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":578668,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159441,"text":"70159441 - 2016 - A quantitative framework for estimating risk of collision between marine mammals and boats","interactions":[],"lastModifiedDate":"2016-07-17T23:21:24","indexId":"70159441","displayToPublicDate":"2015-10-29T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A quantitative framework for estimating risk of collision between marine mammals and boats","docAbstract":"Speed regulations of watercraft in protected areas are designed to reduce lethal collisions with wildlife but can have economic consequences. We present a quantitative framework for investigating the risk of deadly collisions between boats and wildlife.
\nWe apply encounter rate theory to demonstrate how marine mammal-boat encounter rate can be used to predict the expected number of deaths associated with management scenarios. We illustrate our approach with management scenarios for two endangered species: the Florida manatee Trichechus manatus latirostris and the North Atlantic right whale Eubalaena glacialis. We used a Monte Carlo simulation approach to demonstrate the uncertainty that is associated with our estimate of relative mortality.
\nWe show that encounter rate increased with vessel speed but that the expected number of encounters varies depending on the boating activities considered. For instance, in a scenario involving manatees and boating activities such as water skiing, the expected number of encounters in a given area (in a fixed time interval) increased with vessel speed. In another scenario in which a vessel made a transit of fixed length the expected number of encounters decreases slightly with boat speed. In both cases the expected number of encounters increased with distanced travelled by the boat. For whales, we found a slight reduction (~0.1%) in the number of encounters under a scenario where speed is unregulated; this reduction, however, is negligible, and overall expected relative mortality was ~30% lower under the scenario with speed regulation. The probability of avoidance by the animal or vessel was set to 0 because of lack of data, but we explored the importance of this parameter on the model predictions. In fact, expected relative mortality under speed regulations decreases even further when the probability of avoidance is a decreasing function of vessel speed.
\nBy applying encounter rate theory to the case of boat collisions with marine mammals, we gained new insights about encounter processes between wildlife and watercraft. Our work emphasizes the importance of considering uncertainty when estimating wildlife mortality. Finally, our findings are relevant to other systems and ecological processes involving the encounter between moving agents.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12447","usgsCitation":"Martin, J., Sabatier, Q., Gowan, T.A., Giraud, C., Gurarie, E., Calleson, S., Ortega-Ortiz, J.G., Deutsch, C., Rycyk, A., and Koslovsky, S., 2016, A quantitative framework for estimating risk of collision between marine mammals and boats: Methods in Ecology and Evolution, v. 7, no. 1, p. 42-50, https://doi.org/10.1111/2041-210X.12447.","productDescription":"9 p.","startPage":"42","endPage":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060059","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12447","text":"Publisher Index Page"},{"id":310761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-12","publicationStatus":"PW","scienceBaseUri":"5633357ce4b048076347ee95","contributors":{"authors":[{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","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":578671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sabatier, Quentin","contributorId":149517,"corporation":false,"usgs":false,"family":"Sabatier","given":"Quentin","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gowan, Timothy A.","contributorId":138595,"corporation":false,"usgs":false,"family":"Gowan","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":578673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giraud, Christophe","contributorId":149518,"corporation":false,"usgs":false,"family":"Giraud","given":"Christophe","email":"","affiliations":[{"id":17764,"text":"Universite Paris Sud","active":true,"usgs":false}],"preferred":false,"id":578674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gurarie, Eliezer","contributorId":149519,"corporation":false,"usgs":false,"family":"Gurarie","given":"Eliezer","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":578675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calleson, Scott","contributorId":149520,"corporation":false,"usgs":false,"family":"Calleson","given":"Scott","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578676,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ortega-Ortiz, Joel G.","contributorId":149521,"corporation":false,"usgs":false,"family":"Ortega-Ortiz","given":"Joel","email":"","middleInitial":"G.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":578677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":578678,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rycyk, Athena","contributorId":149522,"corporation":false,"usgs":false,"family":"Rycyk","given":"Athena","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":578679,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koslovsky, Stacie M.","contributorId":149523,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578680,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70159418,"text":"70159418 - 2016 - Deep divergence and structure in the Tropical Oceanic Pacific: a multilocus phylogeography of a widespread gekkonid lizard (Squamata: Gekkonidae: Gehyra oceanica)","interactions":[],"lastModifiedDate":"2016-01-18T09:32:13","indexId":"70159418","displayToPublicDate":"2015-10-29T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Deep divergence and structure in the Tropical Oceanic Pacific: a multilocus phylogeography of a widespread gekkonid lizard (Squamata: Gekkonidae: Gehyra oceanica)","docAbstract":"The islands of the Tropical Oceanic Pacific (TOP) host both local radiations and widespread, colonizing species. The few phylogeographical analyses of widespread species often point to recent human-aided expansions through the Pacific, suggesting that the communities are recently assembled. Here we apply multilocus data to infer biogeographical history of the gekkonid lizard, Gehyra oceanica, which is widespread, but for which prior analyses suggested a pre-human history and in situ diversification.
\nTropical Oceanic Pacific.
\nWe generated a data set including mtDNA and diagnostic SNPs for 173 individuals of G. oceanica spanning Micronesia, Melanesia, and Polynesia. For a subset of these individuals, we also sequenced nuclear loci. From these data, we performed maximum likelihood and Bayesian inference to reveal major clades. We also performed Bayesian clustering analyses and coalescence–based species delimitation tests to infer the number of species in this area.
\nWe found evidence for six independent evolutionary lineages (candidate species) within G. oceanica that diverged between the Pliocene and the early Pleistocene, with high diversity through northern Melanesia, and pairing of northern Melanesian endemic taxa with widespread lineages across Micronesia and Polynesia.
\nThe islands of northern Melanesia not only have unrecognized diversity, but also were the source of independent expansions of lineages through the more remote northern and eastern Pacific. These results highlight the very different evolutionary histories of island faunas on remote archipelagos versus those across Melanesia and point to the need for more intensive studies of fauna within Melanesia if we are to understand the evolution of diversity across the tropical Pacific.
\nConserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 days of flight with a mean seasonal survivorship of 90.5% (95% CI = 89.2%, 91.9%) whereas spring migration took a mean of 23.5 days of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1,036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1947","usgsCitation":"Lonsdorf, E.V., Thogmartin, W.E., Jacobi, S., Coppen, J., Davis, A.Y., Fox, T.J., Heglund, P.J., Johnson, R., Jones, T., Kenow, K.P., Lyons, J., Luke, K.E., Still, S., and Tavernia, B., 2016, A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation: Ecological Applications, v. 26, no. 4, p. 1136-1153, https://doi.org/10.1890/14-1947.","productDescription":"18 p.","startPage":"1136","endPage":"1153","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059704","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":310752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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study tested the hypothesis that duration of freezing differentially affects whole-body morphometrics of a derived teleost. Whole-body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole-body morphometrics changed as a result of freezing, 23 whole-body morphometrics of age-1 white perch (Morone americana) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P < 0.0001). The first canonical axis reflected long-axis morphometrics, where there was a clear pattern of positive translation along this axis with duration of preservation. Re-classification analysis demonstrated fish were typically assigned to their original preservation class except for fish frozen 100 days, which assigned mostly to frozen 200 days. Morphometric comparisons using frozen fish must be done on fish frozen for identical periods of time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin- and alcohol-preserved specimens.
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Despite the importance of this epizootic, the pattern, dynamics and determinants of WNV spread in its natural hosts remain uncertain. In particular, it is unclear whether the virus encountered major barriers to transmission, or spread in an unconstrained manner, and if specific viral lineages were favored over others indicative of intrinsic differences in fitness. To address these key questions in WNV evolution and ecology we sequenced the complete genomes of approximately 300 avian isolates sampled across the USA between 2001-2012. Phylogenetic analysis revealed a relatively ‘star-like' tree structure, indicative of explosive viral spread in US, although with some replacement of viral genotypes through time. These data are striking in that viral sequences exhibit relatively limited clustering according to geographic region, particularly for those viruses sampled from birds, and no strong phylogenetic association with well sampled avian species. The genome sequence data analysed here also contain relatively little evidence for adaptive evolution, particularly on structural proteins, suggesting that most viral lineages are of similar fitness, and that WNV is well adapted to the ecology of mosquito vectors and diverse avian hosts in the USA. In sum, the molecular evolution of WNV in North America depicts a largely unfettered expansion within a permissive host and geographic population with little evidence of major adaptive barriers.
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beaches","interactions":[],"lastModifiedDate":"2021-08-25T16:49:10.727248","indexId":"70159828","displayToPublicDate":"2015-10-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches","docAbstract":"Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.
","language":"English","publisher":"Elsevier","publisherLocation":"Oxford, UK","doi":"10.1016/j.jenvman.2015.10.011","usgsCitation":"Shively, D., Nevers, M., Breitenbach, C., Phanikumar, M., Przybyla-Kelly, K., Spoljaric, A., and Whitman, R.L., 2016, Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches: Journal of Environmental Management, v. 166, p. 285-293, https://doi.org/10.1016/j.jenvman.2015.10.011.","productDescription":"9 p.","startPage":"285","endPage":"293","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061853","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":311747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"Great Lakes, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.65647888183594,\n 42.03552434403621\n ],\n [\n -87.62626647949217,\n 41.99011884096809\n ],\n [\n -87.615966796875,\n 41.91454130182335\n ],\n [\n -87.59193420410156,\n 41.89767733570708\n ],\n [\n -87.56309509277344,\n 41.80766096027984\n ],\n [\n -87.53700256347656,\n 41.7672146942102\n ],\n [\n -87.52601623535156,\n 41.75338543627463\n ],\n [\n -87.52670288085938,\n 41.73084248230534\n ],\n [\n -87.52395629882812,\n 41.70931682567252\n ],\n [\n -87.53837585449219,\n 41.699063978799174\n ],\n [\n -87.63107299804688,\n 41.840408844786396\n ],\n [\n -87.681884765625,\n 41.99522219923445\n ],\n [\n -87.69218444824219,\n 42.02838405374952\n ],\n [\n -87.68119812011717,\n 42.037054301883806\n ],\n [\n -87.659912109375,\n 42.03603433407788\n ],\n [\n -87.65647888183594,\n 42.03552434403621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"166","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565d8140e4b071e7ea543480","contributors":{"authors":[{"text":"Shively, Dawn","contributorId":150065,"corporation":false,"usgs":false,"family":"Shively","given":"Dawn","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":580617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breitenbach, Cathy","contributorId":150066,"corporation":false,"usgs":false,"family":"Breitenbach","given":"Cathy","email":"","affiliations":[{"id":17899,"text":"Chicago Park District","active":true,"usgs":false}],"preferred":false,"id":580619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":580623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Przybyla-Kelly, Kasia","contributorId":150067,"corporation":false,"usgs":false,"family":"Przybyla-Kelly","given":"Kasia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley M.","contributorId":150068,"corporation":false,"usgs":false,"family":"Spoljaric","given":"Ashley M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitman, Richard L.","contributorId":150069,"corporation":false,"usgs":false,"family":"Whitman","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":580622,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159410,"text":"70159410 - 2016 - Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","interactions":[],"lastModifiedDate":"2016-01-11T10:54:13","indexId":"70159410","displayToPublicDate":"2015-10-27T11:30:00","publicationYear":"2016","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":"Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","docAbstract":"Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.
\nGreater sage-grouse Centrocercus urophasianus, hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information.
\nHerein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.
\nWe also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance.
\nSynthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species, and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.
\nDemand for woody biomass fuels is increasing amidst concerns about global energy security and climate change, but there may be negative implications of increased harvesting for forest ecosystem functions and their benefits to society (ecosystem services). Using new methods for assessing ecosystem services based on long-term experimental research, post-harvest changes in ten potential benefits were assessed for ten first-order northern hardwood forest watersheds at three long-term experimental research sites in northeastern North America. As expected, we observed near-term tradeoffs between biomass provision and greenhouse gas regulation, as well as tradeoffs between intensive harvest and the capacity of the forest to remediate nutrient pollution. In both cases, service provision began to recover along with the regeneration of forest vegetation; in the case of pollution remediation, the service recovered to pre-harvest levels within 10 years. By contrast to these two services, biomass harvesting had relatively nominal and transient impacts on other ecosystem services. Our results are sensitive to empirical definitions of societal demand, including methods for scaling societal demand to ecosystem units, which are often poorly resolved. Reducing uncertainty around these parameters can improve confidence in our results and increase their relevance for decision-making. Our synthesis of long-term experimental studies provides insights on the social-ecological resilience of managed forest ecosystems to multiple drivers of change.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York, NY","doi":"10.1007/s10021-015-9928-z","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Caputo, J., Beier, C.D., Groffman, P., Burns, D.A., Beall, F.D., Hazlett, P.W., and Yorks, T.E., 2016, Effects of harvesting forest biomass on water and climate regulation services: A synthesis of long-term ecosystem experiments in eastern North America: Ecosystems, v. 19, no. 2, p. 271-283, https://doi.org/10.1007/s10021-015-9928-z.","productDescription":"13 p.","startPage":"271","endPage":"283","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065229","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320494,"type":{"id":15,"text":"Index 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]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-27","publicationStatus":"PW","scienceBaseUri":"571f3fb7e4b071321fe56a21","contributors":{"authors":[{"text":"Caputo, Jesse","contributorId":168871,"corporation":false,"usgs":false,"family":"Caputo","given":"Jesse","affiliations":[{"id":25371,"text":"Dept of Forest & Natural Resources Mgmt, SUNY College of ESF","active":true,"usgs":false}],"preferred":false,"id":627576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beier, Colin D","contributorId":168872,"corporation":false,"usgs":false,"family":"Beier","given":"Colin","email":"","middleInitial":"D","affiliations":[{"id":25371,"text":"Dept of Forest & Natural Resources Mgmt, SUNY College of ESF","active":true,"usgs":false}],"preferred":false,"id":627577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Groffman, Peter M","contributorId":168873,"corporation":false,"usgs":false,"family":"Groffman","given":"Peter M","affiliations":[{"id":25372,"text":"Senior Research Scientist, Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":627578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beall, Frederick D","contributorId":168874,"corporation":false,"usgs":false,"family":"Beall","given":"Frederick","email":"","middleInitial":"D","affiliations":[{"id":25373,"text":"Research Forester, Natual Resources Canada - Canada Forest Service","active":true,"usgs":false}],"preferred":false,"id":627580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hazlett, Paul W.","contributorId":101177,"corporation":false,"usgs":true,"family":"Hazlett","given":"Paul","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":627581,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yorks, Thad E","contributorId":168875,"corporation":false,"usgs":false,"family":"Yorks","given":"Thad","email":"","middleInitial":"E","affiliations":[{"id":25374,"text":"Environmental Biology Program, Cazenovia College NY","active":true,"usgs":false}],"preferred":false,"id":627582,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156695,"text":"70156695 - 2016 - Engagement with indigenous peoples and honoring traditional knowledge systems","interactions":[],"lastModifiedDate":"2016-12-14T12:22:53","indexId":"70156695","displayToPublicDate":"2015-10-26T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Engagement with indigenous peoples and honoring traditional knowledge systems","docAbstract":"The organizers of the 2014 US National Climate Assessment (NCA) made a concerted effort to reach out to and collaborate with Indigenous peoples, resulting in the most comprehensive information to date on climate change impacts to Indigenous peoples in a US national assessment. Yet, there is still much room for improvement in assessment processes to ensure adequate recognition of Indigenous perspectives and Indigenous knowledge systems. This article discusses the process used in creating the Indigenous Peoples, Land, and Resources NCA chapter by a team comprised of tribal members, agencies, academics, and non-governmental organizations, who worked together to solicit, collect, and synthesize traditional knowledges and data from a diverse array of Indigenous communities across the US. It also discusses the synergy and discord between traditional knowledge systems and science and the emergence of cross-cutting issues and vulnerabilities for Indigenous peoples. The challenges of coalescing information about climate change and its impacts on Indigenous communities are outlined along with recommendations on the types of information to include in future assessment outputs. We recommend that future assessments – not only NCA, but other relevant local, regional, national, and international efforts aimed at the translation of climate information and assessments into meaningful actions – should support integration of Indigenous perspectives in a sustained way that builds respectful relationships and effectively engages Indigenous communities. Given the large number of tribes in the US and the current challenges and unique vulnerabilities of Indigenous communities, a special report focusing solely on climate change and Indigenous peoples is warranted.
This article is part of a special issue on “The National Climate Assessment: Innovations in Science and Engagement” edited by Katharine Jacobs, Susanne Moser, and James Buizer.
The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jme/tjv150","usgsCitation":"Ludwig, A., Ginsberg, H., Hickling, G., and Ogden, N.H., 2016, A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae): Journal of Medical Entomology, v. 53, no. 1, p. 99-115, https://doi.org/10.1093/jme/tjv150.","productDescription":"17 p.","startPage":"99","endPage":"115","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":486932,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/144","text":"External Repository"},{"id":312845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-26","publicationStatus":"PW","scienceBaseUri":"567bd3bae4b0a04ef491a1ee","contributors":{"authors":[{"text":"Ludwig, Antoinette","contributorId":147666,"corporation":false,"usgs":false,"family":"Ludwig","given":"Antoinette","email":"","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":572281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickling, Graham J.","contributorId":88639,"corporation":false,"usgs":true,"family":"Hickling","given":"Graham J.","affiliations":[],"preferred":false,"id":572283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177904,"text":"70177904 - 2016 - Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?","interactions":[],"lastModifiedDate":"2016-12-06T13:03:19","indexId":"70177904","displayToPublicDate":"2015-10-26T09:15:00","publicationYear":"2016","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":"Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?","docAbstract":"Freshwater shrimps are an important biotic component of tropical ecosystems. However, they can have a low probability of detection when abundances are low. We sampled 3 of the most common freshwater shrimp species, Macrobrachium olfersii, Macrobrachium carcinus, and Macrobrachium heterochirus, and used occupancy modeling and logistic regression models to improve our limited knowledge of distribution of these cryptic species by investigating both local- and landscape-scale effects at La Selva Biological Station in Costa Rica. Local-scale factors included substrate type and stream size, and landscape-scale factors included presence or absence of regional groundwater inputs. Capture rates for 2 of the sampled species (M. olfersii and M. carcinus) were sufficient to compare the fit of occupancy models. Occupancy models did not converge for M. heterochirus, but M. heterochirus had high enough occupancy rates that logistic regression could be used to model the relationship between occupancy rates and predictors. The best-supported models for M. olfersii and M. carcinus included conductivity, discharge, and substrate parameters. Stream size was positively correlated with occupancy rates of all 3 species. High stream conductivity, which reflects the quantity of regional groundwater input into the stream, was positively correlated with M. olfersii occupancy rates. Boulder substrates increased occupancy rate of M. carcinus and decreased the detection probability of M. olfersii. Our models suggest that shrimp distribution is driven by factors that function at local (substrate and discharge) and landscape (conductivity) scales.
","language":"English","publisher":"Society for Freshwater Science","doi":"10.1086/684486","usgsCitation":"Snyder, M., Freeman, M., Purucker, S.T., and Pringle, C.M., 2016, Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?: Freshwater Science, v. 35, no. 1, p. 80-90, https://doi.org/10.1086/684486.","productDescription":"11 p.","startPage":"80","endPage":"90","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062926","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":330405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"La Selva Biological Station, Saltito River, Salto River, Sura River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.09004211425781,\n 10.3270789193731\n ],\n [\n -84.09004211425781,\n 10.530007387221294\n ],\n [\n -83.92833709716797,\n 10.530007387221294\n ],\n [\n -83.92833709716797,\n 10.3270789193731\n ],\n [\n -84.09004211425781,\n 10.3270789193731\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f4e4b0f497e79a5a8d","contributors":{"authors":[{"text":"Snyder, Marcia","contributorId":176290,"corporation":false,"usgs":false,"family":"Snyder","given":"Marcia","affiliations":[],"preferred":false,"id":652095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":652094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Purucker, S. Thomas","contributorId":176291,"corporation":false,"usgs":false,"family":"Purucker","given":"S.","email":"","middleInitial":"Thomas","affiliations":[],"preferred":false,"id":652096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pringle, Catherine M.","contributorId":176292,"corporation":false,"usgs":false,"family":"Pringle","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169122,"text":"70169122 - 2016 - Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass","interactions":[],"lastModifiedDate":"2017-01-10T13:17:12","indexId":"70169122","displayToPublicDate":"2015-10-24T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass","docAbstract":"EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0151935","usgsCitation":"Goring, S., Mladenoff, D.J., Cogbill, C., Record, S., Paciorek, C.J., Dietze, M.C., Dawson, A., Matthes, J., McLachlan, J.S., and Williams, J.W., 2016, Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass: PLoS ONE, v. 11, no. 12, e0151935; 34 p., https://doi.org/10.1371/journal.pone.0151935.","productDescription":"e0151935; 34 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066196","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":471443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0151935","text":"Publisher Index Page"},{"id":319089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Jaclyn","contributorId":167494,"corporation":false,"usgs":false,"family":"Matthes","given":"Jaclyn","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":623106,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McLachlan, Jason S.","contributorId":167179,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":623107,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":623098,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70168405,"text":"70168405 - 2016 - Metabolism correlates with variation in post-natal growth rate among songbirds at three latitudes","interactions":[],"lastModifiedDate":"2016-12-16T10:50:10","indexId":"70168405","displayToPublicDate":"2015-10-20T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Metabolism correlates with variation in post-natal growth rate among songbirds at three latitudes","docAbstract":"1. Variation in post-natal growth rates is substantial among organisms and especially strong among latitudes because tropical and south temperate species typically have slower growth than north temperate relatives. Metabolic rate is thought to be a critical mechanism underlying growth rates after accounting for allometric effects of body mass. However, comparative tests on a large spatial scale are lacking, and the importance of metabolism for growth rates remains unclear both within and particularly across latitudes.
\n2. Songbirds exhibit strong interspecific variation in growth rates across geographic space, although within latitudes an association between metabolic rate and growth rate has not always been observed. Moreover, the hypothesis that differences in growth rates across latitudes reflect underlying differences in metabolism is untested. Here, we investigate these possibilities across north temperate, south temperate and tropical study sites.
\n3. Phylogenetic analyses showed that, for a given body mass, metabolic rates of north temperate nestlings were higher than tropical and south temperate species. Metabolic rates controlled for body mass correlated with post-natal growth rates both within and among latitudes. Offspring body mass explained substantial residual variation in growth rates as expected under classic allometric theory.
\n4. Our results suggest that variation in metabolic rates has an important influence on broad patterns of avian growth rates at a global scale. We suggest further studies that address the ecological and physiological costs and consequences of variation in metabolism and growth rates.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2435.12548","usgsCitation":"Ton, R., and Martin, T.E., 2016, Metabolism correlates with variation in post-natal growth rate among songbirds at three latitudes: Functional Ecology, v. 30, no. 5, p. 743-748, https://doi.org/10.1111/1365-2435.12548.","productDescription":"6 p.","startPage":"743","endPage":"748","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056706","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471444,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.12548","text":"Publisher Index Page"},{"id":317982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-20","publicationStatus":"PW","scienceBaseUri":"56bf1057e4b06458514b6918","contributors":{"authors":[{"text":"Ton, Riccardo","contributorId":138795,"corporation":false,"usgs":false,"family":"Ton","given":"Riccardo","email":"","affiliations":[],"preferred":false,"id":620043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619967,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}