The pink-footed shearwater Ardenna creatopus has a breeding range restricted to 3 central-Chilean islands and travels north in the eastern Pacific Ocean during the non-breeding period. Despite its Vulnerable IUCN status, the locations and relative importance of core non-breeding areas and migratory pathways of the species are not well understood. During 5 years between 2006 and 2015, we tracked the movements of 42 after-hatch-year pink-footed shearwaters in the non-breeding season using satellite tags. Tracked shearwaters exhibited 2 post-breeding-season migration strategies: 28% of individuals traveled 1600-2500 km north from their colonies to spend the entire non-breeding season off Peru, and 72% traveled 8000-11000 km north to waters off western North America (Baja California, Mexico, to southernmost Canada). Individuals that traveled to North America stopped in Peruvian waters on each leg of the migration, making this a migratory bottleneck. Core non-breeding-season areas included continental shelf and slope waters off Trujillo to Lima (Peru), central Baja California (Mexico), southern to central California (USA), and central Oregon (USA) to southern Vancouver Island (Canada). Of 12 national exclusive economic zones (EEZs) encountered north of their breeding range, birds primarily utilized the USA, Peru and Mexico, and to a lesser degree Chile, Canada, and Ecuador. Bycatch in fisheries was recently identified as a significant at-sea threat to pink-footed shearwaters, and we found evidence of pink-footed shearwater bycatch in 6 EEZs encountered by tracked birds, although quantification of bycatch magnitude is variable and not all fisheries have been studied.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr00969","usgsCitation":"Felis, J.J., Adams, J., Hodum, P., Carle, R., and Colodro, V., 2019, Eastern Pacific migration strategies of pink-footed shearwaters Ardenna creatopus: Implications for fisheries interactions and international conservation: Endangered Species Research, v. 39, p. 269-282, https://doi.org/10.3354/esr00969.","productDescription":"14 p.","startPage":"269","endPage":"282","ipdsId":"IP-104256","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467381,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00969","text":"Publisher Index Page"},{"id":366854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":769143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Josh","contributorId":218388,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":769142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodum, Peter 0000-0003-2160-5132","orcid":"https://orcid.org/0000-0003-2160-5132","contributorId":169797,"corporation":false,"usgs":false,"family":"Hodum","given":"Peter","email":"","affiliations":[{"id":25597,"text":"Oikonos Ecosystem Knowledge","active":true,"usgs":false}],"preferred":false,"id":769144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carle, Ryan D.","contributorId":213443,"corporation":false,"usgs":false,"family":"Carle","given":"Ryan D.","affiliations":[{"id":25597,"text":"Oikonos Ecosystem Knowledge","active":true,"usgs":false}],"preferred":false,"id":769145,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colodro, Valentina 0000-0001-9285-3171","orcid":"https://orcid.org/0000-0001-9285-3171","contributorId":169798,"corporation":false,"usgs":false,"family":"Colodro","given":"Valentina","email":"","affiliations":[{"id":25597,"text":"Oikonos Ecosystem Knowledge","active":true,"usgs":false}],"preferred":false,"id":769146,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216451,"text":"70216451 - 2019 - Genomic identity of white oak species in an eastern North American syngameon","interactions":[],"lastModifiedDate":"2020-11-18T16:23:42.581442","indexId":"70216451","displayToPublicDate":"2019-08-08T10:17:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":800,"text":"Annals of the Missouri Botanical Garden","active":true,"publicationSubtype":{"id":10}},"title":"Genomic identity of white oak species in an eastern North American syngameon","docAbstract":"The eastern North American white oaks, a complex of approximately 16 potentially interbreeding species, have become a classic model for studying the genetic nature of species in a syngameon. Genetic work over the past two decades has demonstrated the reality of oak species, but gene flow between sympatric oaks raises the question of whether there are conserved regions of the genome that define oak species. Does gene flow homogenize the entire genome? Do the regions of the genome that distinguish a species in one part of its range differ from the regions that distinguish it in other parts of its range, where it grows in sympatry with
different species? Or are there regions of the genome that are relatively conserved across species ranges? In this study, we revisit seven species of the eastern North American white oak syngameon using a set of 80 single-nucleotide polymorphisms (SNPs) selected in a previous study because they show differences among, and consistency within, the species. We test the hypothesis that there exist segments of the genome that do not become homogenized by repeated introgression, but retain distinct alleles characteristic of each species. We undertake a range-wide sampling to investigate whether SNPs that appeared to be fixed based on a relatively small sample in our previous work are fixed or nearly fixed across the range of the species. Each of the seven species remains genetically distinct across its range, given our diagnostic set of markers, with relatively few individuals exhibiting admixture of multiple species. SNPs map back to all 12 Quercus linkage groups (chromosomes) and are separated from each other by an average of 7.47 million bp (± 8.74 million bp, SD), but are significantly clustered relative to a random null distribution, suggesting that our SNP toolkit reflects genome-wide patterns of divergence while potentially being concentrated in regions of the genome that reflect a higher-than-average history of among-species divergence. This application of a DNA toolkit designed for the simple problem of identifying species in the field has two important implications. First, the eastern North American white oak syngameon is composed of entities that most taxonomists would consider “good species.” Second, and more fundamentally, species in the syngameon are genetically coherent because characteristic portions of the genome remain divergent despite a history of introgression. Understanding the conditions under which some loci diverge while others introgress is key to understanding the origins and maintenance of global tree diversity.
Quagga (Dreissena rostriformis bugensis) and zebra (D. polymorpha) mussels are broadcast spawners that produce planktonic, free swimming veligers, a life history strategy dissimilar to native North American freshwater bivalves. Dreissenid veligers require highly nutritious food to grow and survive, and thus may be susceptible to increased mortality rates during harsh environmental conditions like cyanobacteria blooms. However, the impact of cyanobacteria and one of the toxins they can produce (microcystin) has not been evaluated in dreissenid veligers. Therefore, we exposed dreissenid veligers to eleven distinct cultures (isolates) of cyanobacteria representing Anabaena, Aphanizomenon, Dolichospermum, Microcystis, and Planktothrixspecies and the cyanotoxin microcystin to determine the lethality of cyanobacteria on dreissenid veligers. Six-day laboratory bioassays were performed in microplates using dreissenid veligers collected from the Detroit River, Michigan, USA. Veligers were exposed to increasing concentrations of cyanobacteria and microcystin using the green algae Chlorella minutissima as a control. Based on dose response curves formulated from a Probit model, the LC50 values for cyanobacteria used in this study range between 15.06 and 135.06 μg/L chlorophyll-a, with the LC50 for microcystin-LR at 13.03 μg/L. Because LC50 values were within ranges observed in natural waterbodies, it is possible that dreissenid recruitment may be suppressed when veliger abundances overlap with seasonal cyanobacteria blooms. Thus, the toxicity of cyanobacteria to dreissenid veligers may be useful to include in models forecasting dreissenid mussel abundance and spread.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoenv.2019.109426","usgsCitation":"Boegehold, A.G., Johnson, N., and Kashian, D.R., 2019, Bloom forming cyanobacteria can adversely affect zebra and quagga mussel veligers: Ecotoxicology and Environmental Safety, v. 182, Article 109426, https://doi.org/10.1016/j.ecoenv.2019.109426.","productDescription":"Article 109426","ipdsId":"IP-109520","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoenv.2019.109426","text":"Publisher Index Page"},{"id":366365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"182","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boegehold, Anna G.","contributorId":205600,"corporation":false,"usgs":false,"family":"Boegehold","given":"Anna","email":"","middleInitial":"G.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":767856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":767855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kashian, Donna R.","contributorId":205602,"corporation":false,"usgs":false,"family":"Kashian","given":"Donna","email":"","middleInitial":"R.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":767857,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204645,"text":"70204645 - 2019 - Promoting change in common tern (Sterna hirundo) nest site selection to minimize construction related disturbance","interactions":[],"lastModifiedDate":"2019-08-09T10:08:17","indexId":"70204645","displayToPublicDate":"2019-08-08T08:09:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Promoting change in common tern (Sterna hirundo) nest site selection to minimize construction related disturbance","title":"Promoting change in common tern (Sterna hirundo) nest site selection to minimize construction related disturbance","docAbstract":"With dramatic declines in waterbird populations around the globe, wildlife managers have taken great care to minimize disturbance to breeding waterbird colonies. However, sometimes disturbance cannot be avoided and other actions must be considered. During the 2017 breeding season, a colony of Sterna hirundo (Common terns) were deterred from a historic nesting site due to concerns that nearby restoration related construction activities would result in continued disturbances and eventual nest abandonment. Deterrence involved placing overhead lines with flagging 1.5m above the ground surface throughout the historic nesting site early in the nesting season. Concurrently, breeding pairs of S. hirundo from the historic nesting site were encouraged to relocate to a nearby location where construction disturbance was considered minimal via a mix of social attractants (digital calls and decoys). This paired approach of deterrence and attraction was considered successful at relocating the colony, with 240 active S. hirundo nests at the relocation site. While nine nests were established in the historic colony when only diagonal and perpendicular overhead lines were present, no additional nests constructed after overhead parallel lines were added. Eggs (n=13) from these early nests were transferred into similar aged nests in the relocation colony and allowed to incubate naturally with an existing clutch. Eleven of the 13 relocated eggs successfully hatched. The success of this project shows that it is possible, with careful planning and coordination, for construction activities at habitat restoration sites to continue uninterrupted and still allow for successful nesting.
","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.37.3.143","usgsCitation":"McGowan, P.C., Sullivan, J.D., Callahan, C., Schultz, W., Wall, J.L., and Prosser, D., 2019, Promoting change in common tern (Sterna hirundo) nest site selection to minimize construction related disturbance: Ecological Restoration, v. 37, no. 3, p. 143-147, https://doi.org/10.3368/er.37.3.143.","productDescription":"5 p.","startPage":"143","endPage":"147","ipdsId":"IP-094874","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":437369,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZKCA0R","text":"USGS data release","linkHelpText":"Promoting Change in Common Tern (Sterna hirundo) Nest Site Selection to Minimize Construction Related Disturbance"},{"id":366359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":767901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":767902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callahan, Carl C.","contributorId":217953,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, William","contributorId":217954,"corporation":false,"usgs":false,"family":"Schultz","given":"William","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wall, Jennifer L.","contributorId":205845,"corporation":false,"usgs":false,"family":"Wall","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":767905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217952,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":767900,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234294,"text":"70234294 - 2019 - Size selectivity of sampling gears used to sample Kokanee","interactions":[],"lastModifiedDate":"2022-08-08T11:47:10.873554","indexId":"70234294","displayToPublicDate":"2019-08-08T06:44:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Size selectivity of sampling gears used to sample Kokanee","docAbstract":"Kokanee Oncorhynchus nerka provide valued recreational fisheries and also serve as a prey resource for economically, socially, and ecologically important fishes. As such, management of kokanee is a major focus of natural resource agencies. Kokanee are typically monitored using midwater trawls, but the interpretation of data collected using midwater trawls is difficult due to the unknown size selectivity of the gear. We sought to assess the length selectivity of midwater trawls by comparing estimates obtained from midwater trawls with estimates obtained from gill nets adjusted for size selectivity. Experimental curtain gill nets and midwater trawls were used in conjunction to sample kokanee in seven lentic systems in Idaho. The size selectivity of gill nets was estimated by accounting for the probability of encounter and the probability of retention. Estimates of size selectivity were then used to adjust the length distribution of fish sampled in gill nets. The adjusted length distribution of fish sampled in gill nets was compared with estimates obtained from midwater trawls to identify potential size selectivity of midwater trawls. A pattern of size selectivity was apparent for both sampling techniques. The average length of kokanee sampled with midwater trawls was 111 mm; whereas, kokanee sampled with gill nets had a mean length of 235 mm. Our results suggest experimental gill nets are useful for common sampling of kokanee (e.g., trend monitoring) because the gear is less size selective than midwater trawls and is adjustable for size selectivity. However, midwater trawls are likely the best gear for addressing questions associated with early life history. Overall, our results provide a better understanding of gill-net and midwater trawl selectivity and ultimately improve the ability to sample and manage the species.
1. Drylands play a dominant role in global carbon cycling and are particularly vulnerable to increasing temperatures, but our understanding of how dryland ecosystems will respond to climatic change remains notably poor. Considering that the area of drylands is projected to increase 11–23% by 2100, understanding the impacts of warming on the functions and services furnished by these arid and semiarid ecosystems has numerous implications.
2.In a unique 13‐year ecosystem warming experiment in a southwestern U.S. dryland, we investigated the consequences of rising temperature on Achnatherum hymenoides, a widespread, keystone grass species on the Colorado Plateau. We tracked individual‐ and population‐level responses to identify optimal strategies that may have been masked if considering only one level of plant response.
3.We found several factors combined to affect the timing and magnitude of plant responses during the 13th year of warming. These included large warming‐induced biomass increases for individual plants, an 8.5‐day advancement in the growing season, and strong reductions in photosynthetic rates and population cover.
4.Importantly, we observed a lack of photosynthetic acclimation and, thus, a warming‐induced down regulation of photosynthetic rates. However, these physiological responses were concurrent with warmed‐plant increases in growing season length and investment in photosynthetic surfaces, demonstrating the species' ability to balance carbon fixation limitations with warming.
5.These results, which bring together ecophysiological, phenological, reproductive, and morphological assessments of plant responses to warming, suggest that the extent of change in A. hymenoides populations will be based upon numerous adaptive responses that vary in their direction and magnitude. Plant population responses to climatic warming remain poorly resolved, particularly for Earth's drylands, and our in situ experiment assessing multiple strategies offers a novel look into a warmer world.
","language":"English","publisher":"Wiley-Blackwell on behalf of the British Ecological Society (United Kingdom)","doi":"10.1111/1365-2435.13432","usgsCitation":"Winkler, D.E., Grossiord, C., Belnap, J., Howell, A.J., Ferrenberg, S., Smith, H.J., and Reed, S.C., 2019, Earlier plant growth helps compensate for reduced carbon fixation after 13 years of warming: Functional Ecology, v. 33, no. 11, p. 2071-2080, https://doi.org/10.1111/1365-2435.13432.","productDescription":"10 p.","startPage":"2071","endPage":"2080","ipdsId":"IP-105655","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467386,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.13432","text":"Publisher Index Page"},{"id":366445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.50210571289062,\n 38.63725461835644\n ],\n [\n -109.11346435546874,\n 38.63725461835644\n ],\n [\n -109.11346435546874,\n 38.81617117607388\n ],\n [\n -109.50210571289062,\n 38.81617117607388\n ],\n [\n -109.50210571289062,\n 38.63725461835644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grossiord, Charlotte","contributorId":207749,"corporation":false,"usgs":false,"family":"Grossiord","given":"Charlotte","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":768116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrenberg, Scott","contributorId":217143,"corporation":false,"usgs":false,"family":"Ferrenberg","given":"Scott","affiliations":[{"id":39569,"text":"Department of Biology, New Mexico State University, Las Cruces, NM 88001, USA","active":true,"usgs":false}],"preferred":false,"id":768119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Hilda J. 0000-0001-5775-1401 hsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-5775-1401","contributorId":4469,"corporation":false,"usgs":true,"family":"Smith","given":"Hilda","email":"hsmith@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":768121,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204693,"text":"70204693 - 2019 - Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models","interactions":[],"lastModifiedDate":"2019-08-09T12:01:26","indexId":"70204693","displayToPublicDate":"2019-08-07T11:53:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models","docAbstract":"Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.
","language":"English","publisher":"MDPI","doi":"10.3390/w11081629","usgsCitation":"Foks, S., Raffensperger, J.P., Penn, C.A., and Driscoll, J.M., 2019, Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models: Water, v. 11, no. 8, 1629, 25 p., https://doi.org/10.3390/w11081629.","productDescription":"1629, 25 p.","ipdsId":"IP-104087","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467387,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11081629","text":"Publisher Index Page"},{"id":437370,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XF3C11","text":"USGS data 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Center","active":true,"usgs":true}],"preferred":true,"id":768087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penn, Colin A. 0000-0002-5195-2744","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":203851,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling 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conditions is not well understood for marine predators, especially sea turtles. We tagged loggerhead turtles (Caretta caretta) with satellite-linked depth loggers in the Gulf of Mexico, where there is a minimal amount of dive data for this species. We tested for associations between four measurements of dive behavior (total daily dive frequency, frequency of dives to the bottom, frequency of long dives and time-at-depth) and both oceanographic conditions (sea surface temperature [SST], net primary productivity [NPP]) and behavioral mode (inter-nesting, migration, or foraging). From 2011–2013 we obtained 26 tracks from 25 adult female loggerheads tagged after nesting in the Gulf of Mexico. All turtles remained in the Gulf of Mexico and spent about 10% of their time at the surface (10% during inter-nesting, 14% during migration, 9% during foraging). Mean total dive frequency was 41.9 times per day. Most dives were ≤ 25 m and between 30–40 min. During inter-nesting and foraging, turtles dived to the bottom 95% of days. SST was an important explanatory variable for all dive patterns; higher SST was associated with more dives per day, more long dives and more dives to the seafloor. Increases in NPP were associated with more long dives and more dives to the bottom, while lower NPP resulted in an increased frequency of overall diving. Longer dives occurred more frequently during migration and a higher proportion of dives reached the seafloor during foraging when SST and NPP were higher. Our study stresses the importance of the interplay between SST and foraging resources for influencing dive behavior.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0220372","usgsCitation":"Iverson, A., Fujisaki, I., Lamont, M.M., and Hart, K., 2019, Loggerhead sea turtle (Caretta caretta) diving changes with productivity, behavioral mode, and sea surface temperature: PLoS ONE, v. 14, no. 8, e0220372, 19 p., https://doi.org/10.1371/journal.pone.0220372.","productDescription":"e0220372, 19 p.","ipdsId":"IP-101494","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467388,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0220372","text":"Publisher Index Page"},{"id":437371,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PY9YBZ","text":"USGS data release","linkHelpText":"Dive data for loggerhead sea turtles in the Gulf of Mexico, 2011-2013"},{"id":366856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cuba, Mexico, United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.001953125,\n 27.430289738862594\n ],\n [\n -82.99072265625,\n 29.592565403314087\n ],\n [\n -84.35302734375,\n 30.259067203213018\n ],\n [\n -85.23193359375,\n 30.031055426540206\n ],\n [\n -87.14355468749999,\n 30.694611546632277\n ],\n [\n -88.57177734375,\n 30.751277776257812\n ],\n [\n -90.263671875,\n 29.80251790576445\n ],\n [\n -91.34033203125,\n 29.57345707301757\n ],\n [\n -91.93359375,\n 29.973970240516614\n ],\n [\n -92.8125,\n 29.80251790576445\n ],\n [\n -94.28466796874999,\n 29.84064389983441\n ],\n [\n -97.36083984375,\n 28.14950321154457\n ],\n [\n -97.62451171875,\n 26.62781822639305\n ],\n [\n -97.40478515625,\n 25.720735134412106\n ],\n [\n -97.88818359375,\n 25.363882272740256\n ],\n [\n -98.0859375,\n 22.39071391683855\n ],\n [\n -96.328125,\n 18.8543103618898\n ],\n [\n -94.59228515625,\n 18.06231230454674\n ],\n [\n -92.17529296875,\n 18.47960905583197\n ],\n [\n -91.56005859375,\n 18.291949733550336\n ],\n [\n -91.01074218749999,\n 18.812717856407776\n ],\n [\n -90.3515625,\n 19.9526963975442\n ],\n [\n -90.19775390625,\n 20.96143961409684\n ],\n [\n -87.1875,\n 21.166483858206583\n ],\n [\n -87.69287109375,\n 19.828725387681168\n ],\n [\n -87.86865234374999,\n 19.539084135509334\n ],\n [\n -87.9345703125,\n 18.437924653474408\n ],\n [\n -78.5302734375,\n 22.28909641872304\n ],\n [\n -82.001953125,\n 27.430289738862594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Iverson, Autumn 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":218322,"corporation":false,"usgs":true,"family":"Iverson","given":"Autumn","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":769006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":769007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamont, Margaret M. 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":218323,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218324,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204767,"text":"70204767 - 2019 - Chemical and physical controls on mercury source signatures in stream fish from the northeastern United States","interactions":[],"lastModifiedDate":"2019-12-06T06:16:42","indexId":"70204767","displayToPublicDate":"2019-08-07T10:30:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Chemical and physical controls on mercury source signatures in stream fish from the northeastern United States","docAbstract":"Streams in the northeastern U.S. receive mercury (Hg) in varying proportions from atmospheric deposition and legacy point sources, making it difficult to attribute shifts in fish concentrations directly back to changes in Hg source management. Mercury stable isotope tracers were utilized to relate sources of Hg to co-located fish and bed sediments from 23 streams across a forested to urban-industrial land-use gradient within this region. Mass-dependent isotopes (δ202Hg) in prey and game fish at forested sites were depleted (medians -0.95 and -0.83 ‰, respectively) in comparison to fish from urban-industrial settings (medians -0.26 and -0.38 ‰, respectively); the forested site group also had higher prey fish Hg concentrations. The separation of Hg isotope signatures in fish was strongly related to in-stream and watershed land-use indicator variables. Fish isotopes were strongly correlated with bed sediment isotopes, but the comparison of isotopic composition between fish and sediment was variable due to differing ecosystem-specific drivers controlling the extent of MeHg formation. The multivariable approach of analyzing watershed characteristics and stream chemistry reveals that the Hg isotope composition in fish is linked to current and historic Hg sources in the northeastern U.S. and can be used to trace bioaccumulated Hg.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b03394","usgsCitation":"Janssen, S., Riva-Murray, K., DeWild, J.F., Ogorek, J.M., Tate, M., Van Metre, P.C., Krabbenhoft, D.P., and Coles, J.F., 2019, Chemical and physical controls on mercury source signatures in stream fish from the northeastern United States: Environmental Science & Technology, v. 53, no. 17, p. 10110-10119, https://doi.org/10.1021/acs.est.9b03394.","productDescription":"10 p.","startPage":"10110","endPage":"10119","ipdsId":"IP-108655","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":437372,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FHN3RK","text":"USGS data release","linkHelpText":"Chemical and Physical Controls on Mercury Source Signatures in Stream Fish from the Northeastern United States"},{"id":366566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.994140625,\n 47.635783590864854\n ],\n [\n -70.4443359375,\n 46.81509864599243\n ],\n [\n -71.630859375,\n 45.166547157856016\n ],\n [\n -75.498046875,\n 45.182036837015886\n ],\n [\n -77.10205078124999,\n 43.739352079154706\n ],\n [\n -79.40917968749999,\n 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jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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Division","active":true,"usgs":true}],"preferred":true,"id":768390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768391,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203068,"text":"ofr20191039 - 2019 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2017","interactions":[],"lastModifiedDate":"2019-08-07T10:23:41","indexId":"ofr20191039","displayToPublicDate":"2019-08-07T10:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1039","displayTitle":"Streamflow, Water Quality, and Constituent Loads and Yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2017","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, Water Year 2017","docAbstract":"As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with the Providence Water Supply Board, collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2017 (October 1, 2016, through September 30, 2017) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 36 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2017 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for water year 2017.
The Ponaganset River, which is the largest tributary to the reservoir and was monitored by the U.S. Geological Survey, contributed a mean streamflow of 29 cubic feet per second to the reservoir during water year 2017. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.44 to about 20 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,100 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir during water year 2017; chloride yields for the tributaries ranged from 16 to 140 metric tons per square mile, and sodium yields, from 10 to 80 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.3 milligrams per liter for chloride, 0.002 milligram per liter as nitrogen for nitrite, 0.10 milligram per liter as nitrogen for nitrate, 0.05 milligram per liter as phosphate for orthophosphate, 1,200 colony forming units per 100 milliliters for total coliform bacteria, and 14 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 230 kilograms per day, 17 grams per day, 860 grams per day, 690 grams per day, 84,000 million colony forming units per day, and 1,200 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were were 87 kilograms per day per square mile, 6.1 grams per day per square mile, 280 grams per day per square mile, 260 grams per day per square mile, 44,000 million colony forming units per day per square mile, and 655 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191039","collaboration":"Prepared in cooperation with the Providence Water Supply Board, Rhode Island","usgsCitation":"Smith, K.P., 2019, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2017: U.S. Geological Survey Open-File Report 2019–1039, 33 p., https://doi.org/10.3133/ofr20191039.","productDescription":"Report: v, 33 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102155","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":365646,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPAKP6","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2017"},{"id":365582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1039/coverthb.jpg"},{"id":365583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1039/ofr20191039.pdf","text":"Report","size":"1.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1039"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78878784179688,\n 41.72110557838152\n ],\n [\n -71.53610229492188,\n 41.72110557838152\n ],\n [\n -71.53610229492188,\n 41.97174336327968\n ],\n [\n -71.78878784179688,\n 41.97174336327968\n ],\n [\n -71.78878784179688,\n 41.72110557838152\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
The U.S. Geological Survey assessed the effective solubilities of organic analytes at the BKK Class Ⅰ Landfill site, West Covina, California, in cooperation with the California Department of Toxic Substances Control, using available data for liquid samples collected within (in-waste) and below (sub-waste) the landfill in 2014–16. The primary purpose of the effective solubility calculations was to determine the likely presence or absence of dense non-aqueous phase liquids (DNAPLs), which is important for understanding the sources, persistence, and movement of the leachate contaminants. Percent effective solubility (a measure of the degree of deviation of a measured liquid concentration of a compound from the aqueous effective solubility) greater than 1 percent is the threshold that commonly has been used to infer the presence of DNAPLs or mixed DNAPLs in aqueous monitoring results. In the present study, however, thresholds higher than 1 percent were used because of elevated temperatures and concentrations of cosolvents in the liquid samples—thresholds of 10 percent or 100 percent, respectively, were used for liquid and solid (at 25 degrees Celsius) organic compounds for potential non-aqueous phase liquid presence.
Overall, the effective solubility calculations indicate the likely presence of DNAPLs or mixed DNAPLs in some samples for a range of compounds, including tetrachloroethene, trichloroethene, 1,1-dichloroethene, vinyl chloride, 1,2,4-trichlorobenzene, 1,4-dichlorobenzene, 1,2-dichlorobenzene, naphthalene, toluene, ethylbenzene, and xylenes. Samples with the highest calculated percent effective solubilities for chlorinated ethenes, ethanes, and benzenes were from a location where liquid in the waste prism is known to be in contact with the groundwater beneath the landfill. Trends in the effective solubilities for the chlorinated ethenes and ethanes were generally consistent between the in-waste and sub-waste samples, supporting a similar source composition for these liquids. Percent effective solubilities were less than 10 for the chlorinated ethanes in all the in-waste and sub-waste samples, indicating that DNAPL of these compounds is not present. Percent effective solubilities of chlorinated benzenes, ethylbenzene, and xylenes exceeded the 10-percent effective solubility threshold in more of the sub-waste samples than the in-waste liquid samples. Volatilization also may influence the patterns in the calculated effective solubilities but were not included in this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191080","collaboration":"Prepared in cooperation with the California Department of Toxic Substances Control","usgsCitation":"Lorah, M.M., Majcher, E.H., and Morel, C.J., 2019, Effective solubility assessment for organic analytes in liquid samples, BKK Class Ⅰ Landfill, West Covina, California, 2014–16: U.S. Geological Survey Open-File Report 2019–1080, 18 p., https://doi.org/10.3133/ofr20191080.","productDescription":"Report: v, 18p.; Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105175","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":366110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1080/ofr20191080.pdf","text":"Report","size":"8.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1080"},{"id":366109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1080/coverthb.jpg"},{"id":366188,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1080/ofr20191080_table1.xlsx","text":"Tables SI-1 through SI-11","size":"1.25 MB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Supplemental Information Worksheet - Mole Fraction and Effective Solubility Calculations"}],"country":"United States","state":"California","city":"West Covinia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.99917221069335,\n 34.064463311552615\n ],\n [\n -118.01462173461914,\n 34.04000041165585\n ],\n [\n -117.95145034790039,\n 34.03729768165777\n ],\n [\n -117.91471481323242,\n 34.03800893474363\n ],\n [\n -117.90956497192383,\n 34.04782361826847\n ],\n [\n -117.90939331054688,\n 34.0715732952909\n ],\n [\n -117.94235229492188,\n 34.07143110146331\n ],\n [\n -117.99917221069335,\n 34.064463311552615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration.
The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195044","collaboration":"Prepared in cooperation with the U.S. Bureau of Reclamation","usgsCitation":"Risley, J.C., 2019, Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2019–5044, 37 p., https://doi.org/10.3133/sir20195044.","productDescription":"vi, 37 p.","onlineOnly":"Y","ipdsId":"IP-098864","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":366315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5044/coverthb.jpg"},{"id":366316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5044/sir20195044.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5044"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.42041015624999,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 40.76806170936614\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Observations of seismic anisotropy can provide direct constraints on the character of mantle flow in subduction zones, critical for our broader understanding of subduction dynamics. Here we present over 750 new SKS splitting measurements in the vicinity of Mount St. Helens in the Cascadia subduction zone using a combination of stations from the iMUSH broadband array and Cascades Volcano Observatory network. This provides the highest density of splitting measurements yet available in Cascadia, acting as a focused “telescope” for seismic anisotropy in the subduction zone. We retrieve spatially consistent splitting parameters (mean fast direction Φ: 74°, mean delay time ∂t: 1.0 s) with the azimuthal occurrence of nulls in agreement with the fast direction of splitting. When averaged across the array, a 90° periodicity in splitting parameters as a function of back azimuth is revealed, which has not been recovered previously with single‐station observations. The periodicity is characterized by a sawtooth pattern in Φ with a clearly defined 45° trend. We present new equations that reproduce this behavior based upon known systematic errors when calculating shear wave splitting from data with realistic seismic noise. The corrected results suggest a single layer of anisotropy with an ENE‐WSW fast axis parallel to the motion of the subducting Juan de Fuca plate; in agreement with predictions for entrained subslab mantle flow. The splitting pattern is consistent with that seen throughout Cascadia, suggesting that entrainment of the underlying asthenosphere with the subducting slab is coherent and widespread.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GC008433","usgsCitation":"Eakin, C.M., Wirth, E.A., Wallace, A., Ulberg, C.W., Creager, K.C., and Abers, G.A., 2019, SKS splitting beneath Mount St. Helens: Constraints on subslab mantle entrainment: Geochemistry, Geophysics, Geosystems, v. 20, no. 8, p. 4202-4217, https://doi.org/10.1029/2019GC008433.","productDescription":"16 p.","startPage":"4202","endPage":"4217","ipdsId":"IP-106294","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":467394,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gc008433","text":"Publisher Index Page"},{"id":371738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.06335449218749,\n 45.916765867649005\n ],\n [\n -121.05285644531249,\n 45.916765867649005\n ],\n [\n -121.05285644531249,\n 47.28295557691231\n ],\n [\n -123.06335449218749,\n 47.28295557691231\n ],\n [\n -123.06335449218749,\n 45.916765867649005\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Eakin, Caroline M","contributorId":221907,"corporation":false,"usgs":false,"family":"Eakin","given":"Caroline","email":"","middleInitial":"M","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":780685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":197865,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","email":"","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":780684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Abraham","contributorId":221908,"corporation":false,"usgs":false,"family":"Wallace","given":"Abraham","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":780686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulberg, Carl W 0000-0001-6198-809X","orcid":"https://orcid.org/0000-0001-6198-809X","contributorId":221909,"corporation":false,"usgs":false,"family":"Ulberg","given":"Carl","email":"","middleInitial":"W","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":780687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Creager, Kenneth C 0000-0003-4501-7415","orcid":"https://orcid.org/0000-0003-4501-7415","contributorId":221910,"corporation":false,"usgs":false,"family":"Creager","given":"Kenneth","email":"","middleInitial":"C","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":780688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abers, Geoffrey A","contributorId":221911,"corporation":false,"usgs":false,"family":"Abers","given":"Geoffrey","email":"","middleInitial":"A","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":780689,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203669,"text":"sir20195051 - 2019 - Benthos and plankton of western Lake Michigan Areas of Concern in comparison to non-Areas of Concern for selected rivers and harbors, 2012 and 2014","interactions":[],"lastModifiedDate":"2019-08-06T09:22:47","indexId":"sir20195051","displayToPublicDate":"2019-08-05T12:49:57","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":"2019-5051","displayTitle":"Benthos and Plankton of Western Lake Michigan Areas of Concern in Comparison to Non-Areas of Concern for Selected Rivers and Harbors, 2012 and 2014","title":"Benthos and plankton of western Lake Michigan Areas of Concern in comparison to non-Areas of Concern for selected rivers and harbors, 2012 and 2014","docAbstract":"Since their designation in the 1980s, Areas of Concern (AOCs) around the Great Lakes have been the focus of multi-State and international cleanup efforts that were needed after decades of human activity resulted in severely contaminated sediment, water-quality degradation, loss of habitat for aquatic organisms, and impaired public use. Although individual Great Lake States had been working to cleanup and mitigate environmental concerns, there was insufficient funding and little coordination between Federal and State efforts to address the large and complex set of problems. The Great Lakes Ecosystem Protection Act was passed in 2010, providing for comprehensive multi-State planning and dedicating Federal funds to accelerate cleanup and improve conditions at the AOCs with a particular focus on 14 beneficial use impairments, such as degradation of benthos and degradation of phytoplankton and zooplankton populations. Of Wisconsin’s five AOCs, four lie adjacent to Lake Michigan: Lower Menominee River, Lower Green Bay and Fox River, Sheboygan River, and Milwaukee Estuary (which includes the Milwaukee River, Menomonee River, Kinnickinnic River, and Milwaukee Harbor). The Wisconsin Department of Natural Resources has focused much of the cleanup on removal of contaminated sediment from these AOCs because many beneficial use impairments were a result of contaminated sediment. However, recent and quantitative assessments of the status of benthos and plankton at the AOCs were lacking. Therefore, to inform management decisions regarding the status of benthos and plankton at AOCs, the U.S. Geological Survey, in cooperation with the Wisconsin Department of Natural Resources (WDNR) and the U.S. Environmental Protection Agency, Great Lakes National Program Office, assessed the condition of benthos (benthic invertebrates) and plankton (zooplankton and phytoplankton) at sites in the 4 AOCs and at 6 less-degraded comparison sites (hereafter referred to as “non-AOCs”).
The U.S. Geological Survey collected benthos, plankton, sediment, and water three times per year in 2012 and 2014 between May and August at the AOC and non-AOC comparison sites. Except for Lower Green Bay and Milwaukee Harbor, each AOC site or subsite was paired with sites in two non-AOCs with similar environmental conditions. Community-based metrics were compared using univariate and multivariate statistics between each AOC and the mean of all non-AOCs and between each AOC and the mean of two non-AOC comparison sites. Although it was assumed that, because of their designation as AOCs, the relationships would indicate degraded conditions compared to the non-AOC sites, several metrics for the AOCs did not significantly differ between the AOCs and non-AOCs in 2014. Of all four AOCs examined for benthos, only the Lower Menominee River AOC differed from its two non-AOC comparison sites; the density and richness of taxa in insect orders Ephemeroptera-Plecoptera-Trichoptera (mayflies, stoneflies, and caddisflies) in combined benthos (dredge and artificial substrate samples) were lower at the AOC. For plankton, the assemblages for zooplankton at the Fox River near Allouez (a subsite in the Lower Green Bay AOC) and the Milwaukee River differed from their two non-AOC comparison sites; density of zooplankton was lower at both AOCs. Metrics for combined benthos and combined phytoplankton (soft algae and diatoms) at the Sheboygan River AOC did not differ from the two non-AOC comparison sites; however, the diversity of zooplankton in 2014 was lower at the Sheboygan River AOC than at the two non-AOC comparison sites. The combination of univariate and multivariate statistics provided a way to evaluate the status of the aquatic assemblage at each AOC and whether or not the assemblage differed from less-degraded non-AOC comparison sites. Results for this study provide multiple lines of evidence for evaluating the status of aquatic communities at AOC sites in Wisconsin along the western Lake Michigan shoreline in 2012 and 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195051","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency, Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Olds, H.T., Burns, D.J., Bell, A.H., and Carter, J.L., 2019, Benthos and plankton of western Lake Michigan Areas of Concern in comparison non-Areas of Concern for to selected rivers and harbors, 2012 and 2014: U.S. Geological Survey Scientific Investigations Report 2019–5051, 50 p., https://doi.org/10.3133/sir20195051.","productDescription":"Report: viii, 50 p.; Companion Reports: 2","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081397","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366200,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/ds1000","text":"Data Series 1000","size":"31.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1000","linkHelpText":"– Benthos and Plankton Community Data for Selected Rivers and Harbors along the Western Lake Michigan Shoreline, 2014"},{"id":366183,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5051/coverthb.jpg"},{"id":366184,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5051/sir20195051.pdf","text":"Report","size":"2.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5051"},{"id":366199,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0824/","text":"Data Series 824","size":"4.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 824","linkHelpText":"– Benthos and Plankton Community Data for Selected Rivers and Harbors along Wisconsin’s Lake Michigan Shoreline, 2012"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Western Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.43994140625,\n 42.49640294093705\n ],\n [\n -86.60522460937499,\n 42.49640294093705\n ],\n [\n -86.60522460937499,\n 46.05036097561633\n ],\n [\n -88.43994140625,\n 46.05036097561633\n ],\n [\n -88.43994140625,\n 42.49640294093705\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
American woodcock (Scolopax minor; woodcock) migratory connectivity (i.e., association between breeding and wintering areas) is largely unknown, even though current woodcock management is predicated on such associations. Woodcock are currently managed in the Eastern and Central management regions in the United States with the boundary between management regions analogous to the boundary between the Atlantic and Mississippi flyways, based largely on analysis of band returns from hunters. Factors during migration influence survival and fitness, and existing data derived from banding and very high frequency telemetry provide only coarse-scale information to assess factors influencing woodcock migratory movement patterns and behavior. To assess whether current management-region boundaries correspond with woodcock migratory connectivity in the Central Management Region and to describe migration patterns with higher resolution than has been previously possible, we deployed satellite transmitters on 73 woodcock (25 adult and 28 juvenile females, and 8 adult and 12 juvenile males) and recorded 87 autumn or spring migration paths from 2014 to 2016. Marked woodcock used 2 primary migrations routes: a Western Route and a Central Route. The Western Route ran north-south, connecting the breeding and wintering grounds within the Central Management Region. The hourglass-shaped Central Route connected an area on the wintering grounds reaching from Texas to Florida, to sites throughout northeastern North America in both the Eastern Management Region and Central Management Region and woodcock following this route migrated through the area between the Appalachian Mountains and the Mississippi Alluvial Valley in western Tennessee during autumn and spring. Two of 17 woodcock captured associated with breeding areas in Michigan, Wisconsin, or Minnesota migrated to wintering sites in the Eastern Management Region and 12 marked woodcock captured on wintering areas in Texas and Louisiana migrated to breeding sites in the Eastern Management Region. Woodcock that used the Western Route exhibited high concentrations of stopovers during spring in the Arkansas Ozark Mountains and northern Missouri, and along the Mississippi River on the border between Wisconsin and Minnesota, and autumn concentrations of stopovers in southwestern Iowa, central Missouri, the Arkansas portion of the Ozark Mountains, and around the junction of Texas, Louisiana, Oklahoma, and Arkansas. Woodcock that used the Central Route exhibited high concentrations of stopovers during spring in northern Mississippi through western Tennessee, western Kentucky, and the Missouri Bootheel, and autumn concentrations of stopovers in northern Illinois, southwestern Ohio, and the portions of Kentucky and Tennessee west of the Appalachian Mountains. We suggest that current management of woodcock based on 2 management regions may not be consistent with the apparent lack of strong migratory connectivity we observed. Our results also suggest where management of migration habitat might be most beneficial to woodcock.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21741","usgsCitation":"Moore, J.D., Andersen, D.E., Cooper, T.R., Duguay, J.P., Oldenburger, S., Stewart, C.A., and Krementz, D.G., 2019, Migratory connectivity of American woodcock derived using satellite telemetry: Journal of Wildlife Management, v. 83, no. 7, p. 1617-1627, https://doi.org/10.1002/jwmg.21741.","productDescription":"11 p.","startPage":"1617","endPage":"1627","ipdsId":"IP-098884","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.85546875,\n 25.958044673317843\n ],\n [\n -94.74609375,\n 29.075375179558346\n ],\n [\n -90.17578124999999,\n 28.998531814051795\n ],\n [\n -84.638671875,\n 30.44867367928756\n ],\n [\n -85.69335937499999,\n 35.24561909420681\n ],\n [\n -83.75976562499999,\n 34.95799531086792\n ],\n [\n -81.474609375,\n 37.020098201368114\n ],\n [\n -83.3203125,\n 36.80928470205937\n ],\n [\n -79.62890625,\n 37.78808138412046\n ],\n [\n -74.1796875,\n 40.713955826286046\n ],\n [\n -69.08203125,\n 40.84706035607122\n ],\n [\n -63.6328125,\n 46.800059446787316\n ],\n [\n -63.6328125,\n 49.03786794532644\n ],\n [\n -68.64257812499999,\n 49.781264058178344\n ],\n [\n -83.232421875,\n 50.45750402042058\n ],\n [\n -99.49218749999999,\n 52.53627304145948\n ],\n [\n -97.55859375,\n 44.02442151965934\n ],\n [\n -98.0859375,\n 36.73888412439431\n ],\n [\n -98.701171875,\n 30.751277776257812\n ],\n [\n -97.998046875,\n 26.27371402440643\n ],\n [\n -96.85546875,\n 25.958044673317843\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"7","noUsgsAuthors":false,"publicationDate":"2019-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, J. D.","contributorId":275291,"corporation":false,"usgs":false,"family":"Moore","given":"J.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":833938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Thomas R.","contributorId":191468,"corporation":false,"usgs":false,"family":"Cooper","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":834075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duguay, J. P.","contributorId":275292,"corporation":false,"usgs":false,"family":"Duguay","given":"J.","email":"","middleInitial":"P.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":833940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oldenburger, Shaun L.","contributorId":275294,"corporation":false,"usgs":false,"family":"Oldenburger","given":"Shaun L.","affiliations":[{"id":56759,"text":"Texas Parks & Wildlife","active":true,"usgs":false}],"preferred":false,"id":833942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, C. A.","contributorId":275295,"corporation":false,"usgs":false,"family":"Stewart","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833943,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833944,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204599,"text":"70204599 - 2019 - Paleoenvironmental, epigraphic, and archaeological evidence of total warfare among the Classic Maya","interactions":[],"lastModifiedDate":"2020-08-25T13:19:11.001511","indexId":"70204599","displayToPublicDate":"2019-08-05T11:28:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Paleoenvironmental, epigraphic, and archaeological evidence of total warfare among the Classic Maya","docAbstract":"Despite over a century of archaeological research, the nature and broader consequences of Classic Maya warfare remain poorly understood. Based on frequent epigraphic references and iconographic themes, Classic period (250-950 CE) Maya warfare has largely been viewed as ritualized and limited in scope. Evidence of warfare in the Terminal Classic period (TCP, 800-950 CE) is interpreted as an escalation of military tactics that played a role in the socio-economic collapse of the Classic Maya civilization. Implications of specific textual references to war events remain unknown, however, and the paucity of field data precludes our ability to test collapse theories tied to warfare. Here we present geoarchaeological evidence of a large fire event and connect it to a battle described with a Classic period war statement (puluuy), clarifying its meaning and providing insight into the strategies and impacts of Maya warfare. Multiple lines of evidence show that a massive fire occurred across the ancient city of Witzna during the last decade of the 7th century CE, coincident with a written account of Witzna’s burning by the kingdom of Naranjo in 697 CE. Following this event human activity at Witzna declined dramatically, indicating the battle had broad societal impacts. Puluuy is a commonly occurring war statement, and these findings show that the Maya engaged in tactics akin to total warfare earlier and more frequently than previously thought. This research provides insights into the broad societal impacts of Classic period warfare and necessitates a reevaluation of the role of warfare in the Maya collapse.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41562-019-0671-x","usgsCitation":"Wahl, D., Anderson, L., Estrada-Belli, F., and Tokovinine, A., 2019, Paleoenvironmental, epigraphic, and archaeological evidence of total warfare among the Classic Maya: Nature, v. 3, p. 1049-1054, https://doi.org/10.1038/s41562-019-0671-x.","productDescription":"6 p.","startPage":"1049","endPage":"1054","ipdsId":"IP-095862","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":366296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":767730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":797260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estrada-Belli, Francisco","contributorId":149456,"corporation":false,"usgs":false,"family":"Estrada-Belli","given":"Francisco","email":"","affiliations":[{"id":13500,"text":"Tulane University","active":true,"usgs":false}],"preferred":false,"id":767732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tokovinine, Alexandre","contributorId":217879,"corporation":false,"usgs":false,"family":"Tokovinine","given":"Alexandre","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":767733,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}