The interspecific relationships between abundance and site occupancy have been widely studied in plants and animals, but principally in terrestrial systems. With few exceptions, a positive abundance–occupancy relationship has been reported. Few publications have included freshwater fish, possibly suggesting a general lack of abundance–occupancy patterns for this taxonomic group.
We examined the relationship between abundance and the extent of site occupancy by 145 species of freshwater fish, including nine non-indigenous species, sampled over 85 sites spread across the Duck River Basin, Tennessee, U.S.A.
A distinct (r2 = 0.79) positive abundance–occupancy curve was observed, with curves differing relative to feeding and size guilds, but not relative to environmental tolerance, conservation status (i.e. listed/non-listed), or origin (i.e. indigenous/non-indigenous).
The patterns observed are consistent with those reported in many studies of terrestrial taxa.
The existence of positive abundance–occupancy relationships in stream fish has at least two major implications for fish conservation. First, species that decrease in occupancy due to anthropogenic disturbances are likely to decrease in abundance, facing inflated prospects for local extinction. Second, occupancy alone may be used to index community status and the need for, or success of, conservation activities.
Understanding how biotic and abiotic interactions influence community assembly and composition is a fundamental goal in community ecology. Addressing this issue is particularly tractable along elevational gradients in tropical mountains that feature substantial abiotic gradients and rates of species turnover. We examined elevational patterns of avian community structure on 2 mountains in Malaysian Borneo to assess changes in the relative strength of biotic interactions and abiotic constraints. In particular, we used metrics based on (1) phylogenetic relatedness and (2) functional traits associated with both resource acquisition and tolerance of abiotic challenges to identify patterns and causes of elevational differences in community structure. High elevation communities were composed of more phylogenetically and functionally similar species than would be expected by chance. Resource acquisition traits, in particular, were clustered at high elevations, suggesting low resource and habitat diversity were important drivers of those communities. Traits typically associated with tolerance of cold temperatures and low atmospheric pressure showed no elevational patterns. All traits were neutral or overdispersed at low elevations suggesting an absence of strong abiotic filters or an increased influence of interspecific competition. However, relative bill size, which is important for thermoregulation, was larger in low elevation communities, suggesting abiotic factors were also influential there. Regardless of metric, clustered and neutral communities were more frequent than overdispersed communities overall, implying that interspecific competition among close relatives may not be a pervasive driver of elevational distribution and community structure of tropical birds. Overall, our analyses reveal that a diverse set of predominantly biotic factors underlie elevational variation in community structure on tropical mountains.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/auk/ukz054","usgsCitation":"Boyce, A., Shakya, S., Sheldon, F.H., Moyle, R., and Martin, T.E., 2019, Biotic interactions are the dominant drivers of phylogenetic and functional structure in bird communities along a tropical elevational gradient: The Auk, v. 136, no. 4, ukz054, 14 p., https://doi.org/10.1093/auk/ukz054.","productDescription":"ukz054, 14 p.","ipdsId":"IP-103732","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/auk/ukz054","text":"Publisher Index Page"},{"id":388690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malaysia","otherGeospatial":"Kinabalu Park, Mt. Kinabalu, Mt. Tambuyukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 116.41250610351562,\n 5.961656095137535\n ],\n [\n 116.82037353515625,\n 5.961656095137535\n ],\n [\n 116.82037353515625,\n 6.479067290763031\n ],\n [\n 116.41250610351562,\n 6.479067290763031\n ],\n [\n 116.41250610351562,\n 5.961656095137535\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"136","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Boyce, Andy J.","contributorId":264918,"corporation":false,"usgs":false,"family":"Boyce","given":"Andy J.","affiliations":[{"id":54582,"text":"cec","active":true,"usgs":false}],"preferred":false,"id":822186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shakya, Subir","contributorId":264919,"corporation":false,"usgs":false,"family":"Shakya","given":"Subir","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":822187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheldon, Frederick H.","contributorId":264920,"corporation":false,"usgs":false,"family":"Sheldon","given":"Frederick","email":"","middleInitial":"H.","affiliations":[{"id":54583,"text":"ku","active":true,"usgs":false}],"preferred":false,"id":822188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moyle, Robert G.","contributorId":264921,"corporation":false,"usgs":false,"family":"Moyle","given":"Robert G.","affiliations":[{"id":54583,"text":"ku","active":true,"usgs":false}],"preferred":false,"id":822189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":822190,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223320,"text":"70223320 - 2019 - Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models","interactions":[],"lastModifiedDate":"2021-08-23T23:16:06.9798","indexId":"70223320","displayToPublicDate":"2019-10-04T18:11:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models","docAbstract":"Understanding how stream fishes respond to changes in habitat availability is complicated by low occurrence rates of many species, which in turn reduces the ability to quantify species–habitat relationships and account for imperfect detection in estimates of species richness. Multispecies occupancy models have been used sparingly in the analysis of fisheries data, but address the aforementioned deficiencies by allowing information to be shared among ecologically similar species, thereby enabling species–habitat relationships to be estimated for entire fish communities, including rare species. Here, we highlight the utility of hierarchical multispecies occupancy models for the analysis of fish community data and demonstrate the modeling framework on a stream fish community dataset collected in the Delaware Water Gap National Recreation Area, USA. In particular, we demonstrate the ability of the modeling framework to make inferences at the species-, guild-, and community-levels, thereby making it a powerful tool for understanding and predicting how environmental variables influence species occupancy probabilities and structure fish assemblages.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0125","collaboration":"National Park Service","usgsCitation":"White, S., Faulk, E., Tzilkowski, C., Weber, A., Marshall, M., and Wagner, T., 2019, Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models: Canadian Journal Fisheries and Aquatic Sciences, v. 77, no. 3, 9 p., https://doi.org/10.1139/cjfas-2019-0125.","productDescription":"9 p.","ipdsId":"IP-101955","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York New Jersey, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.12451171875,\n 40.96330795307353\n ],\n [\n -74.15771484375,\n 40.96330795307353\n ],\n [\n -74.15771484375,\n 41.60722821271717\n ],\n [\n -75.12451171875,\n 41.60722821271717\n ],\n [\n -75.12451171875,\n 40.96330795307353\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon","contributorId":264595,"corporation":false,"usgs":false,"family":"White","given":"Shannon","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulk, Evan","contributorId":264596,"corporation":false,"usgs":false,"family":"Faulk","given":"Evan","email":"","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tzilkowski, Caleb","contributorId":264597,"corporation":false,"usgs":false,"family":"Tzilkowski","given":"Caleb","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Andrew","contributorId":264598,"corporation":false,"usgs":false,"family":"Weber","given":"Andrew","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marshall, Matt","contributorId":264599,"corporation":false,"usgs":false,"family":"Marshall","given":"Matt","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":821724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821719,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205928,"text":"70205928 - 2019 - Standardizing a non-lethal method for characterizing the reproductive status and larval development of freshwater mussels (Bivalvia: Unionoida)","interactions":[],"lastModifiedDate":"2019-10-10T13:50:07","indexId":"70205928","displayToPublicDate":"2019-10-04T13:48:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"Standardizing a non-lethal method for characterizing the reproductive status and larval development of freshwater mussels (Bivalvia: Unionoida)","docAbstract":"Actively monitoring the timing, development, and reproductive patterns of endangered species is critical when managing for population recovery. Freshwater mussels are among the most imperiled organisms in the world, but information about early larval (glochidial) development and brooding periods is still lacking for many species. Previous studies have focused on the complex life history stage when female mussels are ready to parasitize host fish, but few studies have focused on the brooding period and timing of larval development. The protocol described here allows researchers to non-lethally evaluate the state of gravidity for female mussels. The results of this study show that this method does not affect a female mussel’s ability to stay gravid or become gravid again after sampling has been performed. The advantage of this method may permit its use on federally threatened or endangered species or other populations of high conservation concern. This protocol can be adapted for use on both preserved or live individuals and was tested on a variety of mussel species. The database provided is a repository for a breadth of information on timing of reproductive habits and will facilitate future freshwater mussel research, conservation, and recovery efforts.","language":"English","publisher":"JoVE","doi":"10.3791/60244","usgsCitation":"Beaver, C., Geda, S., and Johnson, N., 2019, Standardizing a non-lethal method for characterizing the reproductive status and larval development of freshwater mussels (Bivalvia: Unionoida): Journal of Visualized Experiments, v. 152, e60244, https://doi.org/10.3791/60244.","productDescription":"e60244","ipdsId":"IP-108167","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3791/60244","text":"Publisher Index Page"},{"id":368239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaver, Caitlin 0000-0002-9269-7604","orcid":"https://orcid.org/0000-0002-9269-7604","contributorId":219705,"corporation":false,"usgs":true,"family":"Beaver","given":"Caitlin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":772923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geda, Susan","contributorId":219706,"corporation":false,"usgs":false,"family":"Geda","given":"Susan","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":772924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":216876,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":772922,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205846,"text":"70205846 - 2019 - Decline of the North American avifauna","interactions":[],"lastModifiedDate":"2019-10-08T13:07:48","indexId":"70205846","displayToPublicDate":"2019-10-04T13:06:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Decline of the North American avifauna","docAbstract":"Species extinctions have defined the global biodiversity crisis, but extinction begins with loss in abundance of organisms that can result in extreme compositional and functional changes of ecosystems. Using multiple and independent monitoring networks, we report major population losses across much of the North American avifauna, including in once common species and from nearly every biome. Integration of trend and population size estimates indicates a net loss approaching three billion birds, or 29% of 1970 abundance. Continent-wide weather radar also reveals a comparable decline in biomass passage of migrating birds over a recent 10-year period. Our estimates of abundance and biodiversity loss signals an urgent need to address ongoing threats, in order to avert future avifaunal collapse and associated loss of ecosystem integrity and function.","language":"English","publisher":"AAAS","doi":"10.1126/science.aaw1313","usgsCitation":"Sauer, J.R., Rosenberg, K.V., Dokter, A.M., Blancher, P.J., Smith, A.C., Smith, P.A., Stanton, J.C., Panjabi, A.O., Helft, L., Parr, M.J., and Marra, P.P., 2019, Decline of the North American avifauna: Science, v. 366, no. 6461, p. 120-124, https://doi.org/10.1126/science.aaw1313.","productDescription":"5 p.","startPage":"120","endPage":"124","ipdsId":"IP-105405","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":459608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/science.aaw1313","text":"Publisher Index Page"},{"id":368105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"366","issue":"6461","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":772593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dokter, Adriaan M.","contributorId":219578,"corporation":false,"usgs":false,"family":"Dokter","given":"Adriaan","email":"","middleInitial":"M.","affiliations":[{"id":40028,"text":"Cornell Laboratory of Ornithology, Cornell University, Ithaca, NY 14850, USA","active":true,"usgs":false}],"preferred":false,"id":772594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":772595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Adam C.","contributorId":195234,"corporation":false,"usgs":false,"family":"Smith","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":772596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Paul A.","contributorId":219579,"corporation":false,"usgs":false,"family":"Smith","given":"Paul","email":"","middleInitial":"A.","affiliations":[{"id":40029,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, Ottawa, ON K1A 0H3, Canada.","active":true,"usgs":false}],"preferred":false,"id":772597,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":772598,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":772599,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Helft, Laura","contributorId":219580,"corporation":false,"usgs":false,"family":"Helft","given":"Laura","email":"","affiliations":[{"id":40030,"text":"Cornell Laboratory of Ornithology, Cornell University, Ithaca, NY 14850, USA.","active":true,"usgs":false}],"preferred":false,"id":772600,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Parr, Michael J.","contributorId":147503,"corporation":false,"usgs":false,"family":"Parr","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":772601,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Marra, Peter P.","contributorId":190140,"corporation":false,"usgs":false,"family":"Marra","given":"Peter","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":772602,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70206734,"text":"70206734 - 2019 - Commentary: Variability in shelf sedimentation in response to fluvial sediment supply and coastal erosion over the past 1,000 Years in Monterey Bay, CA, United States","interactions":[],"lastModifiedDate":"2019-11-19T12:02:40","indexId":"70206734","displayToPublicDate":"2019-10-04T12:00:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Commentary: Variability in shelf sedimentation in response to fluvial sediment supply and coastal erosion over the past 1,000 Years in Monterey Bay, CA, United States","docAbstract":"A commentary on:\n\nVariability in Shelf Sedimentation in Response to Fluvial Sediment Supply and Coastal Erosion Over the Past 1,000 Years in Monterey Bay, CA, United States.\n\nby Carlin J., Addison J., Wagner A., Schwartz V., Hayward J., Severin V. (2019)\nFront. Earth Sci., 7:113. doi: 10.3389/feart.2019.00113","language":"English","publisher":"Frontiers ","doi":"10.3389/feart.2019.00256","usgsCitation":"Warrick, J.A., East, A.E., Storlazzi, C.D., and Conrad, J.E., 2019, Commentary: Variability in shelf sedimentation in response to fluvial sediment supply and coastal erosion over the past 1,000 Years in Monterey Bay, CA, United States: Frontiers in Earth Science, v. 7, 256, https://doi.org/10.3389/feart.2019.00256.","productDescription":"256","ipdsId":"IP-109988","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00256","text":"Publisher Index Page"},{"id":369332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":775589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205910,"text":"70205910 - 2019 - Physiological and gene transcription assays to assess responses of mussels to environmental changes","interactions":[],"lastModifiedDate":"2021-07-20T13:44:50.2918","indexId":"70205910","displayToPublicDate":"2019-10-04T07:53:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Physiological and gene transcription assays to assess responses of mussels to environmental changes","docAbstract":"Coastal regions worldwide face increasing management concerns due to natural and anthropogenic forces that have the potential to significantly degrade nearshore marine resources. The goal of our study was to develop and test a monitoring strategy for nearshore marine ecosystems in remote areas that are not readily accessible for sampling. Mussel species have been used extensively to assess ecosystem vulnerability to multiple, interacting stressors. We sampled bay mussels (Mytilus trossulus) in 2015 and 2016 from six intertidal sites in Lake Clark and Katmai National Parks and Preserves, in south-central Alaska. Reference ranges for physiological assays and gene transcription were determined for use in future assessment efforts. Both techniques identified differences among sites, suggesting influences of both large-scale and local environmental factors and underscoring the value of this combined approach to ecosystem health monitoring.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.7800","usgsCitation":"Counihan, K., Bowen, L., Ballachey, B., Coletti, H.A., Hollman, T., Pister, B., and Wilson, T.L., 2019, Physiological and gene transcription assays to assess responses of mussels to environmental changes: PeerJ, e7800, 33 p., https://doi.org/10.7717/peerj.7800.","productDescription":"e7800, 33 p.","ipdsId":"IP-110459","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":459612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.7800","text":"Publisher Index Page"},{"id":368198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Katmai National Park and Preserve, Lake Clark National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.4453125,\n 57.961503094284794\n ],\n [\n -152.490234375,\n 57.961503094284794\n ],\n [\n -152.490234375,\n 60.13056361691419\n ],\n [\n -156.4453125,\n 60.13056361691419\n ],\n [\n -156.4453125,\n 57.961503094284794\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Counihan, Katrina","contributorId":140780,"corporation":false,"usgs":false,"family":"Counihan","given":"Katrina","affiliations":[{"id":13561,"text":"Alaska Sea Life Center, Seward, AK","active":true,"usgs":false}],"preferred":false,"id":772836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":772835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballachey, Brenda 0000-0003-1855-9171 bballachey@usgs.gov","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":219667,"corporation":false,"usgs":true,"family":"Ballachey","given":"Brenda","email":"bballachey@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":772837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coletti, Heather A.","contributorId":187561,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":772838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hollman, Tuula","contributorId":219668,"corporation":false,"usgs":false,"family":"Hollman","given":"Tuula","email":"","affiliations":[{"id":40045,"text":"College of Fisheries and Ocean Sciences, Alaska Sea Life Center and University of Alaska","active":true,"usgs":false}],"preferred":false,"id":772839,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pister, Benjamin","contributorId":219669,"corporation":false,"usgs":false,"family":"Pister","given":"Benjamin","email":"","affiliations":[{"id":40046,"text":"Ocean Alaska Science and Learning Center, National Park Service","active":true,"usgs":false}],"preferred":false,"id":772840,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Tammy L","contributorId":219670,"corporation":false,"usgs":false,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L","affiliations":[{"id":40047,"text":"7Department of Natural Resource Management, South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":772841,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208122,"text":"70208122 - 2019 - Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models","interactions":[],"lastModifiedDate":"2020-01-29T16:24:01","indexId":"70208122","displayToPublicDate":"2019-10-03T13:36:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3766,"text":"Wildlife Biology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models","docAbstract":"Counts of grouse present at leks (breeding grounds) during spring are widely used to monitor population numbers and assess trends. However, only a proportion of birds available to count are detected resulting in a biased population index. We designed a study using an aerial integrated infrared imaging system (AIRIS) and experimental pseudo-leks to quantify sightability (proportion of birds detected) of conventional ground-based visual (GBV) surveys for greater sage-grouse Centrocercus urophasianus. Specifically, we calibrated AIRIS at pseudo-leks composed of known numbers of captively-raised birds, primarily ring-necked pheasant Phasianus colchicus. We then carried out AIRIS and GBV surveys, simultaneously, on nearby sage-grouse leks, allowing us to model AIRIS and GBV sightability. AIRIS detected ∼93% of birds on pseudo-leks while GBV detected ∼86% of sage-grouse on leks. Thus, the ground count observation error was –14% from the ‘true' number of male sage-grouse attending the leks. We also found sagebrush cover decreased sightability for GBV counts but did not influence sightability by AIRIS. Because standard GBV protocols typically make repeated counts of sage-grouse in a single morning, we also modeled repeated GBV counts using N-mixture models and found an 88% sightability, which was nearly the same as GBV sightability from the AIRIS analysis. This suggests that the use of repeated morning counts can potentially account for imperfect detection in the standard GBV surveys currently implemented. We also provide generalized correction values that could be employed by resource managers using either GBV or AIRIS to better estimate ‘true’ numbers of sage-grouse attending leks within similar environments to this study. The findings and interpretation presented can help guide effective monitoring protocols that account for observation error and improve accuracy of data used for population trend and abundance estimation.
","language":"English","publisher":"BioONE","doi":"10.2981/wlb.00552","usgsCitation":"Coates, P.S., Wann, G.T., Gillette, G.L., Ricca, M.A., Prochazka, B.G., Severson, J.P., Andrle, K.M., Espinosa, S.P., Casazza, M.L., and Delehanty, D.J., 2019, Estimating sightability of greater sage-grouse at leks using an aerial infrared system and N-mixture models: Wildlife Biology, v. 2019, no. 1, wlb.00552, 11 p., https://doi.org/10.2981/wlb.00552.","productDescription":"wlb.00552, 11 p.","ipdsId":"IP-100795","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":459615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2981/wlb.00552","text":"Publisher Index Page"},{"id":371652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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2019","interactions":[],"lastModifiedDate":"2019-10-04T06:18:29","indexId":"fs20193044","displayToPublicDate":"2019-10-03T10:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3044","displayTitle":"Assessment of Undiscovered Continuous Oil and Gas Resources in the Upper Ordovician Point Pleasant Formation and Utica Shale of the Appalachian Basin Province, 2019","title":"Assessment of undiscovered continuous oil and gas resources in the Upper Ordovician Point Pleasant Formation and Utica Shale of the Appalachian Basin Province, 2019","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable continuous mean resources of 1.8 billion barrels of oil and 117.2 trillion cubic feet of gas in the Upper Ordovician Point Pleasant Formation and Utica Shale of the Appalachian Basin Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193044","usgsCitation":"Enomoto, C.B., Trippi, M.H., Higley, D.K., Drake, R.M., II, Gaswirth, S.B., Mercier, T.J., Brownfield, M.E., Leathers-Miller, H.M., Le, P.A., Marra, K.R., Tennyson, M.E., Woodall, C.A., and Schenk, C.J., 2019, Assessment of undiscovered continuous oil and gas resources in the Upper Ordovician Point Pleasant Formation and Utica Shale of the Appalachian Basin Province, 2019: U.S. Geological Survey Fact Sheet 2019–3044, 2 p., https://doi.org/10.3133/fs20193044.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437313,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93RVVAL","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project - Appalachian Basin Province, Point Pleasant Formation and Utica Shale Assessment Unit Boundaries and Assessment Input Data Forms"},{"id":367873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3044/coverthb.jpg"},{"id":367874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3044/fs20193044.pdf","text":"Report","size":"848 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3044"},{"id":367898,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93RVVAL ","text":"USGS data release","description":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Appalachian Basin Province, Point Pleasant Formation and Utica Shale Assessment Unit Boundaries and Assessment Input Data Forms"}],"country":"United States","state":"New York, Ohio, Pennsylvania, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.407958984375,\n 38.16047628099622\n ],\n [\n -74.981689453125,\n 38.16047628099622\n ],\n [\n -74.981689453125,\n 42.94838139765314\n ],\n [\n -84.407958984375,\n 42.94838139765314\n ],\n [\n -84.407958984375,\n 38.16047628099622\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable continuous mean resources of 96.5 trillion cubic feet of gas in the Middle Devonian Marcellus Shale of the Appalachian Basin Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston,VA","doi":"10.3133/fs20193050","usgsCitation":"Higley, D.K., Enomoto, C.B., Leathers-Miller, H.M., Ellis, G.S., Mercier, T.J., Schenk, C.J., Trippi, M.H., Le, P.A., Brownfield, M.E., Woodall, C.A., Marra, K.R., and Tennyson, M.E., 2019, Assessment of undiscovered gas resources in the Middle Devonian Marcellus Shale of the Appalachian Basin Province, 2019: U.S. Geological Survey Fact Sheet 2019–3050, 2 p., https://doi.org/10.3133/fs20193050.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"N","ipdsId":"IP-108590","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":382921,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/70207372","text":"Controls on Petroleum Resources for the Devonian Marcellus Shale in the Appalachian Basin Province, Kentucky, West Virginia, Ohio, Pennsylvania, and New York"},{"id":382920,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/70217792","text":"Burial History Reconstruction of the Appalachian Basin in Kentucky, West Virginia, Ohio, Pennsylvania, and New York, Using 1D Petroleum System Models"},{"id":367867,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3050/fs20193050.pdf","text":"Report","size":"984 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3050"},{"id":367866,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3050/coverthb.jpg"},{"id":367907,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S948U5","text":"USGS data release","description":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Appalachian Basin Province, Middle Devonian Marcellus Shale Assessment Units and Input Data Forms"}],"country":"United States","state":"Maryland, New York, Ohio, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Middle Devonian Marcellus Shale","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.73779296875,\n 36.56260003738545\n ],\n [\n -74.102783203125,\n 36.56260003738545\n ],\n [\n -74.102783203125,\n 43.052833917627936\n ],\n [\n -83.73779296875,\n 43.052833917627936\n ],\n [\n -83.73779296875,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Measures of reproductive output in turtles are generally positively correlated with female body size. However, a full understanding of reproductive allometry in turtles requires logarithmic transformation of reproductive and body size variables prior to regression analyses. This allows for slope comparisons with expected linear or cubic relationships for linear to linear and linear to volumetric variables, respectively. We compiled scaling data using this approach from published and unpublished turtle studies (46 populations of 25 species from eight families) to quantify patterns among taxa. Our results suggest that for log–log comparisons of clutch size, egg width, egg mass, clutch mass, and pelvic aperture width to shell length, all scale hypoallometrically despite theoretical predictions of isometry. Clutch size generally scaled at ~1.7 to 2.0 (compared to an isometric expectation of 3.0), egg width at ~0.5 (compared to an expectation of 1.0), egg mass at ~1.1 to 1.3 (3.0), clutch mass at ~2.5 to 2.8 (3.0), and pelvic aperture width at 0.8–0.9 (1.0). We also found preliminary evidence that scaling may differ across years and clutches even in the same population, as well as across populations of the same species. Future investigators should aspire to collect data on all these reproductive parameters and to report log–log allometric analyses to test our preliminary conclusions regarding reproductive allometry in turtles.
The maps and graphs in this summary describe national streamflow conditions for water year 2018 (October 1, 2017, to September 30, 2018) in the context of streamflow ranks relative to the 89-year period of water years 1930–2018. The illustrations are based on observed data from the U.S. Geological Survey National Streamflow Network. Annual runoff in the Nation’s rivers and streams during water year 2018 was higher than the long-term (water years 1930–2018) mean annual runoff of 9.33 inches. Nationwide, the 2018 streamflow ranked 33d highest out of the 89 years.
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415 National Center
Reston, VA 20192
Laboratory trials conducted over the past decade at U.S. Geological Survey National Wildlife Health Center indicate that wild populations of prairie dogs (Cynomys spp.) display different degrees of susceptibility to experimental challenge with fully virulent Yersinia pestis, the causative agent of plague. We evaluated patterns in prairie dog susceptibility to plague to determine whether the historical occurrence of plague at location of capture was related to survival times of prairie dogs challenged with Y. pestis. We found that black-tailed prairie dogs (Cynomys ludovicianus) from South Dakota (captured prior to the detection of plague in the state), Gunnison's prairie dogs (Cynomys gunnisoni) from Colorado, and Utah prairie dogs (Cynomys parvidens) from Utah were most susceptible to plague. Though the susceptibility of black-tailed prairie dogs in South Dakota compared with western locations supports our hypothesis regarding historical exposure, both Colorado and Utah prairie dogs have a long history of exposure to plague. It is possible that for these populations, genetic isolation/bottle necks have made them more susceptible to plague outbreaks.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5684","usgsCitation":"Russell, R., Tripp, D.W., and Rocke, T.E., 2019, Differential plague susceptibility in species and populations of prairie dogs: Ecology and Evolution, v. 9, no. 20, p. 11962-11971, https://doi.org/10.1002/ece3.5684.","productDescription":"10 p., Data release","startPage":"11962","endPage":"11971","ipdsId":"IP-106563","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":459620,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5684","text":"Publisher Index Page"},{"id":418322,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AZREUM","text":"USGS data release","description":"USGS data release","linkHelpText":"Survival of prairie dogs (Cynomys spp.) challenged with Yersina pestis 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\"}}]}","volume":"9","issue":"20","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":773678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":773679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":773680,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204655,"text":"sir20195075 - 2019 - Potential interaction of groundwater and surface water including autonomous underwater vehicle reconnaissance at Nolin River Lake, Kentucky, 2016","interactions":[],"lastModifiedDate":"2019-10-02T17:00:48","indexId":"sir20195075","displayToPublicDate":"2019-10-02T13:12:29","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5075","displayTitle":"Potential Interaction of Groundwater and Surface Water Including Autonomous Underwater Vehicle Reconnaissance at Nolin River Lake, Kentucky, 2016","title":"Potential interaction of groundwater and surface water including autonomous underwater vehicle reconnaissance at Nolin River Lake, Kentucky, 2016","docAbstract":"The U.S. Geological Survey collaborated with the U.S. Army Corps of Engineers, Louisville District, on a synoptic study of water quality at Nolin River Lake during August 2016. The purpose of the study was to develop a better understanding of the potential for interaction between groundwater and surface water at Nolin River Lake, Kentucky. Groundwater can have properties that are measurably different from those in adjacent surface water, and inflows and outflows can be an important component of water quality and quantity. An improved understanding of potential interaction of groundwater and surface water at Nolin River Lake may be used to refine lake-management strategies. This study (1) compiled and interpreted existing information to characterize the hydrogeological setting and implications for potential interaction of groundwater and surface water in the Nolin River Lake watershed; (2) collected transects of onsite water-quality parameters using an autonomous underwater vehicle (AUV) in areas with potential for interaction of groundwater and surface water, including five sites on Nolin River Lake and one site on the Nolin River; and (3) collected discrete water-quality and phytoplankton community data at the same six sites.
A review of existing hydrogeologic information did not indicate the presence of karst features adjacent to or beneath Nolin River Lake that would facilitate groundwater interaction with the reservoir. Observations leading to this conclusion include (1) limestone that is adjacent to the shoreline and perhaps beneath the lake, is overlain with siliciclastic rocks and fine-grained sediment that inhibits infiltration and development of karst features that encourage rapid groundwater flow; (2) the geologic deposits surrounding the reservoir are described as having limited or no potential for development of karst features, some exceptions may exist in tributary valleys; (3) very few karst features were mapped within 1 mile of the reservoir or in the area currently occupied by the reservoir; and (4) faults that intersect the reservoir but may not possess hydraulic properties that cause the faults to be conduits for groundwater flow. Groundwater interaction with reservoir tributaries is likely more common in areas of the watershed upstream from Nolin River Lake where karst hydrogeology is prevalent.
Results of water-quality surveys using an AUV from August 15 to 19, 2016, did not identify areas of anomalous values that might indicate groundwater inflows through preferential flow zones. Spatial distributions of water-quality parameters were generally uniform within each constant-depth layer. The constant-depth layers were selected to be above, within, and below the thermocline and ranged from the water surface to 25 feet. Surveys near the bottom of the reservoir that might have been more sensitive to groundwater inflows were not done because presurvey data were not available to indicate locations of obstacles that could ensnare the AUV. Water-quality data collected with the AUV did identify water-quality anomalies where stream tributaries were discharging to the reservoir.
The discrete water-quality samples indicated uniformity among the five reservoir sites. The riverine site that is immediately upstream from Nolin River Lake, however, had some unique water-quality characteristics relative to sites on the reservoir. The highest concentrations of nitrate plus nitrite as nitrogen (0.145 milligrams per liter [mg/L]), total phosphorous (0.07 mg/L), chlorophyll a (36.1 micrograms per liter), and pheophytin a (10.2 micrograms per liter) were measured at the Nolin River Lake riverine site (site 2NRR20034). The concentrations of nutrients and chlorophyll a at the riverine site did exceed the 25th percentile of median concentrations measured by the U.S. Environmental Protection Agency (EPA) at other lakes and reservoirs in EPA level IV ecoregion 71a. Concentrations of most nutrients and chlorophyll a at the five reservoir sites also exceeded the 25th percentile of median concentrations in EPA level IV ecoregion 72h. The exception was the concentrations of total phosphorus as phosphorus at the reservoir sites that were at or below the 25th percentile of median concentrations measured by EPA (0.03 mg/L). Concentrations of orthophosphate as phosphorus were less than the method detection limit of 0.004 mg/L at all sites. The phytoplankton community in Nolin River Lake was almost exclusively (greater than 90 percent of total phytoplankton abundance) cyanobacteria, also known as blue-green algae. A species of Cylindrospermopsis dominated the cyanobacterial community at the five reservoir sites, while Chroococcus microscopicus was most abundant at the riverine site. Cyanobacterial cell densities ranged from 10,000 to 198,067,460 cells per liter in five areas in the reservoir and from 4,800 to 73,751,253 cells per liter at the riverine site.
Multiple potential sources of water to Nolin River Lake include direct precipitation, overland flow, interflow, groundwater, and surface water. Understanding the exact contribution of each of these components to the water budget at Nolin River Lake may help the U.S. Army Corps of Engineers manage the water quality, water quantity, and biological communities in the reservoir. Additional hydrogeologic and water-quality data that builds on the results of this study may refine the inferences of this study; for example, deeper AUV surveys that target the largest fault zones might further the understanding of the potential for groundwater flow through those features. A complete understanding of the reservoir hydrology, however, may require the use of scientific methods intended for water bodies as large as Nolin River Lake, such as aerial infrared photography and imagery; water mass, chemical, and isotopic balance studies; geophysical measurements; and numerical simulations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195075","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Louisville District","usgsCitation":"Crain, A.S., Boldt, J.A., Bayless, E.R., Bunch, A.R., Young, J.L., Thomason, J.C., and Wolf, Z.L., 2019, Potential interaction of groundwater and surface water including autonomous underwater vehicle reconnaissance at Nolin River Lake, Kentucky, 2016: U.S. Geological Survey Scientific Investigations Report 2019–5075, 36 p., https://doi.org/10.3133/sir20195075.\n","productDescription":"Report: vi, 36 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-085091","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":367882,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5075/sir20195075.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5075"},{"id":367881,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5075/coverthb.jpg"},{"id":367883,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F798857D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-Quality Datasets from Synoptic Surveys in Nolin River Lake, Kentucky, using an Autonomous Underwater Vehicle, Discrete Sampling, and Depth Profiles, August 2016"}],"country":"United States","state":"Kentucky","otherGeospatial":"Nolin River Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.28387451171875,\n 37.25929865437848\n ],\n [\n -86.0504150390625,\n 37.25929865437848\n ],\n [\n -86.0504150390625,\n 37.40780092202727\n ],\n [\n -86.28387451171875,\n 37.40780092202727\n ],\n [\n -86.28387451171875,\n 37.25929865437848\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299–1906
In viviparous organisms, the ability to feed while pregnant may mitigate energetic trade-offs experienced during the reproductive process and enhance fecundity. However, anorexia during pregnancy has been reported in many crotaline snakes. The potential costs and benefits of feeding while pregnant are not completely described in the literature, and experimental studies have been conducted in a limited number of taxa, rendering our understanding of the forces that may underlie the evolution of anorexia in pregnant snakes incomplete. Here, we examine the impact of food supplementation during mid to late pregnancy on mothers and offspring in a viviparous crotaline snake species, the Pygmy Rattlesnake (Sistrurus miliarius). Specifically, we offered multiple large meals to mothers held in outdoor enclosures and measured a suite of maternal and offspring traits including maternal body condition, offspring length and mass, maternal disease state, and offspring foraging behaviors. We focused on interactions between feeding, clinical signs of snake fungal disease (SFD), and the presence of its causative agent, Ophidiomyces ophiodiicola, in mothers. Pregnant females fed readily when offered food, but feeding did not impact offspring traits. Food supplementation significantly increased maternal postparturient body condition, but also increased clinical signs of disease in mothers and led to a significantly higher reproductive failure rate in the treatment group, particularly in mothers afflicted with SFD. Our results suggest that food supplementation during pregnancy may disrupt the reproductive process in pregnant rattlesnakes, and that such disruption is particularly pronounced in mothers suffering from SFD.
","language":"English","publisher":"BioOne","doi":"10.1670/18-147","usgsCitation":"Lind, C.M., Clark, A., Smiley-Walters, S.A., Taylor, D., Isidoro Ayza, M., Lorch, J.M., and Farrell, T.M., 2019, Interactive effects of food supplementation and snake fungal disease on pregnant Pygmy Rattlesnakes and their offspring: Journal of Herpetology, v. 53, no. 4, p. 282-288, https://doi.org/10.1670/18-147.","productDescription":"7 p.","startPage":"282","endPage":"288","ipdsId":"IP-101778","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":379984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lind, Craig M.","contributorId":201569,"corporation":false,"usgs":false,"family":"Lind","given":"Craig","email":"","middleInitial":"M.","affiliations":[{"id":27623,"text":"Stetson University","active":true,"usgs":false}],"preferred":false,"id":803585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Amber","contributorId":244248,"corporation":false,"usgs":false,"family":"Clark","given":"Amber","email":"","affiliations":[{"id":27623,"text":"Stetson University","active":true,"usgs":false}],"preferred":false,"id":803586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smiley-Walters, Sarah A","contributorId":244249,"corporation":false,"usgs":false,"family":"Smiley-Walters","given":"Sarah","email":"","middleInitial":"A","affiliations":[{"id":27623,"text":"Stetson University","active":true,"usgs":false}],"preferred":false,"id":803587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Daniel 0000-0001-5391-0321","orcid":"https://orcid.org/0000-0001-5391-0321","contributorId":216693,"corporation":false,"usgs":true,"family":"Taylor","given":"Daniel","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":803588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Isidoro Ayza, Marcos 0000-0002-9380-7254 misidoroayza@usgs.gov","orcid":"https://orcid.org/0000-0002-9380-7254","contributorId":192509,"corporation":false,"usgs":true,"family":"Isidoro Ayza","given":"Marcos","email":"misidoroayza@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":803589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":803590,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Farrell, Terence M.","contributorId":176253,"corporation":false,"usgs":false,"family":"Farrell","given":"Terence","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":803591,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205773,"text":"70205773 - 2019 - Prediction and inference of flow-duration curves using multi-output neural networks","interactions":[],"lastModifiedDate":"2019-10-02T12:09:28","indexId":"70205773","displayToPublicDate":"2019-10-02T12:06:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and inference of flow-duration curves using multi-output neural networks","docAbstract":"We develop multi-output neural network models (MNNs) to predict flow-duration curves (FDCs) in 9,203 ungaged locations in the Southeastern United States for six decades between 1950-2009. The model architecture contains multiple response variables in the output layer that correspond to individual quantiles along the FDC. During training, predictions are made for each quantile, and a combined loss function is used for back propagation and parameter updating. The loss function accounts for the covariance between the quantiles and generates physically consistent outputs (i.e., monotonically increasing quantiles with increasing nonexceedance probabilities). We use neural-network dropout to generate posterior-predictive distributions for FDCs, and test model performance under cross validation. Finally, we demonstrate how local surrgotate models, via the Local Interpretable Model-agnostic Explanations (LIME) method, can be used to infer the relation between basin characteristics and the predicted FDCs. Results suggest that MNNs can learn the monotonic relations between adjacent quantiles on an FDC, they result in better predictions than single output neural-network models that predict each quantile independently, and basin characteristics are most useful for predicting smaller quantiles, whereas bias terms from neighboring quantiles are most informative for predicting higher quantiles.","language":"English","publisher":"Wiley","doi":"10.1029/2018WR024463","usgsCitation":"Worland, S.C., Steinschneider, S., Asquith, W.H., Knight, R., and Wieczorek, M., 2019, Prediction and inference of flow-duration curves using multi-output neural networks: Water Resources Research, v. 55, no. 8, p. 6850-6868, https://doi.org/10.1029/2018WR024463.","productDescription":"19 p.","startPage":"6850","endPage":"6868","onlineOnly":"N","ipdsId":"IP-091599","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":459623,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr024463","text":"Publisher Index Page"},{"id":437314,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGKZZV","text":"USGS data release","linkHelpText":"Estimated quantiles for the pour points of 9,203 level-12 Hydrologic Unit Code in the Southeastern United States--1950--2010"},{"id":367923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steinschneider, Scott 0000-0002-8882-1908","orcid":"https://orcid.org/0000-0002-8882-1908","contributorId":206359,"corporation":false,"usgs":false,"family":"Steinschneider","given":"Scott","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":772283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wieczorek, Michael E. 0000-0003-0999-5457 mewieczo@usgs.gov","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":178736,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael E.","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772286,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70205770,"text":"70205770 - 2019 - Applying the ecology of aquatic–terrestrial linkages to freshwater and riparian management","interactions":[],"lastModifiedDate":"2020-01-03T10:05:01","indexId":"70205770","displayToPublicDate":"2019-10-02T11:51:36","publicationYear":"2019","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":"Applying the ecology of aquatic–terrestrial linkages to freshwater and riparian management","docAbstract":"Global stressors such as climate change, invasive species, urbanization, agricultural practices, and pollution can alter aquatic resource subsidies to terrestrial consumers. The effects of these stressors on timing, quality, and quantity of aquatic subsidies, such as adult aquatic insects, to birds, herpetofauna, and mammals, have large implications for wildlife management (Baxter et al. 2004, Saunders and Fausch 2007, Walters et al. 2008, Sullivan and Rodewald 2012, Morrissey et al. 2015, Kraus et al. 2016, Larsen et al. 2016, Sullivan et al. 2019). For example, insect-mediated contaminant transport from polluted rivers expose song bird nestlings and other protected birds to potentially toxic levels of persistent organic contaminants and pharmaceuticals (Walters et al. 2010, Richmond et al. 2018). Recent declines in aquatic insect production caused by pollution and changes in land use have been tied to global declines in terrestrial insectivores such as birds and bats (Hallmann et al. 2014, Morrissey et al. 2015, Raby et al. 2018). These natural-resource impacts from aquatic–terrestrial exposure and loss of resource subsidies are leading to changes in monitoring protocols and how management agencies evaluate the effectiveness of corrective remedies (Muehlbauer et al. 2019). For researchers interested in the application of resource subsidy research, a logical next step is to help practitioners anticipate effects of global stressors on aquatic-terrestrial linkages and incorporate these principles into decision making.
","language":"English","publisher":"University of Chicago Press Journals","doi":"10.1086/705994","usgsCitation":"Kraus, J.M., 2019, Applying the ecology of aquatic–terrestrial linkages to freshwater and riparian management: Freshwater Science, v. 38, no. 4, p. 917-918, https://doi.org/10.1086/705994.","productDescription":"2 p.","startPage":"917","endPage":"918","ipdsId":"IP-112487","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":367926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":772270,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70205674,"text":"70205674 - 2019 - A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California","interactions":[],"lastModifiedDate":"2019-11-13T13:43:35","indexId":"70205674","displayToPublicDate":"2019-10-02T11:26:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California","docAbstract":"Incorporating coastal ecosystems in climate adaptation planning is needed to maintain the well-being of both natural and human systems. Our vulnerability study uses a multidisciplinary approach to evaluate climate change vulnerability of an urbanized coastal community that could serve as a model approach for communities worldwide, particularly in similar Mediterranean climates. We synthesize projected changes in climate, coastal erosion and flooding, watershed runoff and impacts to two important coastal ecosystems, sandy beaches and coastal salt marshes. Using downscaled climate models along with other regional models, we find that temperature, extreme heat events, and sea level are expected to increase in the future, along with more intense rainfall events, despite a negligible change in annual rainfall. Consequently, more droughts are expected but the magnitude of larger flood events will increase. Associated with the continuing rise of mean sea level, extreme coastal water levels will occur with increasingly greater magnitudes and frequency. Severe flooding will occur for both natural (wetlands, beaches) and built environments (airport, harbor, freeway, and residential areas). Adaptation actions can reduce the impact of rising sea level, which will cause losses of sandy beach zones and salt marsh habitats that support the highest biodiversity in these ecosystems, including regionally rare and endangered species, with substantial impacts occurring by 2050. Providing for inland transgression of coastal habitats, effective sediment management, reduced beach grooming and removal of shoreline armoring are adaptations that would help maintain coastal ecosystems and the beneficial services they provide.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2019.104921","usgsCitation":"Myers, M., Barnard, P., Beighley, E., Cayan, D., Dugan, J.E., Feng, D., Iacobellis, S.F., Melack, J.M., and Page, H.M., 2019, A multidisciplinary coastal vulnerability assessment for local government focused on ecosystems, Santa Barbara area, California: Ocean and Coastal Management, v. 182, 104921, https://doi.org/10.1016/j.ocecoaman.2019.104921.","productDescription":"104921","ipdsId":"IP-107676","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocecoaman.2019.104921","text":"Publisher Index Page"},{"id":367925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Barbara","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.48249816894531,\n 34.41370754457088\n ],\n [\n -119.47906494140624,\n 34.4142740103038\n ],\n [\n -119.86564636230467,\n 34.44485746154028\n ],\n [\n -119.8773193359375,\n 34.36384353883067\n ],\n [\n -119.47631835937499,\n 34.36100946506246\n ],\n [\n -119.48249816894531,\n 34.41370754457088\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"182","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Monique","contributorId":219345,"corporation":false,"usgs":false,"family":"Myers","given":"Monique","email":"","affiliations":[{"id":39996,"text":"California Sea Grant","active":true,"usgs":false}],"preferred":false,"id":772060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":772059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beighley, Edward","contributorId":219346,"corporation":false,"usgs":false,"family":"Beighley","given":"Edward","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":772061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayan, Daniel R.","contributorId":219347,"corporation":false,"usgs":false,"family":"Cayan","given":"Daniel R.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":772062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugan, Jenifer E.","contributorId":219348,"corporation":false,"usgs":false,"family":"Dugan","given":"Jenifer","email":"","middleInitial":"E.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772063,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feng, Dongmei","contributorId":219349,"corporation":false,"usgs":false,"family":"Feng","given":"Dongmei","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":772064,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Iacobellis, Samuel F.","contributorId":219350,"corporation":false,"usgs":false,"family":"Iacobellis","given":"Samuel","email":"","middleInitial":"F.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":772065,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Melack, John M.","contributorId":219351,"corporation":false,"usgs":false,"family":"Melack","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772066,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Page, Henry M.","contributorId":219352,"corporation":false,"usgs":false,"family":"Page","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":772067,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205702,"text":"70205702 - 2019 - A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data","interactions":[],"lastModifiedDate":"2019-10-02T11:26:38","indexId":"70205702","displayToPublicDate":"2019-10-02T11:26:30","publicationYear":"2019","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 spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data","docAbstract":"This paper introduces our research in developing a probabilistic model to extract linear terrain features from high resolution DEM (Digital Elevation Model) data. The proposed model takes full advantage of spatio-contextual information to characterize terrain changes. It first derives a quantifiable measure of spatio-contextual patterns of linear terrain feature, such as ridgelines, valley lines and crater boundaries, and then adopts multiple neighborhood analysis and a probability model to address data uncertainty in terrain surface modeling. Different from traditional approaches, the proposed model has the ability to achieve near-automated processing, and to support effective extraction of terrain features in both smooth and rough surfaces. Through a series of experiments, we demonstrate that the proposed approach outperforms existing techniques, including: thresholding, stream/drainage network analysis, visual descriptor, object-based image analysis and edge detection. We hope this work contributes to both the geospatial data science and geomorphology communities with a new way of utilizing high-resolution imagery in terrain analysis.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/13658816.2018.1554814","usgsCitation":"Zhou, X., Li, W., and Arundel, S., 2019, A spatio-contextual probabilistic model for extracting linear features in hilly terrain from high-resolution DEM data: International Journal of Geographical Information Science, v. 33, no. 4, p. 666-686, https://doi.org/10.1080/13658816.2018.1554814.","productDescription":"21 p.","startPage":"666","endPage":"686","ipdsId":"IP-085062","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":367920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Xiran","contributorId":219357,"corporation":false,"usgs":false,"family":"Zhou","given":"Xiran","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":772120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","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":772119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205665,"text":"70205665 - 2019 - Modeling sediment bypassing around idealized rocky headlands","interactions":[],"lastModifiedDate":"2019-10-02T11:19:58","indexId":"70205665","displayToPublicDate":"2019-10-02T11:19:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Modeling sediment bypassing around idealized rocky headlands","docAbstract":"Alongshore sediment bypassing rocky headlands remains understudied despite the importance of characterizing littoral processes for erosion abatement, beach management, and climate change adaptation. To address this gap, a numerical model sediment transport study was developed to identify controlling factors and mechanisms for sediment headland bypassing potential. Four idealized headlands were designed to investigate sediment flux around the headlands using the process-based hydrodynamic model Delft-3D and spectral wave model SWAN. The 120 simulations explored morphologies, substrate compositions, sediment grain sizes, and physical forcings (i.e., tides, currents, and waves) commonly observed in natural settings. A generalized analytical framework based on flow disruption and sediment volume was used to refine which factors and conditions were more useful to address sediment bypassing. A bypassing parameter was developed for alongshore sediment flux between upstream and downstream cross-shore transects to determine the degree of blockage by a headland. The shape of the headland heavily influenced the fate of the sediment by changing the local angle between the shore and the incident waves, with oblique large waves generating the most flux. All headlands may allow sediment flux, although larger ones blocked sediment more effectively, promoting their ability to be littoral cell boundaries. The controlling factors on sediment bypassing were determined to be wave angle, size, and shape of the headland, and sediment grain size.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse7020040","usgsCitation":"Douglas A. George, John L. Largier, Pasternack, G.B., Barnard, P., Storlazzi, C.D., and Erikson, L.H., 2019, Modeling sediment bypassing around idealized rocky headlands: Journal of Marine Science and Engineering, v. 7, no. 2, 40; 37 p., https://doi.org/10.3390/jmse7020040.","productDescription":"40; 37 p.","ipdsId":"IP-111887","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse7020040","text":"Publisher Index Page"},{"id":367918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas A. George","contributorId":219341,"corporation":false,"usgs":false,"family":"Douglas A. 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A novel combination of numerical modeling and statistical methods allows estimation of regional RTDs with unprecedented speed. In this method, particle RTDs are generated in 30 type locales in the northeastern glaciated U.S using automated generalized finite-difference groundwater flow and advective transport models. Targets for statistical learning were created from particle RTDs by fitting Weibull, gamma, and inverse Gaussian distributions. Whole-basin flux-weighted RTDs were well fit by one-component Weibull distributions. Flux-weighted RTDs at stressed receptors such as wells often produced more complicated RTDs that required a two-component mixture to fit. A Multitask Lasso regression was trained on the parametric RTDs using hydrogeographic features of the modeled areas as explanatory features. In this way, RTDs are regionalized using mappable physical features such as recharge and aquifer volume. The shape, location, and scale parameters of the parametric RTDs are strongly related to the mean exponential age. The shape parameter of the distribution, which controls deviation from exponential, is additionally a function of aquifer heterogeneity and hydrologic features. Regionalized RTDs provide useful metrics with respect to groundwater lag times and solute loading to streams. The lag time between input and output contained in the RTD is critical to understanding the relation between the land surface and human and ecological receptors.","language":"English","publisher":"Wiley","doi":"10.1029/2017WR021531","usgsCitation":"Starn, J., and Belitz, K., 2019, Regionalization of groundwater residence time using metamodeling: Water Resources Research, v. 54, no. 9, p. 6357-6373, https://doi.org/10.1029/2017WR021531.","productDescription":"17 p.","startPage":"6357","endPage":"6373","ipdsId":"IP-086784","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr021531","text":"Publisher Index Page"},{"id":367916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"9","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. 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These volumes are from more than 11,700 non-commingled wells. Areas of greatest production and future potential for gas and NGL from the Marcellus Shale are within and near the northeast-trending Rome trough in northern West Virginia and Pennsylvania. Southernmost New York, eastern Ohio, western Virginia, and Maryland also contain petroleum potential and (or) reserves. A confluence of factors enhances gas and NGL reserves and resources in the Marcellus Shale. These include (1) brittleness based on lithofacies composition; (2) thickness and distribution of brittle and organic-rich shale; (3) measured thermal maturity of 1% vitrinite reflectance and greater; (4) at least 2 weight percent total organic carbon; (5) dense and complex fracturing and faulting; (6) presence of evaporite beds in the underlying Silurian Salina Group; (7) potential overpressure; (8) current depths of 1,370 m (4,500 ft) and greater; and (9) predominately horizontal wells with laterals that are oriented to the northwest or southeast, or roughly perpendicular to the direction of maximum horizontal stress, and that cross major fault and fracture sets.","language":"English","publisher":"The Rocky Mountain Association of Geologists","doi":"10.31582/rmag.mg.56.4.323","usgsCitation":"Higley, D., Enomoto, C., and Leathers-Miller, H.M., 2019, Controls on petroleum resources for the Devonian Marcellus Shale in the Appalachian Basin Province, Kentucky, West Virginia, Ohio, 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