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}]}} ,{"id":70159200,"text":"70159200 - 2016 - Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","interactions":[],"lastModifiedDate":"2016-01-11T10:52:23","indexId":"70159200","displayToPublicDate":"2015-10-20T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","docAbstract":"A baseline assessment of the Missouri River fish community and species-specific habitat use patterns conducted from 1996 to 1998 provided the first comprehensive analysis of Missouri River benthic fish population trends and habitat use in the Missouri and Lower Yellowstone rivers, exclusive of reservoirs, and provided the foundation for the present Pallid Sturgeon Population Assessment Program (PSPAP). Data used in such studies are frequently zero inflated. To address this issue, the zero-inflated Poisson (ZIP) model was applied. This follow-up study is based on PSPAP data collected up to 15 years later along with new understanding of how habitat characteristics among and within bends affect habitat use of fish species targeted by PSPAP, including pallid sturgeon. This work demonstrated that a large-scale, large-river, PSPAP-type monitoring program can be an effective tool for assessing population trends and habitat usage of large-river fish species. Using multiple gears, PSPAP was effective in monitoring shovelnose and pallid sturgeons, sicklefin, shoal and sturgeon chubs, sand shiner, blue sucker and sauger. For all species, the relationship between environmental variables and relative abundance differed, somewhat, among river segments suggesting the importance of the overall conditions of Upper and Middle Missouri River and Lower Missouri and Kansas rivers on the habitat usage patterns exhibited. Shoal and sicklefin chubs exhibited many similar habitat usage patterns; blue sucker and shovelnose sturgeon also shared similar responses. For pallid sturgeon, the primary focus of PSPAP, relative abundance tended to increase in Upper and Middle Missouri River paralleling stocking efforts, whereas no evidence of an increasing relative abundance was found in the Lower Missouri River despite stocking.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.2846","usgsCitation":"Wildhaber, M.L., Yang, W., and Arab, A., 2016, Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment: River Research and Applications, v. 32, p. 36-65, https://doi.org/10.1002/rra.2846.","productDescription":"30 p.","startPage":"36","endPage":"65","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055609","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":310114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Kansas River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.99414062499999,\n 45.72152152227954\n ],\n [\n -113.719482421875,\n 49.49667452747045\n ],\n [\n -99.7119140625,\n 49.01625665778159\n ],\n [\n -96.591796875,\n 45.90529985724796\n ],\n [\n -94.932861328125,\n 43.52465500687185\n ],\n [\n -93.09814453125,\n 40.60561205826018\n ],\n [\n -89.97802734375,\n 38.865374851611634\n ],\n [\n -89.835205078125,\n 36.50963615733049\n ],\n [\n -94.537353515625,\n 36.500805317604794\n ],\n [\n -102.095947265625,\n 39.99395569397331\n ],\n [\n -114.08203125,\n 43.96119063892024\n ],\n [\n -113.99414062499999,\n 45.72152152227954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-04","publicationStatus":"PW","scienceBaseUri":"562757a8e4b0d158f5926505","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":577837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Wen-Hsi","contributorId":45228,"corporation":false,"usgs":true,"family":"Yang","given":"Wen-Hsi","email":"","affiliations":[],"preferred":false,"id":577838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Ali","contributorId":75002,"corporation":false,"usgs":true,"family":"Arab","given":"Ali","email":"","affiliations":[],"preferred":false,"id":577839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159637,"text":"70159637 - 2016 - Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment","interactions":[],"lastModifiedDate":"2018-08-08T10:38:02","indexId":"70159637","displayToPublicDate":"2015-10-16T03:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment","docAbstract":"The Northern snakehead, Channa argus (Cantor), is a non-native predatory fish that has become established regionally in some temperate freshwater habitats within the United States. Over the past decade, Northern snakehead populations have developed within aquatic ecosystems throughout the eastern USA, including the Potomac River system within Virginia, Maryland and Washington, D.C. Since this species was initially observed in this region in 2002, the population has expanded considerably (Odenkirk & Owens 2007). In the Chesapeake Bay watershed, populations of Northern snakehead exist in the lower Potomac River and Rappahannock Rivers on the Western shore of the Bay, and these fish have also been found in middle or upper reaches of river systems on the Eastern shore of the Bay, including the Nanticoke and Wicomico Rivers among others. Over the past several years, many aspects of Northern snakehead life history in the Potomac River have been described, including range and dispersal patterns, microhabitat selection and diet (Lapointe, Thorson & Angermeier 2010; Saylor, Lapointe & Angermeier 2012; Lapointe, Odenkirk & Angermeier 2013). However, comparatively little is known about their health status including susceptibility to parasitism and disease and their capacity to serve as reservoirs of disease for native wildlife. Although considered hardy by fisheries biologists, snakehead fish have demonstrated susceptibility to a number of described piscine diseases within their native range and habitat in Asia. Reported pathogens of significance in snakehead species in Asia include snakehead rhabdovirus (Lio-Po et al. 2000), aeromonad bacteria (Zheng, Cao & Yang 2012), Nocardia (Wang et al. 2007) andMycobacterium spp. (Chinabut, Limsuwan & Chantatchakool 1990; ). Mycobacterial isolates recovered from another snakehead species (Channa striata) in the previous studies have included M. marinum and M. fortuitum, as identified through molecular-based diagnostics (Puttinaowarat et al. 2002). We have conducted health screenings of Northern snakehead from the Potomac River system over the past several years and have detected few associated pathogens. Typical observations have largely consisted of incidental identification of parasitism with protozoal, monogenean or trematode organisms (unpublished data). We have also identified largemouth bass virus (LMBV) in clinically normal Northern snakehead collected from the Potomac River (Iwanowicz et al. 2013). Continued research concerning these and other pathogens of this introduced species is important to fully understand the potential impacts of these fish on indigenous wildlife and aquatic ecosystems.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/jfd.12412","usgsCitation":"Densmore, C.L., Iwanowicz, L., Henderson, A., Iwanowicz, D.D., and Odenkirk, J., 2016, Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment: Journal of Fish Diseases, v. 39, no. 6, p. 771-775, https://doi.org/10.1111/jfd.12412.","productDescription":"5 p.","startPage":"771","endPage":"775","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065068","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":311384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Potomac River, Pohick Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.12471008300781,\n 38.6895295540336\n ],\n [\n -77.13912963867188,\n 38.6999799615129\n ],\n [\n -77.16041564941406,\n 38.70667813760075\n ],\n [\n -77.19543457031249,\n 38.6999799615129\n ],\n [\n -77.20333099365233,\n 38.674253135311496\n ],\n [\n -77.19509124755858,\n 38.662726661586646\n ],\n [\n -77.17655181884766,\n 38.65387950468725\n ],\n [\n -77.15835571289062,\n 38.64369051578083\n ],\n [\n -77.13912963867188,\n 38.628940728833264\n ],\n [\n -77.10479736328125,\n 38.622503507032874\n ],\n [\n -77.07664489746094,\n 38.626258623311166\n ],\n [\n -77.05432891845703,\n 38.64288606020925\n ],\n [\n -77.05982208251953,\n 38.67452117076055\n ],\n [\n -77.08076477050781,\n 38.691673351832996\n ],\n [\n -77.12471008300781,\n 38.6895295540336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-16","publicationStatus":"PW","scienceBaseUri":"564b0c55e4b0ebfbef0d3172","contributors":{"authors":[{"text":"Densmore, Christine L. 0000-0001-6440-0781 cdensmore@usgs.gov","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":4560,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine","email":"cdensmore@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":579837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":579896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Anne ahenderson@usgs.gov","contributorId":4373,"corporation":false,"usgs":true,"family":"Henderson","given":"Anne","email":"ahenderson@usgs.gov","affiliations":[],"preferred":true,"id":579897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":579898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Odenkirk, J.S.","contributorId":149880,"corporation":false,"usgs":false,"family":"Odenkirk","given":"J.S.","affiliations":[],"preferred":false,"id":579899,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158932,"text":"70158932 - 2016 - Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model","interactions":[],"lastModifiedDate":"2016-06-02T10:32:38","indexId":"70158932","displayToPublicDate":"2015-10-13T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model","docAbstract":"There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.01179","collaboration":"Prepared in collaboration with U.S. Fish and Wildlife Service","usgsCitation":"Crimmins, S.M., Walleser, L.R., Hertel, D.R., McKann, P., Rohweder, J.J., and Thogmartin, W.E., 2016, Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model: Ecography, v. 39, no. 6, p. 524-532, https://doi.org/10.1111/ecog.01179.","productDescription":"9 p.","startPage":"524","endPage":"532","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057940","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":309843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.8115234375,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 42.71473218539458\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-30","publicationStatus":"PW","scienceBaseUri":"561e1d28e4b0cdb063e59ca5","contributors":{"authors":[{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walleser, Liza R. lwalleser@usgs.gov","contributorId":4329,"corporation":false,"usgs":true,"family":"Walleser","given":"Liza","email":"lwalleser@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hertel, Dan R.","contributorId":149113,"corporation":false,"usgs":false,"family":"Hertel","given":"Dan","email":"","middleInitial":"R.","affiliations":[{"id":17647,"text":"United States Fish and Wildlife Service, Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":576940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKann, Patrick C.","contributorId":14940,"corporation":false,"usgs":true,"family":"McKann","given":"Patrick C.","affiliations":[],"preferred":false,"id":576941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":576942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":576937,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159529,"text":"70159529 - 2016 - Effects of temperature on Renibacterium salmoninarum infection and transmission potential in Chinook salmon, Oncorhynchus tshawytscha (Walbaum)","interactions":[],"lastModifiedDate":"2016-12-19T11:56:02","indexId":"70159529","displayToPublicDate":"2015-10-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Effects of temperature on Renibacterium salmoninarum infection and transmission potential in Chinook salmon, Oncorhynchus tshawytscha (Walbaum)","docAbstract":"Renibacterium salmoninarum is a significant pathogen of salmonids and the causative agent of bacterial kidney disease (BKD). Water temperature affects the replication rate of pathogens and the function of the fish immune system to influence the progression of disease. In addition, rapid shifts in temperature may serve as stressors that reduce host resistance. This study evaluated the effect of shifts in water temperature on established R. salmoninarum infections. We challenged Chinook salmon with R. salmoninarum at 12°C for 2 weeks and then divided the fish into three temperature groups (8, 12 and 15°C). Fish in the 8°C group had significantly higher R. salmoninarum-specific mortality, kidney R. salmoninarum loads and bacterial shedding rates relative to the fish held at 12 or 15°C. There was a trend towards suppressed bacterial load and shedding in the 15°C group, but the results were not significant. Bacterial load was a significant predictor of shedding for the 8 and 12°C groups but not for the 15°C group. Overall, our results showed little effect of temperature stress on the progress of infection, but do support the conclusion that cooler water temperatures contribute to infection progression and increased transmission potential in Chinook salmon infected with R. salmoninarum.
","language":"English","publisher":"Blackwell Science","doi":"10.1111/jfd.12409","usgsCitation":"Purcell, M., McKibben, C.L., Pearman-Gillman, S., Elliott, D.G., and Winton, J., 2016, Effects of temperature on Renibacterium salmoninarum infection and transmission potential in Chinook salmon, Oncorhynchus tshawytscha (Walbaum): Journal of Fish Diseases, v. 39, no. 7, p. 787-798, https://doi.org/10.1111/jfd.12409.","productDescription":"12 p.","startPage":"787","endPage":"798","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065789","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311135,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-09","publicationStatus":"PW","scienceBaseUri":"5641d1bee4b0831b7d62e73a","contributors":{"authors":[{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":138685,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":579408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKibben, Constance L. cmckibben@usgs.gov","contributorId":3831,"corporation":false,"usgs":true,"family":"McKibben","given":"Constance","email":"cmckibben@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearman-Gillman, Schuyler spearman-gillman@usgs.gov","contributorId":149756,"corporation":false,"usgs":true,"family":"Pearman-Gillman","given":"Schuyler","email":"spearman-gillman@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":579411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579412,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winton, James R. jwinton@usgs.gov","contributorId":149757,"corporation":false,"usgs":true,"family":"Winton","given":"James R.","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":579413,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158943,"text":"70158943 - 2016 - Measuring spatial variation in secondary production and food quality using a common consumer approach in Lake Erie","interactions":[],"lastModifiedDate":"2016-06-02T10:31:07","indexId":"70158943","displayToPublicDate":"2015-10-08T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Measuring spatial variation in secondary production and food quality using a common consumer approach in Lake Erie","docAbstract":"Lake Erie is a large lake straddling the border of the U.S. and Canada that has become increasingly eutrophic in recent years. Eutrophication is particularly focused in the shallow western basin. The western basin of Lake Erie is hydrodynamically similar to a large estuary, with riverine inputs from the Detroit and Maumee Rivers mixing together and creating gradients in chemical and physical conditions. This study was driven by two questions: How does secondary production and food quality for consumers vary across this large mixing zone? and Are there correlations between cyanobacterial abundance and secondary production or food quality for consumers? Measuring spatial and temporal variation in secondary production and food quality is difficult for a variety of logistical reasons, so here a common consumer approach was used. In a common consumer approach, individuals of a single species are raised under similar conditions until placed in the field across environmental gradients of interest. After some period of exposure, the response of that common consumer is measured to provide an index of spatial variation in conditions. Here, a freshwater mussel (Lampsilis siliquoidea) was deployed at 32 locations that spanned habitat types and a gradient in cyanobacterial abundance in the western basin of Lake Erie to measure spatial variation in growth (an index of secondary production) and fatty acid (FA) content (an index of food quality). We found secondary production was highest within the Maumee rivermouth and lowest in the open waters of the lake. Mussel tissues in the Maumee rivermouth also included more eicosapentaenoic and docosapentaenoic fatty acids (EPA and DPA, respectively), but fewer bacterial FAs, suggesting more algae at the base of the food web in the Maumee rivermouth compared to open lake sites. The satellite-derived estimate of cyanobacterial abundance was not correlated to secondary production, but was positively related to EPA and DPA content in the mussels, suggesting more of these important FAs in locations with more cyanobacteria. These results suggest that growth of secondary consumers and the availability of important fatty acids in the western basin are centered on the Maumee rivermouth.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0440","collaboration":"Prepared in collaboration with National Oceanic and Atmospheric Administration","usgsCitation":"Larson, J.H., Richardson, W.B., Evans, M.A., Schaeffer, J., Wynne, T., Bartsch, M., Bartsch, L., Nelson, J., and Vallazza, J., 2016, Measuring spatial variation in secondary production and food quality using a common consumer approach in Lake Erie: Ecological Applications, v. 26, no. 3, p. 873-885, https://doi.org/10.1890/15-0440.","productDescription":"13 p.","startPage":"873","endPage":"885","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063448","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471445,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1890/15-0440","text":"External Repository"},{"id":438649,"rank":0,"type":{"id":30,"text":"Data 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Rocky reefs in 45 many temperate areas worldwide serve as habitat for canopy forming macroalgae and these 46 structure forming species of kelps (order Laminariales) often serve as important habitat for a great 47 diversity of species. Macrocystis pyrifera is the most common canopy forming kelp species found 48 along the coast of California but the distribution and abundance of M. pyrifera varies in space and 49 time. The purpose of this study is to determine what environmental parameters are correlated with 50 the spatial and temporal persistence of M. pyrifera along the central coast of California and how 51 well those environmental parameters can be used to predict areas where M. pyrifera is more likely 52 to persist. Nine environmental variables considered in this study included depth of the seafloor, 53 structure of the rocky reef, proportion of rocky reef, size of kelp patch, biomass of kelp within a 54 patch, distance from the edge of a kelp patch, sea surface temperature, wave orbital velocities, and 55 population connectivity of individual kelp patches. Using a generalized linear mixed effects model 56 (GLMM), the persistence of M. pyrifera was significantly associated with seven of the nine 57 variables considered: depth, complexity of the rocky reef, proportion of rock, patch biomass, 58 distance from the edge of a patch, population connectivity, and wave-orbital velocities. These 59 seven environmental variables were then used to predict the persistence of kelp across the central 60 coast and these predictions were compared to a reserved dataset of M. pyrifera persistence, which 61 was not used in the creation of the GLMM. The environmental variables were shown to accurately 62 predict the persistence of M. pyrifera within the central coast of California (r = 0.71, P<0.001). 63 Because persistence of giant kelp is important to the community structure of kelp forests, 64 understanding those factors that support persistent populations of M. pyrifera will enable more 65 effective management of these ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0267.1","collaboration":"Prepared in collaboration with University of California at Santa Cruz, University of California at Los Angeles","usgsCitation":"Young, M.A., Cavanaugh, K.C., Bell, T.W., Raimondi, P.T., Edwards, C.A., Drake, P.T., Erikson, L., and Storlazzi, C.D., 2016, Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California: Ecology, v. 86, no. 1, p. 45-60, https://doi.org/10.1890/15-0267.1.","productDescription":"16 p.","startPage":"45","endPage":"60","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063935","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502615,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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On 1 April 2014, this region was struck by a large earthquake following a two week long series of foreshocks. This study combines a wide range of observations, including geodetic, tsunami, and seismic data, to produce a reliable kinematic slip model of the Mw=8.1 main shock and a static slip model of the Mw=7.7 aftershock. We use a novel Bayesian modeling approach that accounts for uncertainty in the Green's functions, both static and dynamic, while avoiding nonphysical regularization. The results reveal a sharp slip zone, more compact than previously thought, located downdip of the foreshock sequence and updip of high-frequency sources inferred by back-projection analysis. Both the main shock and the Mw=7.7 aftershock did not rupture to the trench and left most of the seismic gap unbroken, leaving the possibility of a future large earthquake in the region.
","language":"English","publisher":"AGU","doi":"10.1002/2015GL065402","usgsCitation":"Duputel, Z., Jiang, J., Jolivet, R., Simons, M., Rivera, L., Ampuero, J., Riel, B., Owen, S.E., Moore, A.W., Samsonov, S.V., Ortega Culaciati, F., and Minson, S.E., 2016, The Iquique earthquake sequence of April 2014: Bayesian modeling accounting for prediction uncertainty: Geophysical Research Letters, v. 42, no. 19, p. 7949-7957, https://doi.org/10.1002/2015GL065402.","productDescription":"9 p.","startPage":"7949","endPage":"7957","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068742","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471446,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065402","text":"Publisher Index Page"},{"id":325568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, 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Canada","active":true,"usgs":false}],"preferred":false,"id":643330,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ortega Culaciati, Francisco","contributorId":173109,"corporation":false,"usgs":false,"family":"Ortega Culaciati","given":"Francisco","email":"","affiliations":[{"id":27153,"text":"Departamento de Geof ́ısica, Universidad de Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":643331,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":643320,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70158602,"text":"70158602 - 2016 - Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896)","interactions":[],"lastModifiedDate":"2016-08-17T08:46:44","indexId":"70158602","displayToPublicDate":"2015-10-01T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896)","docAbstract":"The Central Texas endemic freshwater mussel, Quadrula mitchelli (Simpson in Dall, 1896), had been presumed extinct until relict populations were recently rediscovered. To help guide ongoing and future conservation efforts focused on Q. mitchelli we set out to resolve several uncertainties regarding its evolutionary history, specifically its unknown generic position and untested species boundaries. We designed a molecular matrix consisting of two loci (cytochrome c oxidase subunit I and internal transcribed spacer I) and 57 terminal taxa to test the generic position of Q. mitchelli using Bayesian inference and maximum likelihood phylogenetic reconstruction. We also employed two Bayesian species validation methods to test five a priori species models (i.e. hypotheses of species delimitation). Our study is the first to test the generic position of Q.mitchelli and we found robust support for its inclusion in the genusFusconaia. Accordingly, we introduce the binomial, Fusconaia mitchelli comb. nov., to accurately represent the systematic position of the species. We resolved F. mitchelli individuals in two well supported and divergent clades that were generally distinguished as distinct species using Bayesian species validation methods, although alternative hypotheses of species delineation were also supported. Despite strong evidence of genetic isolation within F. mitchelli, we do not advocate for species-level status of the two clades as they are allopatrically distributed and no morphological, behavioral, or ecological characters are known to distinguish them. These results are discussed in the context of the systematics, distribution, and conservation ofF. mitchelli.
","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-015-0780-7","usgsCitation":"Pfeiffer, J.M., Johnson, N.A., Randklev, C.R., Howells, R.G., and Williams, J.D., 2016, Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896): Conservation Genetics, v. 17, no. 2, p. 279-292, https://doi.org/10.1007/s10592-015-0780-7.","productDescription":"14 p.","startPage":"279","endPage":"292","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059406","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":309395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-26","publicationStatus":"PW","scienceBaseUri":"563486b7e4b048076347fb22","contributors":{"authors":[{"text":"Pfeiffer, John M. III","contributorId":148964,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John","suffix":"III","email":"","middleInitial":"M.","affiliations":[{"id":17607,"text":"Cherokee Nation Technology Solutions, Contracted to U.S. Geological Survey, Southeast Ecological Science Center","active":true,"usgs":false}],"preferred":false,"id":576273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":576272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Randklev, Charles R.","contributorId":25470,"corporation":false,"usgs":true,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":576274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howells, Robert G.","contributorId":21072,"corporation":false,"usgs":true,"family":"Howells","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":576275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, James D.","contributorId":17690,"corporation":false,"usgs":false,"family":"Williams","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":576276,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157162,"text":"70157162 - 2016 - Assessing accuracy and precision for field and laboratory data: a perspective in ecosystem restoration","interactions":[],"lastModifiedDate":"2016-01-18T09:22:20","indexId":"70157162","displayToPublicDate":"2015-10-01T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing accuracy and precision for field and laboratory data: a perspective in ecosystem restoration","docAbstract":"Unlike most laboratory studies, rigorous quality assurance/quality control (QA/QC) procedures may be lacking in ecosystem restoration (“ecorestoration”) projects, despite legislative mandates in the United States. This is due, in part, to ecorestoration specialists making the false assumption that some types of data (e.g. discrete variables such as species identification and abundance classes) are not subject to evaluations of data quality. Moreover, emergent behavior manifested by complex, adapting, and nonlinear organizations responsible for monitoring the success of ecorestoration projects tend to unconsciously minimize disorder, QA/QC being an activity perceived as creating disorder. We discuss similarities and differences in assessing precision and accuracy for field and laboratory data. Although the concepts for assessing precision and accuracy of ecorestoration field data are conceptually the same as laboratory data, the manner in which these data quality attributes are assessed is different. From a sample analysis perspective, a field crew is comparable to a laboratory instrument that requires regular “recalibration,” with results obtained by experts at the same plot treated as laboratory calibration standards. Unlike laboratory standards and reference materials, the “true” value for many field variables is commonly unknown. In the laboratory, specific QA/QC samples assess error for each aspect of the measurement process, whereas field revisits assess precision and accuracy of the entire data collection process following initial calibration. Rigorous QA/QC data in an ecorestoration project are essential for evaluating the success of a project, and they provide the only objective “legacy” of the dataset for potential legal challenges and future uses.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12284","usgsCitation":"Stapanian, M.A., Lewis, T.E., Palmer, C.J., and Middlebrook Amos, M., 2016, Assessing accuracy and precision for field and laboratory data: a perspective in ecosystem restoration: Restoration Ecology, v. 24, no. 1, p. 18-26, https://doi.org/10.1111/rec.12284.","productDescription":"9 p.","startPage":"18","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054244","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":309393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"563486aae4b048076347fafb","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":572040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, Timothy E","contributorId":147563,"corporation":false,"usgs":false,"family":"Lewis","given":"Timothy","email":"","middleInitial":"E","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":572041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmer, Craig J.","contributorId":36028,"corporation":false,"usgs":true,"family":"Palmer","given":"Craig","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":572042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middlebrook Amos, Molly","contributorId":147564,"corporation":false,"usgs":false,"family":"Middlebrook Amos","given":"Molly","email":"","affiliations":[{"id":6937,"text":"CSC – IT Centre for Science, P.O. Box 405, 02101, Espoo, Finland","active":true,"usgs":false}],"preferred":false,"id":572043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191236,"text":"70191236 - 2016 - An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States","interactions":[],"lastModifiedDate":"2017-10-02T16:19:59","indexId":"70191236","displayToPublicDate":"2015-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1191,"text":"Cartography and Geographic Information Science","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States","docAbstract":"Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230406.2015.1067829","usgsCitation":"Wendel, J., Buttenfield, B., and Stanislawski, L.V., 2016, An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States: Cartography and Geographic Information Science, v. 43, no. 3, p. 233-249, https://doi.org/10.1080/15230406.2015.1067829.","productDescription":"17 p.","startPage":"233","endPage":"249","ipdsId":"IP-062949","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":346332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"43","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-15","publicationStatus":"PW","scienceBaseUri":"59d35029e4b05fe04cc34d65","contributors":{"authors":[{"text":"Wendel, Jochen","contributorId":196803,"corporation":false,"usgs":false,"family":"Wendel","given":"Jochen","affiliations":[],"preferred":false,"id":711651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":711652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":711650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173663,"text":"70173663 - 2016 - Animal movement constraints improve resource selection inference in the presence of telemetry error","interactions":[],"lastModifiedDate":"2016-06-07T15:20:38","indexId":"70173663","displayToPublicDate":"2015-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Animal movement constraints improve resource selection inference in the presence of telemetry error","docAbstract":"Multiple factors complicate the analysis of animal telemetry location data. Recent advancements address issues such as temporal autocorrelation and telemetry measurement error, but additional challenges remain. Difficulties introduced by complicated error structures or barriers to animal movement can weaken inference. We propose an approach for obtaining resource selection inference from animal location data that accounts for complicated error structures, movement constraints, and temporally autocorrelated observations. We specify a model for telemetry data observed with error conditional on unobserved true locations that reflects prior knowledge about constraints in the animal movement process. The observed telemetry data are modeled using a flexible distribution that accommodates extreme errors and complicated error structures. Although constraints to movement are often viewed as a nuisance, we use constraints to simultaneously estimate and account for telemetry error. We apply the model to simulated data, showing that it outperforms common ad hoc approaches used when confronted with measurement error and movement constraints. We then apply our framework to an Argos satellite telemetry data set on harbor seals (Phoca vitulina) in the Gulf of Alaska, a species that is constrained to move within the marine environment and adjacent coastlines.
","language":"English","publisher":"Ecological Society of America, Wiley","doi":"10.1890/15-0472.1","usgsCitation":"Brost, B.M., Hooten, M., Hanks, E., and Small, R.J., 2016, Animal movement constraints improve resource selection inference in the presence of telemetry error: Ecology, v. 96, no. 10, p. 2590-2597, https://doi.org/10.1890/15-0472.1.","productDescription":"8 p.","startPage":"2590","endPage":"2597","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060441","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/15-0472.1","text":"Publisher Index Page"},{"id":323199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5757f02ee4b04f417c24da1b","contributors":{"authors":[{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":637471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Ephraim M.","contributorId":104630,"corporation":false,"usgs":true,"family":"Hanks","given":"Ephraim M.","affiliations":[],"preferred":false,"id":637596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Small, Robert J.","contributorId":171486,"corporation":false,"usgs":false,"family":"Small","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":637597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168681,"text":"70168681 - 2016 - Evaluating abundance and trends in a Hawaiian avian community using state-space analysis","interactions":[],"lastModifiedDate":"2018-01-04T12:37:05","indexId":"70168681","displayToPublicDate":"2015-09-30T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating abundance and trends in a Hawaiian avian community using state-space analysis","docAbstract":"Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.
","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge","doi":"10.1017/S0959270915000088","usgsCitation":"Camp, R., Brinck, K., Gorresen, P.M., and Paxton, E., 2016, Evaluating abundance and trends in a Hawaiian avian community using state-space analysis: Bird Conservation International, v. 26, no. 2, p. 225-242, https://doi.org/10.1017/S0959270915000088.","productDescription":"18 p.","startPage":"225","endPage":"242","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064721","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":318360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hakalau Forest 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 -155.467529296875,\n 19.427743935948932\n ],\n [\n -155.467529296875,\n 19.89330573274471\n ],\n [\n -155.15167236328125,\n 19.89330573274471\n ],\n [\n -155.15167236328125,\n 19.427743935948932\n ],\n [\n -155.467529296875,\n 19.427743935948932\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-30","publicationStatus":"PW","scienceBaseUri":"56cee261e4b015c306ec5ebf","contributors":{"authors":[{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":621250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W.","contributorId":78215,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","affiliations":[],"preferred":false,"id":621251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorresen, P. M. mgorresen@usgs.gov","contributorId":18552,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":621252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":621249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170002,"text":"70170002 - 2016 - A new method for discovering behavior patterns among animal movements","interactions":[],"lastModifiedDate":"2017-08-26T16:45:50","indexId":"70170002","displayToPublicDate":"2015-09-29T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2046,"text":"International Journal of Geographical Information Science","active":true,"publicationSubtype":{"id":10}},"title":"A new method for discovering behavior patterns among animal movements","docAbstract":"Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.
","language":"English","publisher":"Royal Institute of International Affairs","publisherLocation":"London","doi":"10.1080/13658816.2015.1091462","usgsCitation":"Wang, Y., Luo, Z., Takekawa, J.Y., Prosser, D.J., Xiong, Y., Newman, S., Xiao, X., Batbayar, N., Spragens, K.A., Balachandran, S., and Yan, B., 2016, A new method for discovering behavior patterns among animal movements: International Journal of Geographical Information Science, v. 30, no. 5, p. 929-947, https://doi.org/10.1080/13658816.2015.1091462.","productDescription":"19 p.","startPage":"929","endPage":"947","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066274","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471449,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4874732","text":"External Repository"},{"id":319713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-29","publicationStatus":"PW","scienceBaseUri":"56ff9bb7e4b0328dcb7eaa38","contributors":{"authors":[{"text":"Wang, Y.","contributorId":64213,"corporation":false,"usgs":true,"family":"Wang","given":"Y.","affiliations":[],"preferred":false,"id":625839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":625841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":625840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, Y.","contributorId":168415,"corporation":false,"usgs":false,"family":"Xiong","given":"Y.","email":"","affiliations":[{"id":25285,"text":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":625842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, S.","contributorId":7678,"corporation":false,"usgs":true,"family":"Newman","given":"S.","affiliations":[],"preferred":false,"id":625843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiao, X.","contributorId":82869,"corporation":false,"usgs":true,"family":"Xiao","given":"X.","email":"","affiliations":[],"preferred":false,"id":625844,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Batbayar, N.","contributorId":47074,"corporation":false,"usgs":true,"family":"Batbayar","given":"N.","email":"","affiliations":[],"preferred":false,"id":625845,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spragens, Kyle A. kspragens@usgs.gov","contributorId":5775,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle","email":"kspragens@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":625846,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Balachandran, S.","contributorId":26891,"corporation":false,"usgs":true,"family":"Balachandran","given":"S.","affiliations":[],"preferred":false,"id":625847,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yan, B.","contributorId":11739,"corporation":false,"usgs":true,"family":"Yan","given":"B.","email":"","affiliations":[],"preferred":false,"id":625848,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70157593,"text":"70157593 - 2016 - Human activities cause distinct dissolved organic matter composition across freshwater ecosystems","interactions":[],"lastModifiedDate":"2016-02-01T13:16:17","indexId":"70157593","displayToPublicDate":"2015-09-29T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Human activities cause distinct dissolved organic matter composition across freshwater ecosystems","docAbstract":"Dissolved organic matter (DOM) composition in freshwater ecosystems is influenced by interactions between physical, chemical, and biological processes that are controlled, at one level, by watershed landscape, hydrology, and their connections. Against this environmental template, humans may strongly influence DOM composition. Yet, we lack a comprehensive understanding of DOM composition variation across freshwater ecosystems differentially affected by human activity. Using optical properties, we described DOM variation across five ecosystem groups of the Laurentian Great Lakes Region: large lakes, Kawartha Lakes, Experimental Lakes Area, urban stormwater ponds, and rivers (n = 184 sites). We determined how between ecosystem variation in DOM composition related to watershed size, land use and cover, water quality measures (conductivity, dissolved organic carbon (DOC), nutrient concentration, chlorophyll a), and human population density. The five freshwater ecosystem groups had distinctive DOM composition from each other. These significant differences were not explained completely through differences in watershed size nor spatial autocorrelation. Instead, multivariate partial least squares regression showed that DOM composition was related to differences in human impact across freshwater ecosystems. In particular, urban/developed watersheds with higher human population densities had a unique DOM composition with a clear anthropogenic influence that was distinct from DOM composition in natural land cover and/or agricultural watersheds. This nonagricultural, human developed impact on aquatic DOM was most evident through increased levels of a microbial, humic-like parallel factor analysis component (C6). Lotic and lentic ecosystems with low human population densities had DOM compositions more typical of clear water to humic-rich freshwater ecosystems but C6 was only present at trace to background levels. Consequently, humans are strongly altering the quality of DOM in waters nearby or flowing through highly populated areas, which may alter carbon cycles in anthropogenically disturbed ecosystems at broad scales.
","language":"English","publisher":"John Wiley & Sons Ltd.","doi":"10.1111/gcb.13094","usgsCitation":"Williams, C.J., Frost, P.C., Morales-Williams, A.M., Larson, J.H., Richardson, W.B., Chiandet, A.S., and Xenopoulos, M.A., 2016, Human activities cause distinct dissolved organic matter composition across freshwater ecosystems: Global Change Biology, v. 22, no. 2, p. 613-626, https://doi.org/10.1111/gcb.13094.","productDescription":"14 p.","startPage":"613","endPage":"626","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064700","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":308689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-11","publicationStatus":"PW","scienceBaseUri":"560ba83de4b058f706e53a7f","contributors":{"authors":[{"text":"Williams, Clayton J.","contributorId":138631,"corporation":false,"usgs":false,"family":"Williams","given":"Clayton","email":"","middleInitial":"J.","affiliations":[{"id":12468,"text":"Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":573702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frost, Paul C.","contributorId":138628,"corporation":false,"usgs":false,"family":"Frost","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":573703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales-Williams, Ana M.","contributorId":148057,"corporation":false,"usgs":false,"family":"Morales-Williams","given":"Ana","email":"","middleInitial":"M.","affiliations":[{"id":16985,"text":"Trent University & Iowa State University","active":true,"usgs":false}],"preferred":false,"id":573704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":573701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":573705,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chiandet, Aisha S.","contributorId":148058,"corporation":false,"usgs":false,"family":"Chiandet","given":"Aisha","email":"","middleInitial":"S.","affiliations":[{"id":16986,"text":"Severn Sound Environmental Association","active":true,"usgs":false}],"preferred":false,"id":573706,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xenopoulos, Marguerite A.","contributorId":138629,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite","email":"","middleInitial":"A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":573707,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176942,"text":"70176942 - 2016 - Precipitation regime classification for the Mojave Desert: Implications for fire occurrence","interactions":[],"lastModifiedDate":"2017-04-07T13:55:04","indexId":"70176942","displayToPublicDate":"2015-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation regime classification for the Mojave Desert: Implications for fire occurrence","docAbstract":"Long periods of drought or above-average precipitation affect Mojave Desert vegetation condition, biomass and susceptibility to fire. Changes in the seasonality of precipitation alter the likelihood of lightning, a key ignition source for fires. The objectives of this study were to characterize the relationship between recent, historic, and future precipitation patterns and fire. Classifying monthly precipitation data from 1971 to 2010 reveals four precipitation regimes: low winter/low summer, moderate winter/moderate summer, high winter/low summer and high winter/high summer. Two regimes with summer monsoonal precipitation covered only 40% of the Mojave Desert ecoregion but contain 88% of the area burned and 95% of the repeat burn area. Classifying historic precipitation for early-century (wet) and mid-century (drought) periods reveals distinct shifts in regime boundaries. Early-century results are similar to current, while the mid-century results show a sizeable reduction in area of regimes with a strong monsoonal component. Such a shift would suggest that fires during the mid-century period would be minimal and anecdotal records confirm this. Predicted precipitation patterns from downscaled global climate models indicate numerous epochs of high winter precipitation, inferring higher fire potential for many multi-decade periods during the next century.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2015.09.002","usgsCitation":"Tagestad, J., Brooks, M.L., Cullinan, V., Downs, J., and McKinley, R., 2016, Precipitation regime classification for the Mojave Desert: Implications for fire occurrence: Journal of Arid Environments, v. 124, p. 388-397, https://doi.org/10.1016/j.jaridenv.2015.09.002.","productDescription":"10 p.","startPage":"388","endPage":"397","numberOfPages":"10","ipdsId":"IP-063012","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":329530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.817138671875,\n 33.47727218776036\n ],\n [\n -118.817138671875,\n 37.96152331396614\n ],\n [\n -112.664794921875,\n 37.96152331396614\n ],\n [\n -112.664794921875,\n 33.47727218776036\n ],\n [\n -118.817138671875,\n 33.47727218776036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf6","contributors":{"authors":[{"text":"Tagestad, Jerry","contributorId":175339,"corporation":false,"usgs":false,"family":"Tagestad","given":"Jerry","email":"","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":650819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cullinan, Valerie","contributorId":175340,"corporation":false,"usgs":false,"family":"Cullinan","given":"Valerie","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Janelle","contributorId":175341,"corporation":false,"usgs":false,"family":"Downs","given":"Janelle","email":"","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650822,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKinley, Randy 0000-0001-7644-6365 rmckinley@usgs.gov","orcid":"https://orcid.org/0000-0001-7644-6365","contributorId":1354,"corporation":false,"usgs":true,"family":"McKinley","given":"Randy","email":"rmckinley@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":650823,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157236,"text":"70157236 - 2016 - Blind identification of the Millikan Library from earthquake data considering soil–structure interaction","interactions":[],"lastModifiedDate":"2016-06-17T09:37:01","indexId":"70157236","displayToPublicDate":"2015-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5007,"text":"Structural Control and Health Monitoring","active":true,"publicationSubtype":{"id":10}},"title":"Blind identification of the Millikan Library from earthquake data considering soil–structure interaction","docAbstract":"The Robert A. Millikan Library is a reinforced concrete building with a basement level and nine stories above the ground. Located on the campus of California Institute of Technology (Caltech) in Pasadena California, it is among the most densely instrumented buildings in the U.S. From the early dates of its construction, it has been the subject of many investigations, especially regarding soil–structure interaction effects. It is well accepted that the structure is significantly interacting with the surrounding soil, which implies that the true foundation input motions cannot be directly recorded during earthquakes because of inertial effects. Based on this limitation, input–output modal identification methods are not applicable to this soil–structure system. On the other hand, conventional output-only methods are typically based on the unknown input signals to be stationary whitenoise, which is not the case for earthquake excitations. Through the use of recently developed blind identification (i.e. output-only) methods, it has become possible to extract such information from only the response signals because of earthquake excitations. In the present study, we employ such a blind identification method to extract the modal properties of the Millikan Library. We present some modes that have not been identified from force vibration tests in several studies to date. Then, to quantify the contribution of soil–structure interaction effects, we first create a detailed Finite Element (FE) model using available information about the superstructure; and subsequently update the soil–foundation system's dynamic stiffnesses at each mode such that the modal properties of the entire soil–structure system agree well with those obtained via output-only modal identification.
","language":"English","publisher":"International Association for Structural Control and Monitoring","publisherLocation":"Chichester, UK","doi":"10.1002/stc.1803","usgsCitation":"Ghahari, S.F., Abazarsa, F., Avci, O., Çelebi, M., and Taciroglu, E., 2016, Blind identification of the Millikan Library from earthquake data considering soil–structure interaction: Structural Control and Health Monitoring, v. 23, no. 4, p. 684-706, https://doi.org/10.1002/stc.1803.","productDescription":"23 p.","startPage":"684","endPage":"706","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068999","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471450,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/stc.1803","text":"Publisher Index Page"},{"id":318538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Pasadena","otherGeospatial":"Robert A. Millikan Library, California Insttitute of Technology","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.12946319580077,\n 34.13136240467381\n ],\n [\n -118.12946319580077,\n 34.14203648796777\n ],\n [\n -118.12130928039551,\n 34.14203648796777\n ],\n [\n -118.12130928039551,\n 34.13136240467381\n ],\n [\n -118.12946319580077,\n 34.13136240467381\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-29","publicationStatus":"PW","scienceBaseUri":"56d96e3ce4b015c306f7644c","contributors":{"authors":[{"text":"Ghahari, S. F.","contributorId":147707,"corporation":false,"usgs":false,"family":"Ghahari","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abazarsa, F.","contributorId":147708,"corporation":false,"usgs":false,"family":"Abazarsa","given":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avci, O.","contributorId":147709,"corporation":false,"usgs":false,"family":"Avci","given":"O.","email":"","affiliations":[{"id":16914,"text":"University of Qatar","active":true,"usgs":false}],"preferred":false,"id":572367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Çelebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":3205,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":572364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taciroglu, E.","contributorId":147710,"corporation":false,"usgs":false,"family":"Taciroglu","given":"E.","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211939,"text":"70211939 - 2016 - Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics","interactions":[],"lastModifiedDate":"2021-04-27T18:50:22.024529","indexId":"70211939","displayToPublicDate":"2015-09-28T11:43:50","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics","docAbstract":"A workshop on Restoration of Impaired Ecosystems was held in Jackson, Wyoming, in June 2014. Experts from Australia, Canada, Mexico, the United Kingdom, and the United States in ecotoxicology, restoration, and related fields from both the Society of Environmental Toxicology and Chemistry and the Society for Ecological Restoration convened to advance the practice of restoring ecosystems that have been contaminated or impaired from industrial activities. The overall goal of this workshop was to provide a forum for ecotoxicologists and restoration ecologists to define the best scientific practices to achieve ecological restoration while addressing contaminant concerns. To meet this goal, participants addressed 5 areas: 1) links between ecological risk assessment and ecological restoration, 2) restoration goals, 3) restoration design, 4) monitoring for restoration effectiveness and 5) recognizing opportunities and challenges. Definitions are provided to establish a common language across the varied disciplines. The current practice for addressing restoration of impaired ecosystems tends to be done sequentially to remediate contaminants, then to restore ecological structure and function. A better approach would anticipate or plan for restoration throughout the process. By bringing goals to the forefront, we may avoid intrusive remediation activities that close off options for the desired restoration. Participants realized that perceived limitations in the site assessment process hinder consideration of restoration goals; contaminant presence will influence restoration goal choices; social, economic, and cultural concerns can factor into goal setting; restoration options and design should be considered early during site assessment and management; restoration of both structure and function is encouraged; creative solutions can overcome limitations; a regional focus is imperative; monitoring must occur throughout the restoration process; and reciprocal transfer of knowledge is needed among theorists, practitioners, and stakeholders and among varied disciplines.
","language":"English","publisher":"Wiley","doi":"10.1002/ieam.1687","usgsCitation":"Farag, A.M., Hull, R.N., Clements, W.H., Glomb, S., Larson, D.L., Stahl, R.G., and Stauber, J., 2016, Restoration of impaired ecosystems: An ounce of prevention or a pound of cure? introduction, overview, and key messages from a SETAC-SER workshop: Integrated Environmental Assessment and Management, v. 12, no. 2, p. 247-252, https://doi.org/10.1002/ieam.1687.","productDescription":"6 p.","startPage":"247","endPage":"252","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061919","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1687","text":"Publisher Index Page"},{"id":312578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-01","publicationStatus":"PW","scienceBaseUri":"567930d2e4b0da412f4fb591","contributors":{"authors":[{"text":"Farag, Aida M. 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":1139,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":582880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hull, Ruth N.","contributorId":150740,"corporation":false,"usgs":false,"family":"Hull","given":"Ruth","email":"","middleInitial":"N.","affiliations":[{"id":18085,"text":"Intrinsik Environmental Sciences Inc., Mississauga, ON, Canada","active":true,"usgs":false}],"preferred":false,"id":582881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Will H.","contributorId":150741,"corporation":false,"usgs":false,"family":"Clements","given":"Will","email":"","middleInitial":"H.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":582882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glomb, Steve","contributorId":150742,"corporation":false,"usgs":false,"family":"Glomb","given":"Steve","email":"","affiliations":[{"id":18086,"text":"US Department of Interior, Washington, D.C","active":true,"usgs":false}],"preferred":false,"id":582883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":582884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stahl, Ralph G.","contributorId":78666,"corporation":false,"usgs":true,"family":"Stahl","given":"Ralph","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":582885,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stauber, Jenny","contributorId":11970,"corporation":false,"usgs":true,"family":"Stauber","given":"Jenny","affiliations":[],"preferred":false,"id":582886,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160785,"text":"70160785 - 2016 - Behavioural response of adult sea lamprey (Petromyzon marinus) to predator and conspecific alarm cues: evidence of additive effects","interactions":[],"lastModifiedDate":"2016-12-14T12:45:15","indexId":"70160785","displayToPublicDate":"2015-09-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Behavioural response of adult sea lamprey (Petromyzon marinus) to predator and conspecific alarm cues: evidence of additive effects","docAbstract":"Sea lampreys Petromyzon marinus, an invasive pest in the Upper Great Lakes, avoid odours that represent danger in their habitat. These odours include conspecific alarm cues and predator cues, like 2-phenylethylamine hydrochloride (PEA HCl), which is found in the urine of mammalian predators. Whether conspecific alarm cues and predator cues function additively or synergistically when mixed together is unknown. The objectives of this experimental study were to determine if the avoidance response of sea lamprey to PEA HCl is proportional to the concentration delivered, and if the avoidance response to the combination of a predator cue (PEA HCl) and sea lamprey alarm cue is additive. To accomplish the first objective, groups of ten sea lampreys were placed in an artificial stream channel and presented with stepwise concentrations of PEA HCl ranging from 5 × 10−8 to 5 × 10−10 M and a deionized water control. Sea lampreys exhibited an increase in their avoidance behaviour in response to increasing concentrations of PEA HCl. To accomplish the second objective, sea lampreys were exposed to PEA HCl, conspecific alarm cue and a combination of the two. Sea lampreys responded to the combination of predator cue and conspecific alarm cue in an additive manner.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-015-2508-6","usgsCitation":"Di Rocco, R.T., Imre, I., Johnson, N., and Brown, G.B., 2016, Behavioural response of adult sea lamprey (Petromyzon marinus) to predator and conspecific alarm cues: evidence of additive effects: Hydrobiologia, v. 767, no. 1, p. 279-287, https://doi.org/10.1007/s10750-015-2508-6.","productDescription":"9 p.","startPage":"279","endPage":"287","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065576","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471452,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://spectrum.library.concordia.ca/979649/1/Di_Rocco_MSc_Thesis.pdf","text":"External Repository"},{"id":313136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada; United States","otherGeospatial":"St.Mary's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.57824707031249,\n 46.53052428878426\n ],\n [\n -84.63043212890625,\n 46.479482189368646\n ],\n [\n -84.6002197265625,\n 46.42081919374916\n ],\n [\n -84.495849609375,\n 46.43596408010131\n ],\n [\n -84.462890625,\n 46.45488927067795\n ],\n [\n -84.39971923828125,\n 46.492719928122746\n ],\n [\n -84.28985595703124,\n 46.47380788661107\n ],\n [\n -84.254150390625,\n 46.38672781370433\n ],\n [\n -84.2156982421875,\n 46.29950860500902\n ],\n [\n -84.1827392578125,\n 46.23685258143992\n ],\n [\n -84.23492431640624,\n 46.21215024064958\n ],\n [\n -84.23492431640624,\n 46.17222297845542\n ],\n [\n -84.14154052734374,\n 46.176026824576574\n ],\n [\n -84.0673828125,\n 46.145588688591964\n ],\n [\n -84.03717041015625,\n 46.1322667089571\n ],\n [\n -84.0673828125,\n 46.09228143052649\n ],\n [\n -83.9739990234375,\n 46.01603873833416\n ],\n [\n -83.91357421875,\n 46.010316293096196\n ],\n [\n -83.7982177734375,\n 46.14749156542368\n ],\n [\n -83.74603271484375,\n 46.272936008641494\n ],\n [\n -83.76800537109374,\n 46.29381556233369\n ],\n [\n -83.89984130859374,\n 46.32796494040748\n ],\n [\n -84.0618896484375,\n 46.320378031062354\n ],\n [\n -84.1058349609375,\n 46.3583020562222\n ],\n [\n -84.09484863281249,\n 46.464349400461124\n ],\n [\n -84.10308837890624,\n 46.50784482789971\n ],\n [\n -84.17724609375,\n 46.53808200546305\n ],\n [\n -84.26239013671875,\n 46.50973514453879\n ],\n [\n -84.36676025390625,\n 46.5002829039397\n ],\n [\n -84.46563720703125,\n 46.48704700597017\n ],\n [\n -84.49859619140625,\n 46.47380788661107\n ],\n [\n -84.561767578125,\n 46.522965520307295\n ],\n [\n -84.57824707031249,\n 46.53052428878426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"767","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-26","publicationStatus":"PW","scienceBaseUri":"56865fbee4b0e7594ee74cb6","contributors":{"authors":[{"text":"Di Rocco, Richard T.","contributorId":150984,"corporation":false,"usgs":false,"family":"Di Rocco","given":"Richard","email":"","middleInitial":"T.","affiliations":[{"id":6586,"text":"Concordia University","active":true,"usgs":false}],"preferred":false,"id":583894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Imre, Istvan","contributorId":150985,"corporation":false,"usgs":false,"family":"Imre","given":"Istvan","email":"","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":583895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Grant B","contributorId":150986,"corporation":false,"usgs":false,"family":"Brown","given":"Grant","email":"","middleInitial":"B","affiliations":[{"id":6586,"text":"Concordia University","active":true,"usgs":false}],"preferred":false,"id":583896,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157212,"text":"70157212 - 2016 - Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use","interactions":[],"lastModifiedDate":"2016-12-14T12:24:51","indexId":"70157212","displayToPublicDate":"2015-09-25T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1844,"text":"Global and Planetary Change","active":true,"publicationSubtype":{"id":10}},"title":"Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use","docAbstract":"Although fire was arguably the primary tool used by the Maya to alter the landscape and extract resources, little attention has been paid to biomass burning in paleoenvironmental reconstructions from the Maya lowlands. Here we report two new well-dated, high-resolution records of biomass burning based on analysis of macroscopic fossil charcoal recovered from lacustrine sediment cores. The records extend from the early Holocene, through the full arc of Maya prehistory, the Colonial, and post-Colonial periods (~ 9000 cal yr BP to the present). (Hereafter BP) The study sites, Lago Paixban and Lago Puerto Arturo, are located in northern Peten, Guatemala. Results provide the first quantitative analysis from the region demonstrating that frequent fires have occurred in the closed canopy forests since at least the early Holocene (~ 9000 BP), prior to occupation by sedentary agriculturalists. Following the arrival of agriculture around 4600 BP, the system transitioned from climate controlled to anthropogenic control. During the Maya period, changes in fire regime are muted and do not appear to be driven by changes in climate conditions. Low charcoal influx and fire frequency in the Earliest Preclassic period suggest that land use strategies may have included intensive agriculture much earlier than previously thought. Preliminary results showing concentrations of soot/black-carbon during the middle and late Preclassic periods are lower than modern background values, providing intriguing implications regarding the efficiency of Maya fuel consumption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2015.09.012","usgsCitation":"Anderson, L., and Wahl, D.B., 2016, Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use: Global and Planetary Change, v. 138, p. 82-92, https://doi.org/10.1016/j.gloplacha.2015.09.012.","productDescription":"11 p.","startPage":"82","endPage":"92","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060515","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gloplacha.2015.09.012","text":"Publisher Index Page"},{"id":312843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guatemala","state":"Peten","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.72235107421874,\n 17.808841135842886\n ],\n [\n -89.6649169921875,\n 17.808841135842886\n ],\n [\n -89.61822509765625,\n 17.371610024104744\n ],\n [\n -89.83795166015625,\n 17.041029311689186\n ],\n [\n -90.13732910156249,\n 17.012141149739257\n ],\n [\n -90.60150146484375,\n 17.012141149739257\n ],\n [\n -90.79925537109375,\n 17.27984137051228\n ],\n [\n -90.72235107421874,\n 17.808841135842886\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"138","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3c1e4b0a04ef491a226","chorus":{"doi":"10.1016/j.gloplacha.2015.09.012","url":"http://dx.doi.org/10.1016/j.gloplacha.2015.09.012","publisher":"Elsevier BV","authors":"Anderson Lysanna, Wahl David","journalName":"Global and Planetary Change","publicationDate":"3/2016"},"contributors":{"authors":[{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":572278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, David B. 0000-0002-0451-3554 dwahl@usgs.gov","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":3433,"corporation":false,"usgs":true,"family":"Wahl","given":"David","email":"dwahl@usgs.gov","middleInitial":"B.","affiliations":[{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":572279,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174886,"text":"70174886 - 2016 - Evaluating the adequacy of a reference site pool for ecological assessments in environmentally complex regions","interactions":[],"lastModifiedDate":"2016-07-20T11:03:34","indexId":"70174886","displayToPublicDate":"2015-09-24T14:30:00","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":"Evaluating the adequacy of a reference site pool for ecological assessments in environmentally complex regions","docAbstract":"Many advances in the field of bioassessment have focused on approaches for objectively selecting the pool of reference sites used to establish expectations for healthy waterbodies, but little emphasis has been placed on ways to evaluate the suitability of the reference-site pool for its intended applications (e.g., compliance assessment vs ambient monitoring). These evaluations are critical because an inadequately evaluated reference pool may bias assessments in some settings. We present an approach for evaluating the adequacy of a reference-site pool for supporting biotic-index development in environmentally heterogeneous and pervasively altered regions. We followed common approaches for selecting sites with low levels of anthropogenic stress to screen 1985 candidate stream reaches to create a pool of 590 reference sites for assessing the biological integrity of streams in California, USA. We assessed the resulting pool of reference sites against 2 performance criteria. First, we evaluated how well the reference-site pool represented the range of natural gradients present in the entire population of streams as estimated by sites sampled through probabilistic surveys. Second, we evaluated the degree to which we were successful in rejecting sites influenced by anthropogenic stress by comparing biological metric scores at reference sites with the most vs fewest potential sources of stress. Using this approach, we established a reference-site pool with low levels of human-associated stress and broad coverage of environmental heterogeneity. This approach should be widely applicable and customizable to particular regional or programmatic needs.
","language":"English","publisher":"The Society for Freshwater Science and the University of Chicago Press","doi":"10.1086/684003","collaboration":"Southern California Coastal Water Research Project; California Department of Fish and Wildlife","usgsCitation":"Ode, P.R., Rehn, A.C., Mazor, R.D., Schiff, K.C., Stein, E.D., May, J., Brown, L.R., Herbst, D.B., Gillette, D., Lunde, K., and Hawkins, C., 2016, Evaluating the adequacy of a reference site pool for ecological assessments in environmentally complex regions: Freshwater Science, v. 35, no. 1, p. 237-248, https://doi.org/10.1086/684003.","productDescription":"11 p.","startPage":"237","endPage":"248","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/684003","text":"Publisher Index 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The products are mainly basaltic andesites, with the 2000–2012 eruptive products the most mafic. The geochemistry of Copahue products is compared with those of the main Andes arc (Llaima, Callaqui, Tolhuaca), the older Caviahue volcano directly east of Copahue, and the back arc volcanics of the Loncopue graben. The Caviahue rocks resemble the main Andes arc suite, whereas the Copahue rocks are characterized by lower Fe and Ti contents and higher incompatible element concentrations. The rocks have negative Nb-Ta anomalies, modest enrichments in radiogenic Sr and Pb isotope ratios and slightly depleted Nd isotope ratios. The combined trace element and isotopic data indicate that Copahue magmas formed in a relatively dry mantle environment, with melting of a subducted sediment residue. The back arc basalts show a wide variation in isotopic composition, have similar water contents as the Copahue magmas and show evidence for a subducted sedimentary component in their source regions. The low 206Pb/204Pb of some backarc lava flows suggests the presence of a second endmember with an EM1 flavor in its source. The overall magma genesis is explained within the context of a subducted slab with sediment that gradually looses water, water-mobile elements, and then switches to sediment melt extracts deeper down in the subduction zone. With the change in element extraction mechanism with depth comes a depletion and fractionation of the subducted complex that is reflected in the isotope and trace element signatures of the products from the main arc to Copahue to the back arc basalts.
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Optimal egg size (OES) theory predicts that any increase in resources allocated to reproduction should increase clutch size with minimal effects on egg size. Variations of OES predict that egg size should be optimized, although not necessarily constant across a population, because optimality is contingent on maternal phenotypes, such as body size and morphology, and recent environmental conditions. We examined the relationships among body size variables (pelvic aperture width, caudal gap height, and plastron length), clutch size, and egg width of diamondback terrapins from separate but proximate populations at Kiawah Island and Edisto Island, South Carolina. We found that terrapins do not meet some of the predictions of OES theory. Both populations exhibited greater variation in egg size among clutches than within, suggesting an absence of optimization except as it may relate to phenotype/habitat matching. We found that egg size appeared to be constrained by more than just pelvic aperture width in Kiawah terrapins but not in the Edisto population. Terrapins at Edisto appeared to exhibit osteokinesis in the caudal region of their shells, which may aid in the oviposition of large eggs.
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Consequently, natural-resource managers face increasingly urgent conservation questions related to biodiversity loss, expansion of invasive species, and deteriorating ecosystem services. We argue that our ability to address these questions is hampered by the lack of explicit consideration of species’ adaptive capacity (AC). AC is the ability of a species or population to cope with climatic changes and is characterized by three fundamental components: phenotypic plasticity, dispersal ability, and genetic diversity. However, few studies simultaneously address all elements; often, AC is confused with sensitivity or omitted altogether from climate-change vulnerability assessments. Improved understanding, consistent definition, and comprehensive evaluations of AC are needed. Using classic ecological-niche theory as an analogy, we propose a new paradigm that considers fundamental and realized AC: the former reflects aspects inherent to species, whereas the latter denotes how extrinsic factors constrain AC to what is actually expressed or observed. Through this conceptualization, we identify ecological attributes contributing to AC, outline areas of research necessary to advance understanding of AC, and provide examples demonstrating how the inclusion of AC can better inform conservation and natural-resource management.
","language":"English","publisher":"Wiley","doi":"10.1111/conl.12190","usgsCitation":"Beever, E., O’Leary, J., Mengelt, C., West, J.M., Julius, S., Green, N., Magness, D., Petes, L.E., Stein, B.A., Nicotra, A.B., Hellmann, J.J., Robertson, A.L., Staudinger, M.D., Rosenberg, A.A., Babij, E., Brennan, J., Schuurman, G.W., and Hofmann, G.E., 2016, Improving conservation outcomes with a new paradigm for understanding species’ fundamental and realized adaptive capacity: Conservation Letters, v. 9, no. 2, p. 131-137, https://doi.org/10.1111/conl.12190.","productDescription":"7 p.","startPage":"131","endPage":"137","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059591","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/conl.12190","text":"Publisher Index 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