We provide an overview of a 2019 workshop on the use of fragile geologic features (FGFs) to evaluate seismic hazard models. FGFs have been scarcely utilized in the evaluation of seismic hazard models, despite nearly 30 yr having passed since the first recognition of their potential value. Recently, several studies have begun to focus on the implementation of FGFs in seismic hazard modeling. The workshop was held to capture a “snapshot” of the state‐of‐the‐art in FGF work and to define key research areas that would increase confidence in FGF‐based evaluation of seismic hazard models. It was held at the annual meeting of the Southern California Earthquake Center on 8 September 2019, and the conveners were Mark Stirling (University of Otago, New Zealand) and Michael Oskin (University of California, Davis). The workshop attracted 44 participants from a wide range of disciplines. The main topics of discussion were FGF fragility age estimation (age at which an FGF achieved its current fragile geometry), fragility estimation, FGF‐based evaluation of seismic hazard models, and ethical considerations relating to documentation and preservation of FGFs. There are now many scientists working on, or motivated to work on, FGFs, and more types of FGFs are being worked on than just the precariously balanced rock (PBR) variety. One of the ideas presented at the workshop is that fragility ages for FGFs should be treated stochastically rather than assuming that all share a common age. In a similar vein, new studies propose more comprehensive methods of fragility assessment beyond peak ground acceleration and peak ground velocity‐based approaches. Two recent studies that apply PBRs to evaluate probabilistic seismic hazard models use significantly different methods of evaluation. Key research needs identified from the workshop will guide future, focused efforts that will ultimately facilitate the uptake of FGFs in seismic hazard analysis.
The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated ‘One Health’ observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/jme/tjaa220","usgsCitation":"Ogden, N.H., Beard, C.B., Ginsberg, H., and Tsao, J.I., 2021, Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations: Journal of Medical Entomology, v. 58, no. 4, p. 1536-1545, https://doi.org/10.1093/jme/tjaa220.","productDescription":"10 p.","startPage":"1536","endPage":"1545","ipdsId":"IP-121581","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjaa220","text":"Publisher Index Page"},{"id":379905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":803337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beard, Charles B.","contributorId":148018,"corporation":false,"usgs":false,"family":"Beard","given":"Charles","email":"","middleInitial":"B.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":803338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":803340,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219547,"text":"70219547 - 2021 - Relative abundance of coyotes (Canis latrans) influences gray fox (Urocyon cinereoargenteus) occupancy across the eastern United States","interactions":[],"lastModifiedDate":"2021-04-13T12:57:42.705789","indexId":"70219547","displayToPublicDate":"2020-10-22T07:56:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Relative abundance of coyotes (Canis latrans) influences gray fox (Urocyon cinereoargenteus) occupancy across the eastern United States","docAbstract":"Climatic shifts, disturbances, and land-use change can alter hydrologic flowpaths, water quality, and water supply to downstream communities. Prior research investigating streamflow generation processes in mountainous areas has largely focused on high-elevation alpine and subalpine catchments; less is known about these processes in lower-elevation foothills and montane catchments. In these lower-elevation ecoregions, precipitation shifts seasonally from snow to rain, which can result in differing seasonal flowpaths. We analyzed stream water for electrical conductivity, SiO2, Ca, Mg, Na, Cl, SO4, K, and dissolved organic carbon on both a weekly and storm event basis from April to August 2018 in three small (<10 km2) foothill catchments, and one larger (63.2 km2) catchment extending from the foothills to the subalpine ecoregions, in the Colorado Front Range. Using two end-member hydrograph separations and concentration-runoff relationships, we inferred the dominant catchment-scale flowpaths of precipitation to the streams. We selected catchments with varying land use to investigate the relationship between these characteristics and hydrologic flowpaths. We observed that concentrations of lithogenic constituents generally increased and dissolved organic carbon decreased as seasonal runoff decreased in the three foothill catchments, reflecting a transition from shallow subsurface flowpaths to deeper subsurface flowpaths. Elevated SO4 and Cl concentrations during low-flow periods in two of our catchments suggest that historical or current anthropogenic activities, such as mining, application of road salt, and/or near-stream septic systems, affect local stream and groundwater chemistry. In a foothill catchment with anthropogenic and geologic impervious surfaces, streamflow during storm responses was sourced from faster, surficial flowpaths compared to a less disturbed neighboring catchment, highlighting the influence of anthropogenic land-use on runoff generation. This study provides insight into the fundamental hydrology of foothill catchments and how they may function in the future with human development, precipitation shifts and disturbances.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125672","usgsCitation":"Bukoski, I.S., Murphy, S.F., Birch, A.L., and Barnard, H.R., 2021, Summer runoff generation in foothill catchments of the Colorado Front Range: Journal of Hydrology, v. 595, 125672, 13 p., https://doi.org/10.1016/j.jhydrol.2020.125672.","productDescription":"125672, 13 p.","ipdsId":"IP-117845","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454362,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.125672","text":"Publisher Index Page"},{"id":385217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.083984375,\n 39.757879992021756\n ],\n [\n -104.765625,\n 39.757879992021756\n ],\n [\n -104.765625,\n 40.212440718286466\n ],\n [\n -106.083984375,\n 40.212440718286466\n ],\n [\n -106.083984375,\n 39.757879992021756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"595","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bukoski, Isaac S.","contributorId":257521,"corporation":false,"usgs":false,"family":"Bukoski","given":"Isaac","email":"","middleInitial":"S.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":814487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":814488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birch, Andrew L.","contributorId":257522,"corporation":false,"usgs":false,"family":"Birch","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":814489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Holly R.","contributorId":257523,"corporation":false,"usgs":false,"family":"Barnard","given":"Holly","email":"","middleInitial":"R.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":814490,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254939,"text":"70254939 - 2021 - Hierarchical computing for hierarchical models in ecology","interactions":[],"lastModifiedDate":"2024-06-12T00:14:56.560958","indexId":"70254939","displayToPublicDate":"2020-10-17T19:13:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Hierarchical computing for hierarchical models in ecology","docAbstract":"Transport of nutrients to lakes can occur via surface-water inflow, atmospheric deposition, groundwater (GW) inflow and benthic processes. Identifying and quantifying within-lake nutrient sources and recycling processes is challenging. Prior studies in hypereutrophic Upper Klamath Lake, Oregon, USA, indicated that ~60% of the early summer phosphorus (P) load to the lake was internal and hypothesized to be lakebed sediment release. Dynamic nutrient transport processes were examined to better characterize the nutrient sources. One-dimensional heat transport models calibrated to observed lakebed temperatures and a cross-sectional GW flow model provided estimates of GW-inflow rates that were greatest in spring and decreased through summer. One-dimensional solute transport models calibrated to observed lakebed pore-water dissolved silica (Si) and dissolved phosphate-phosphorus (DP) concentrations indicated that nutrients were transported from the lakebed by advection, diffusion, and enhanced mixing by benthic organisms and waves, and that DP removal occurred near the lakebed interface. Estimated water, Si, DP and total-phosphorus (TP) budgets indicated that GW contributed 21% of lake water inflow and at least 26, 20 and 16% of total Si, DP and TP inflow, respectively, when conservatively assuming background GW nutrient concentrations. However, lakebed GW (LGW) is enriched in nutrients during flow through lakebed sediment and the estimated GW contribution increased to 29 (33), 49 (67) and 43% (61%) of total Si, DP and TP inflow, respectively, if 20% (50%) of GW inflow to the lake was assumed to have LGW concentrations. Net nutrient inflow to the lake was greatest in spring and coincident with the annual diatom bloom. Inflowing dissolved nutrients appear to be assimilated by diatoms during the spring and become available for the summer Aphanizomenon flos-aquae bloom when the diatoms senesce. Thus, nutrient-enriched GW inflow and nutrient recycling by successive algal blooms must be considered when evaluating internal nutrient loading to lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.142768","usgsCitation":"Essaid, H.I., Kuwabara, J.S., Corson-Dosch, N., Carter, J.L., and Topping, B.R., 2021, Evaluating the dynamics of groundwater, lakebed transport, nutrient inflow and algal blooms in Upper Klamath Lake, Oregon, USA: Science of the Total Environment, v. 765, 142768, 16 p., https://doi.org/10.1016/j.scitotenv.2020.142768.","productDescription":"142768, 16 p.","ipdsId":"IP-115458","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436656,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98C5H5N","text":"USGS data release","linkHelpText":"MODFLOW, MT3D-USGS and VS2DH simulations used to estimate groundwater and nutrient inflow to Upper Klamath Lake, Oregon"},{"id":383225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10273742675781,\n 42.21987327563142\n ],\n [\n -121.79374694824219,\n 42.21987327563142\n ],\n [\n -121.79374694824219,\n 42.6026307853624\n ],\n [\n -122.10273742675781,\n 42.6026307853624\n ],\n [\n -122.10273742675781,\n 42.21987327563142\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"765","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":810173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corson-Dosch, Nicholas 0000-0002-6776-6241","orcid":"https://orcid.org/0000-0002-6776-6241","contributorId":202630,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Nicholas","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, James L. 0000-0002-0104-9776","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":215951,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810176,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228609,"text":"70228609 - 2021 - Impacts of small dams on stream temperature","interactions":[],"lastModifiedDate":"2022-02-14T17:19:08.866549","indexId":"70228609","displayToPublicDate":"2020-09-16T11:14:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of small dams on stream temperature","docAbstract":"Small, surface-release dams are ubiquitous features of the landscape that typically slow water flow and decrease canopy cover through impounded reaches, potentially increasing stream temperatures. However, reported effects of small dams on water temperature are variable, likely due to differences in landscape and dam characteristics. To quantify the range of thermal effects of small dams, we deployed continuous temperature loggers for one to four years at 30 dam sites across a range of environmental settings throughout Massachusetts (USA). Most dams (67%) warmed downstream waters, with August mean temperatures 0.20–5.25 °C higher than upstream. Downstream temperatures cooled with increased distance from the dam at 68% of sites, such that the warmest temperatures were observed closest to the dam. Where there was both a significant downstream warming effect and cooling pattern (seven sites), elevated temperatures persisted for an average of 1.31 km downstream of the dam. Dams with impoundments that caused the greatest relative widening of the stream channel and those on coldwater streams had the most warming, while streams with short dams in forested watersheds cooled most quickly downstream of the dam. Flow had a homogenizing effect on water temperatures at over half of the sites, whereby summer thermal impacts were more pronounced (e.g., more warming, faster cooling rates) under periods of lower flows. Downstream warming may reduce habitat for coldwater fishes and invertebrates, particularly where dams shift coldwater/coolwater habitat to warmwater. These results suggest that dam removal may mitigate elevated stream temperatures and increase ecosystem resilience in the face of a changing climate via restoration of critical coldwater habitats.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2020.106878","usgsCitation":"Zaidel, P.A., Roy, A.H., Houle, K.M., Lambert, B., Letcher, B., Nislow, K., and Smith, C., 2021, Impacts of small dams on stream temperature: Ecological Indicators, v. 120, 106878, 13 p., https://doi.org/10.1016/j.ecolind.2020.106878.","productDescription":"106878, 13 p.","ipdsId":"IP-117686","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454440,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2020.106878","text":"Publisher Index Page"},{"id":395896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Center","active":true,"usgs":true}],"preferred":true,"id":834786,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nislow, Keith H.","contributorId":276357,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":834787,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Christopher","contributorId":276358,"corporation":false,"usgs":false,"family":"Smith","given":"Christopher","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":834788,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230605,"text":"70230605 - 2021 - Detecting population declines via monitoring the effective number of breeders (Nb)","interactions":[],"lastModifiedDate":"2022-04-19T15:03:35.91164","indexId":"70230605","displayToPublicDate":"2020-09-02T10:00:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Detecting population declines via monitoring the effective number of breeders (Nb)","title":"Detecting population declines via monitoring the effective number of breeders (Nb)","docAbstract":"Estimating the effective population size and effective number of breeders per year (Nb) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of Nb in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. Nb estimates were biased by ~5%–10% when using SNPs or microsatellites in species ranging from fishes to mosquitoes, frogs, and seaweed. The bias (high or low) was similar for different life history types within a species suggesting that life history variation in populations will not influence Nb estimation. Precision was higher for 100 SNPs (H ≈ 0.30) than for 15 microsatellites (H ≈ 0.70). Confidence intervals (CIs) were occasionally too narrow, and biased high when Nb was small (Nb < 50); however, the magnitude of bias would unlikely influence management decisions. The CIs (from LDNe) were sufficiently narrow to achieve high statistical power (≥0.80) to reject the null hypothesis that Nb = 50 when the true Nb = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject Nb = 500 when the true Nb = 400 and when sampling 200 individuals and 5,000 loci. Finally, we present a linear regression method that provides high power to detect a decline in Nb when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate Nb for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in Nb and population declines.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.13251","usgsCitation":"Luikart, G., Antao, T., Hand, B., Muhlfeld, C.C., Boyer, M.C., Corsart, T., Trethewey, B., Al-Chokhachy, R.K., and Waples, R.S., 2021, Detecting population declines via monitoring the effective number of breeders (Nb): Molecular Ecology Resources, v. 21, no. 2, p. 379-393, https://doi.org/10.1111/1755-0998.13251.","productDescription":"15 p.","startPage":"379","endPage":"393","ipdsId":"IP-099662","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454456,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1755-0998.13251","text":"External Repository"},{"id":399088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":840880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antao, Tiago","contributorId":290364,"corporation":false,"usgs":false,"family":"Antao","given":"Tiago","email":"","affiliations":[{"id":62410,"text":"The Welcome Trust Centre for Human Genetics","active":true,"usgs":false}],"preferred":false,"id":840881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hand, Brian K.","contributorId":139248,"corporation":false,"usgs":false,"family":"Hand","given":"Brian K.","affiliations":[{"id":12707,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":840882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":290365,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":840883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Matthew C.","contributorId":48468,"corporation":false,"usgs":false,"family":"Boyer","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":840884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsart, Ted","contributorId":290366,"corporation":false,"usgs":false,"family":"Corsart","given":"Ted","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":840885,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trethewey, Brian","contributorId":290367,"corporation":false,"usgs":false,"family":"Trethewey","given":"Brian","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":840886,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":840887,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Waples, Robin S.","contributorId":126721,"corporation":false,"usgs":false,"family":"Waples","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":840888,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70212609,"text":"70212609 - 2021 - Status of the major aquaculture carps of China in the Laurentian Great Lakes Basin","interactions":[],"lastModifiedDate":"2021-10-29T13:13:24.00058","indexId":"70212609","displayToPublicDate":"2020-08-20T08:51:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Status of the major aquaculture carps of China in the Laurentian Great Lakes Basin","docAbstract":"There is concern of economic and environmental damage occuring if any of the four major aquacultured carp species of China, black carp Mylopharyngodon piceus, bighead carp Hypophthalmichthys nobilis, silver carp H. molitrix, or grass carp Ctenopharyngodon idella, were to establish in the Laurentian Great Lakes. All four are reproducing in the Mississippi River Basin. We review the status of these fishes in relation to the Great Lakes and their proximity to pathways into the Great Lakes, based on captures and collections of eggs and larvae. No black carp have been captured in the Great Lakes Basin. One silver carp and one bighead carp were captured within the Chicago Area Waterway System, on the Great Lakes side of electric barriers designed to keep carp from entering the Great Lakes from the greater Mississippi River Basin. Three bighead carp were captured in Lake Erie, none later than the year 2000. By December 2019, at least 650 grass carps had been captured in the Great Lakes Basin, most in western Lake Erie, but none in Lake Superior. Grass carp reproduction has been documented in the Sandusky and Maumee rivers in Ohio, tributaries of Lake Erie. We also discuss environmental DNA (eDNA) results as an early detection and monitoring tool for bighead and silver carps. Detection of eDNA does not necessarily indicate presence of live fish, but bigheaded carp eDNA has been detected on the Great Lakes side of the barriers and in a small proportion of samples from the western basin of Lake Erie.
Abandoned tropical pastures offer opportunities for passive and active restoration of native forest communities. Tree architecture of remnant canopy trees may be one important factor that can facilitate native plant recruitment in abandoned pastures but has largely been overlooked. Here, we evaluated patterns of native woody plant recruitment under remnant trees in abandoned pastures on Hawai’i Island and how these might be related to both tree architectural features and landscape variables. We measured native woody stems (excluding sprouts of the tree itself) in a 5 m radius around the base of each tree and modeled total basal area of native stems as a function of tree architectural characteristics. Recruitment was positively correlated with tree height as well as horizontal woody area below 1 m (tree structure that occurred below 1 m and was < 45° angle from the ground) around the base of trees. Tall trees likely attract more avian seed dispersers due to their higher visibility on the landscape and increased crown volume. Horizontal woody area likely provides establishment microsites that are above the pasture grass layer, similar to how dead or decaying logs act as nurse substrates. Unlike previous studies, we found little evidence that landscape variables such as distance to the intact forest or nearest canopy neighbor influenced understory recruitment. Tree architectural characteristics can be important predictors of native plant recruitment in abandoned tropical pastures and should be considered in addition to local and landscape-level variables.
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\"}}]}","volume":"222","noUsgsAuthors":false,"publicationDate":"2020-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rehm, Evan M","contributorId":216487,"corporation":false,"usgs":false,"family":"Rehm","given":"Evan","email":"","middleInitial":"M","affiliations":[{"id":39457,"text":"University of California at Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":818707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":818708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Marley Puanani","contributorId":260775,"corporation":false,"usgs":false,"family":"Smith","given":"Marley","email":"","middleInitial":"Puanani","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":818709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"D’Antonio, Carla M.","contributorId":140014,"corporation":false,"usgs":false,"family":"D’Antonio","given":"Carla","email":"","middleInitial":"M.","affiliations":[{"id":13358,"text":"Environmental Studies, University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":818710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70213293,"text":"70213293 - 2021 - Mortality predispositions of conifers across western USA","interactions":[],"lastModifiedDate":"2020-12-29T21:33:00.393927","indexId":"70213293","displayToPublicDate":"2020-08-09T12:07:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Mortality predispositions of conifers across western USA","docAbstract":"Widespread invasion by non-native, submerged aquatic vegetation (SAV) may modify the sediment budget of an estuary, reducing the availability of inorganic sediment required by marshes to maintain their position in the tidal frame. The instantaneous trapping rate of suspended sediment in SAV patches in an estuary has not previously been quantified via field observations. In this study, flows of water and suspended sediment through patches of invasive SAV were measured at three tidally forced, freshwater sites, all located within the Sacramento-San Joaquin Delta in California. An acoustic Doppler current profiler deployed from a roving vessel provided velocity and backscatter data used to quantify fluxes of both water and suspended sediment. Sediment trapping efficiency, defined as instantaneous net trapped flux divided by incident flux, was positive in 24 of 29 cases, averaging + 5%. Coupled with 3 years of measured sediment flux data at one site, this suggests that trapping averages 3.7 kg m−2 year−1. This estimate compares favorably with the mean mass accumulation rate of 3.8 kg m−2 year−1 estimated from dated sediment cores collected at the study sites. Long-term measurements made upstream reveal a strong negative trend (− 1.8% year−1) in suspended sediment concentration, and intra-annual changes in both suspended sediment concentration and percent fines. The large footprint and high spatial density of invasive SAV coupled with declining sediment supply are diminishing downstream suspended sediment concentrations, potentially reducing the resiliency of marshes in the Delta and lower estuary to future sea-level rise.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00799-w","usgsCitation":"Work, P.A., Downing-Kunz, M.A., and Drexler, J.Z., 2021, Trapping of suspended sediment by submerged aquatic vegetation in a tidal freshwater region: Field observations and long-term trends: Estuaries and Coasts, v. 44, p. 734-739, https://doi.org/10.1007/s12237-020-00799-w.","productDescription":"6 p.","startPage":"734","endPage":"739","ipdsId":"IP-114567","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":376440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.32177734375,\n 37.60117623656667\n ],\n [\n -121.17919921875001,\n 37.60117623656667\n ],\n [\n -121.17919921875001,\n 38.543869175876154\n ],\n [\n -122.32177734375,\n 38.543869175876154\n ],\n [\n -122.32177734375,\n 37.60117623656667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2020-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":792943,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211507,"text":"70211507 - 2021 - A synthesis of the biology and ecology of sculpin species in the Laurentian Great Lakes and implications for the adaptive capacity of the benthic ecosystem","interactions":[],"lastModifiedDate":"2021-02-03T23:03:20.36816","indexId":"70211507","displayToPublicDate":"2020-07-14T09:32:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5984,"text":"Reviews in Fisheries Science and Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of the biology and ecology of sculpin species in the Laurentian Great Lakes and implications for the adaptive capacity of the benthic ecosystem","docAbstract":"The Laurentian Great Lakes have experienced recent ecosystem changes that could lead to reductions in adaptive capacity and ultimately a loss of biodiversity and production throughout the food web. Observed changes in Great Lakes benthic communities include declines of native species and widespread success of invasive species like dreissenid mussels in all but Lake Superior. Understanding the ecology of native benthic deepwater preyfish and the reasons for their declines is important for predicting future losses in adaptive capacity and diversity, as well as managing the Great Lakes ecosystem to avoid such losses. Native sculpin species (Cottus bairdii, C. cognatus, C. ricei, Myoxocephalus thompsonii) historically were among the most abundant of the Great Lakes native deepwater benthic preyfish community and are an important link between offshore benthic and pelagic food webs. With one exception, these species have declined in abundance throughout the Great Lakes in recent years, but relatively little is known about their biology and ecology. This review synthesizes the available knowledge for the Great Lakes sculpin species and provides suggestions for future research efforts, which include understanding reproductive ecology and spawning behavior, connectivity and dispersal of populations, early life history, and influences of interactions with native and non-native species.
Dryland ecosystems are increasing in geographic extent and contribute greatly to interannual variability in global carbon dynamics. Disentangling interactions among dominant primary producers, including plants and autotrophic microbes, can help partition their contributions to dryland C dynamics. We measured the δ13C signatures of biological soil crust cyanobacteria and dominant plant species (C3 and C4) across a regional scale in the southwestern USA to determine if biocrust cyanobacteria were coupled to plant productivity (using plant-derived C mixotrophically), or independent of plant activity (and therefore purely autotrophic). Cyanobacterial assemblages located next to all C3 plants and one C4 species had consistently more negative δ13C (by 2‰) than the cyanobacteria collected from plant interspaces or adjacent to two C4Bouteloua grass species. The differences among cyanobacterial assemblages in δ13C could not be explained by cyanobacterial community composition, photosynthetic capacity, or any measured leaf or root characteristics (all slopes not different from zero). Thus, microsite differences in abiotic conditions near plants, rather than biotic interactions, remain a likely mechanism underlying the observed δ13C patterns to be tested experimentally.
","language":"English","publisher":"Springerlink","doi":"10.1007/s00248-020-01536-3","usgsCitation":"Stricker, E., Cain, G., Rudgers, J.A., Sinsabaugh, R.L., Fernandes, V., Nelson, C., Giraldo Silva, A., Garcia-Pichel, F., Belnap, J., and Darrouzet-Nardi, A., 2021, What could explain δ13C signatures in biocrust cyanobacteria of drylands?: Microbial Ecology, v. 81, p. 134-145, https://doi.org/10.1007/s00248-020-01536-3.","productDescription":"12 p.","startPage":"134","endPage":"145","ipdsId":"IP-119493","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":380787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jornada Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.81982421874999,\n 32.36372329228304\n ],\n [\n -106.5289306640625,\n 32.36372329228304\n ],\n [\n -106.5289306640625,\n 33.71291698851023\n ],\n [\n -107.81982421874999,\n 33.71291698851023\n ],\n [\n -107.81982421874999,\n 32.36372329228304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","noUsgsAuthors":false,"publicationDate":"2020-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Stricker, Eva 0000-0002-9742-3434","orcid":"https://orcid.org/0000-0002-9742-3434","contributorId":245190,"corporation":false,"usgs":false,"family":"Stricker","given":"Eva","email":"","affiliations":[{"id":49109,"text":"University of New Mexico, Department of Biology, Albuquerque, NM 87131","active":true,"usgs":false}],"preferred":false,"id":805570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, Grace","contributorId":245238,"corporation":false,"usgs":false,"family":"Cain","given":"Grace","email":"","affiliations":[],"preferred":false,"id":805657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudgers, Jennifer A.","contributorId":195173,"corporation":false,"usgs":false,"family":"Rudgers","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":805658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sinsabaugh, Robert L","contributorId":195172,"corporation":false,"usgs":false,"family":"Sinsabaugh","given":"Robert","email":"","middleInitial":"L","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":805659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fernandes, Vanessa","contributorId":245239,"corporation":false,"usgs":false,"family":"Fernandes","given":"Vanessa","email":"","affiliations":[],"preferred":false,"id":805660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, Corey","contributorId":245240,"corporation":false,"usgs":false,"family":"Nelson","given":"Corey","affiliations":[],"preferred":false,"id":805661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Giraldo Silva, Ana","contributorId":181758,"corporation":false,"usgs":false,"family":"Giraldo Silva","given":"Ana","email":"","affiliations":[],"preferred":false,"id":805662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garcia-Pichel, Ferran","contributorId":166779,"corporation":false,"usgs":false,"family":"Garcia-Pichel","given":"Ferran","email":"","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":805663,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":805578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Darrouzet-Nardi, Anthony adarrouzet-nardi@usgs.gov","contributorId":207292,"corporation":false,"usgs":false,"family":"Darrouzet-Nardi","given":"Anthony","email":"adarrouzet-nardi@usgs.gov","affiliations":[],"preferred":false,"id":805664,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70211895,"text":"70211895 - 2021 - Sediment budget estimates for a highly impacted embayment with extensive wetland loss","interactions":[],"lastModifiedDate":"2021-03-19T20:20:11.364762","indexId":"70211895","displayToPublicDate":"2020-07-01T08:16:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Sediment budget estimates for a highly impacted embayment with extensive wetland loss","docAbstract":"External sediment supply is an important control on wetland morphology and vulnerability to storms, sea-level rise, and land use change. Constraining sediment supply and net budgets is difficult due to multiple timescales of variability in hydrodynamic forcing and suspended-sediment concentrations, as well as the fundamental limitations of measurement and modeling technologies. We used two independent observational campaigns and one hydrodynamic modeling effort to estimate the sediment supply to Jamaica Bay, New York, USA, an urbanized embayment with a history of extensive wetland loss. We found that all three estimates indicate a net import to the system, ranging from 36 x 106 – 74 x 106 kg/y, with a mean estimate of 55,000 t/y +/- 31,000 t/y, which compares well with a prior estimate derived from radionuclide tracers. Net sediment import is controlled by flood-ebb asymmetry in bed shear stress, which results in higher suspended sediment concentrations on flood tide relative to ebb. This indicates a seaward source of sediment, likely offshore marine deposits and potentially sediment from the adjacent Hudson River-Estuary that is resuspended by waves in the coastal ocean. Despite the net sediment import, a simple sediment budget suggests that the rate of supply is not sufficient to maintain the present geomorphic planform of the system relative to sea-level rise. The convergent estimates from independent methods provide reasonable guidance as context for sediment-based restoration efforts.","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00784-3","usgsCitation":"Chant, R., Ralston, D.K., Ganju, N., Pianca, C., Simonson, A., and Cartwright, R., 2021, Sediment budget estimates for a highly impacted embayment with extensive wetland loss: Estuaries and Coasts, v. 44, p. 608-626, https://doi.org/10.1007/s12237-020-00784-3.","productDescription":"19 p.","startPage":"608","endPage":"626","ipdsId":"IP-104431","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":377319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Grassey Bay, Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.14947509765625,\n 40.50126945841645\n ],\n [\n -73.7457275390625,\n 40.50126945841645\n ],\n [\n -73.7457275390625,\n 40.74101426921151\n ],\n [\n -74.14947509765625,\n 40.74101426921151\n ],\n [\n -74.14947509765625,\n 40.50126945841645\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2020-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Chant, Robert","contributorId":237975,"corporation":false,"usgs":false,"family":"Chant","given":"Robert","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":795713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralston, David K. 0000-0002-0774-3101","orcid":"https://orcid.org/0000-0002-0774-3101","contributorId":195909,"corporation":false,"usgs":false,"family":"Ralston","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":795714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":795715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pianca, Casia","contributorId":237976,"corporation":false,"usgs":false,"family":"Pianca","given":"Casia","email":"","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":795716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simonson, Amy","contributorId":237977,"corporation":false,"usgs":false,"family":"Simonson","given":"Amy","affiliations":[{"id":47668,"text":"NYWSC","active":true,"usgs":false}],"preferred":false,"id":795717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cartwright, Richard","contributorId":237978,"corporation":false,"usgs":false,"family":"Cartwright","given":"Richard","affiliations":[{"id":47668,"text":"NYWSC","active":true,"usgs":false}],"preferred":false,"id":795718,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211817,"text":"70211817 - 2021 - Eradication of sea lampreys from the Laurentian Great Lakes is possible","interactions":[],"lastModifiedDate":"2022-01-06T15:29:46.962576","indexId":"70211817","displayToPublicDate":"2020-05-14T08:12:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Eradication of sea lampreys from the Laurentian Great Lakes is possible","docAbstract":"Eradication has been achieved for many vertebrate pest control programs, primarily on small, isolated islands, but has never been considered a practical goal for invasive sea lampreys in the Laurentian Great Lakes. Our objective was to examine evidence relevant to the feasibility of setting eradication as a management goal for Great Lakes sea lampreys. Bomford and O'Brien (1995) listed six conditions for successful eradication of a vertebrate pest; here we examine evidence that these conditions are likely to be met for Great Lakes sea lampreys, with a focus on the first condition: that removal of the pest through control can exceed their rate of replenishment. We analyzed two data sets – one empirical and one synthetic – to estimate stock-recruitment relationships and calculate the exploitation rate necessary for extinction. The empirical data set included the effect of existing lampricide control and suggested an exploitation rate of 59%, in addition to lampricide control, would be sufficient for eventual eradication. The synthetic data set, derived from a simulation of stream-level recruitment dynamics in the absence of lampricide control, suggested that an overall exploitation rate of 90% would be sufficient. We suggest that both of these targets could be achieved. Meeting the other conditions will depend on the scale of the eradication effort, and on development of an exploitation strategy, such as genetic biocontrol, that can target sea lampreys in presently invulnerable habitats. Overall, we concluded that eradication of sea lampreys from the Great Lakes should not be dismissed as a prospective goal.
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University","active":true,"usgs":false}],"preferred":false,"id":795226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":795225,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216760,"text":"70216760 - 2021 - Assessment of NMR logging for estimating hydraulic conductivity in glacial aquifers","interactions":[],"lastModifiedDate":"2021-01-19T16:10:34.106194","indexId":"70216760","displayToPublicDate":"2020-05-10T09:40:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of NMR logging for estimating hydraulic conductivity in glacial aquifers","docAbstract":"Glacial aquifers are an important source of groundwater in the United States and require accurate characterization to make informed management decisions. One parameter that is crucial for understanding the movement of groundwater is hydraulic conductivity, K. Nuclear magnetic resonance (NMR) logging measures the NMR response associated with the water in geological materials. By utilizing an external magnetic field to manipulate the nuclear spins associated with 1H, the time‐varying decay of the nuclear magnetization is measured. This logging method could provide an effective way to estimate K at submeter vertical resolution, but the models that relate NMR measurements to K require calibration. At two field sites in a glacial aquifer in central Wisconsin, we collected a total of four NMR logs and obtained measurements of K in their immediate vicinity with a direct‐push permeameter (DPP). Using a bootstrap algorithm to calibrate the Schlumberger‐Doll Research (SDR) NMR‐K model, we estimated K to within a factor of 5 of the DPP measurements. The lowest levels of accuracy occurred in the lower‐K (K < 10−4 m/s) intervals. We also evaluated the applicability of prior SDR model calibrations. We found the NMR calibration parameters varied with K, suggesting the SDR model does not incorporate all the properties of the pore space that control K. Thus, the expected range of K in an aquifer may need to be considered during calibration of NMR‐K models. This study is the first step toward establishing NMR logging as an effective method for estimating K in glacial aquifers.
Mercury (Hg) bioaccumulates in aquatic ecosystems and may pose a risk to humans who consume fish. Selenium (Se) has the ability to reduce Hg toxicity, but the current guidance for human consumption of fish is based on Hg concentration alone. The purpose of the present study was to examine the relationship between Se and Hg in freshwater sportfish, for which there is a paucity of existing data. We collected three species of fish from different trophic positions from two drinking water reservoirs in central North Carolina, USA, to assess Hg and Se concentrations in relation to fish total length and to compare two measures of the protective ability of Se, the Se:Hg molar ratio and Se health benefit value (HBVSe), to current guidance for Hg. According to the Se:Hg molar ratio, all of the low trophic position fish sampled and the middle trophic position fish sampled from one of the reservoirs were safe for consumption. The same number of fish were considered safe using the HBVSe. More fish were deemed unsafe when using the Se:Hg molar ratio and HBVSe than were considered unsafe when using the U.S. Environmental Protection Agency (USEPA) Hg threshold. These findings suggest that the measures of Se protection may be unnecessarily conservative or that the USEPA Hg threshold may not be sufficiently protective of human health, especially the health of sensitive populations like pregnant or nursing mothers and young children. Future examination of the Se:Hg molar ratio and HBVSe from a variety of fish tissue samples would help refine the accuracy of these measures so that they may be appropriately utilized in ecological and human health risk assessment.
","language":"English","publisher":"MDPI","doi":"10.3390/ijerph15091864","usgsCitation":"Johnson, T.K., LePrevost, C.E., Kwak, T.J., and Cope, W.G., 2021, Selenium, mercury, and their molar ratios in sportfishes from drinking water reservoirs: International Journal of Environmental Research and Public Health, v. 15, no. 9, 1864, 17 p., https://doi.org/10.3390/ijerph15091864.","productDescription":"1864, 17 p.","ipdsId":"IP-100876","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijerph15091864","text":"Publisher Index Page"},{"id":388174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Tara K. B.","contributorId":264411,"corporation":false,"usgs":false,"family":"Johnson","given":"Tara","email":"","middleInitial":"K. B.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LePrevost, C. E.","contributorId":264412,"corporation":false,"usgs":false,"family":"LePrevost","given":"C.","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. G.","contributorId":264384,"corporation":false,"usgs":false,"family":"Cope","given":"W.","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821491,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228638,"text":"70228638 - 2020 - Animal movement models with mechanistic selection functions","interactions":[],"lastModifiedDate":"2022-02-16T21:09:54.812755","indexId":"70228638","displayToPublicDate":"2022-06-20T15:05:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Animal movement models with mechanistic selection functions","docAbstract":"A suite of statistical methods are used to study animal movement. Most of\nthese methods treat animal trajectory data in one of three ways: as discrete pro-\ncesses, as continuous processes, or as point processes. We brie\ny review each of\nthese approaches and then focus in on the latter. In the context of point processes,\nso-called resource selection analyses are among the most common way to statis-\ntically treat animal trajectory data. However, most resource selection analyses provide inference based on approximations of point process models. The forms of\nthese models have been limited to a few types of specications that provide infer-\nence about relative resource use and, less commonly, probability of use. For more\ngeneral spatio-temporal point process models, the most common type of analysis\noften proceeds with a data augmentation approach that is used to create a binary\ndata set that can be analyzed with conditional logistic regression. We show that\nthe conditional logistic regression likelihood can be generalized to accommodate a\nvariety of alternative specications related to resource selection. We then provide\nan example of a case where a spatio-temporal point process model coincides with\nthat implied by a mechanistic model for movement expressed as a partial dier-\nential equation derived from rst principles of movement. We demonstrate that\ninference from this form of point process model is intuitive (and could be useful\nfor management and conservation) by analyzing a set of telemetry data from a\nmountain lion in Colorado, USA, to understand the eects of spatially explicit\nenvironmental conditions on movement behavior of this species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.spasta.2019.100406","usgsCitation":"Hooten, M., Lu, X., Garlick, M., and Powell, J., 2020, Animal movement models with mechanistic selection functions: Spatial Statistics, v. 37, 100406, 14 p., https://doi.org/10.1016/j.spasta.2019.100406.","productDescription":"100406, 14 p.","ipdsId":"IP-113283","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":454582,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1911.03549","text":"External Repository"},{"id":396041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":834902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Xinyi","contributorId":279368,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyi","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":834903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garlick, Martha J.","contributorId":279369,"corporation":false,"usgs":false,"family":"Garlick","given":"Martha J.","affiliations":[{"id":57249,"text":"sdsmt","active":true,"usgs":false}],"preferred":false,"id":834904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, James A.","contributorId":279370,"corporation":false,"usgs":false,"family":"Powell","given":"James A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":834905,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220323,"text":"70220323 - 2020 - Improving the positional and vertical accuracy of named summits above 13,000 ft in the United States","interactions":[],"lastModifiedDate":"2021-05-06T13:30:25.542612","indexId":"70220323","displayToPublicDate":"2020-12-31T08:22:33","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Improving the positional and vertical accuracy of named summits above 13,000 ft in the United States","docAbstract":"The National Map (TNM) portal provides public access to U.S. Geological Survey (USGS) high-resolution topographic datasets, and maps from the Historical Topographic Map Collection (HTMC). Elevation values shown on HTMC maps were obtained from ground spot elevation measurements, as compared to today’s elevation measurements derived from more efficient methods, such as lidar, radar, or sonar. These spot elevations were collected either by levelling in the field or by photogrammetrists in the office, and are called mass points with post-spacings of two-arc seconds (arcsec), approximately 60 meters depending on latitude, in steep terrain and one-half arcsec, approximately 15 meters, in flat terrain (Federal Geographic Data Committee 1997). The vertical accuracy of spot elevations is ± 10 feet. Most spot elevations were used only in contour derivation to create a more spatially continuous representations of terrain, but some were also labelled on the maps to supply accurate elevations of culturally important features such as mountain peaks, gaps, and road junctions.
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population genetic information that provides insights into adaptive potential, population size, interpopulation connectivity, and even extinction risk in portions of a species range. The Striped Whipsnake (Masticophis taeniatus) occurs across 11 western U.S. states and into Mexico but has experienced population declines in parts of its range, particularly in the state of Washington. We analyzed nuclear and mitochondrial DNA extracted from 192 shed skins, 63 muscle tissue samples, and one mouth swab to assess local genetic diversity and differentiation within and between the last known whipsnake populations in Washington. We then placed that information in a regional context to better understand levels of differentiation and diversity among whipsnake populations in the northwestern portion of the range of the species. Microsatellite data analyses indicated that there was comparable genetic diversity between the two extant Washington populations, but gene flow may be somewhat limited. We found moderate to high levels of genetic differentiation among states across all markers, including five microsatellites, two nuclear genes, and two mitochondrial genes. Pairwise state-level comparisons and dendrograms suggested that Washington whipsnakes are most closely related to those in Oregon, and distinct from Idaho, Nevada, and Utah, approximately following an isolation by distance model. We conclude that Washington populations of whipsnakes have experienced recent isolating events, but they have yet to lose genetic diversity. The longevity and high vagility of the species may provide opportunity for conservation of whipsnakes in the state as long as shrubland habitat is available","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Pilliod, D.S., Hallock, L.A., Miller, M.P., Mullins, T.D., and Haig, S.M., 2020, Conservation genetics of imperiled striped whipsnake in Washington: Herpetological Conservation and Biology, v. 15, no. 3, p. 597-610.","productDescription":"14 p.","startPage":"597","endPage":"610","ipdsId":"IP-117373","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":381993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381977,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/~herpconb/contents_vol15_issue3.html"}],"country":"United 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\"}}]}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":807741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hallock, Lisa A.","contributorId":247496,"corporation":false,"usgs":false,"family":"Hallock","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":807754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":807755,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullins, Thomas D. 0000-0001-8948-9604 tom_mullins@usgs.gov","orcid":"https://orcid.org/0000-0001-8948-9604","contributorId":149824,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas","email":"tom_mullins@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":807756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":807757,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228612,"text":"70228612 - 2020 - Inter-individual differences in the foraging behavior of breeding Adélie penguins are driven by individual quality and sex","interactions":[],"lastModifiedDate":"2022-02-14T13:25:50.703049","indexId":"70228612","displayToPublicDate":"2020-12-31T07:22:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2636,"text":"MEPS","active":true,"publicationSubtype":{"id":10}},"title":"Inter-individual differences in the foraging behavior of breeding Adélie penguins are driven by individual quality and sex","docAbstract":"Inter-individual differences in demographic traits of iteroparous species can arise through learning and maturation, as well as from permanent differences in individual ‘quality’ and sex-specific constraints. As the ability to acquire energy determines the resources an individual can allocate to reproduction and self-maintenance, foraging behavior is a key trait to study to better understand the mechanisms underlying these differences. So far, most seabird studies have focused on the effect of maturation and learning processes on foraging performance, while only a few have included measures of individual quality. Here, we investigated the effects of age, breeding experience, sex, and individual breeding quality on the foraging behavior and location of 83 known-age Adélie penguins at Cape Bird, Ross Sea, Antarctica. Over a 2 yr period, we showed that (1) high-quality birds dived deeper than lower quality ones, apparently catching a higher number of prey per dive and targeting different foraging locations; (2) females performed longer foraging trips and a higher number of dives compared to males; (3) there were no significant age-related differences in foraging behavior; and (4) breeding experience had a weak influence on foraging behavior. We suggest that high-quality individuals have higher physiological ability, enabling them to dive deeper and forage more effectively. Further inquiry should focus on determining the physiological differences among penguins of different quality.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps13208","usgsCitation":"Lescroël, A., Lyver, P., Jongsomjit, D., Veloz, S., Dugger, K., Kappes, P., Karl, B., Whitehead, A., Pech, R., Cole, T.L., and Ballard, G., 2020, Inter-individual differences in the foraging behavior of breeding Adélie penguins are driven by individual quality and sex: MEPS, v. 636, p. 189-205, https://doi.org/10.3354/meps13208.","productDescription":"17 p.","startPage":"189","endPage":"205","ipdsId":"IP-112127","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"636","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lescroël, Amelie","contributorId":276366,"corporation":false,"usgs":false,"family":"Lescroël","given":"Amelie","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyver, Phil O’B.","contributorId":276368,"corporation":false,"usgs":false,"family":"Lyver","given":"Phil O’B.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jongsomjit, Dennis","contributorId":276370,"corporation":false,"usgs":false,"family":"Jongsomjit","given":"Dennis","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veloz, Sam","contributorId":276372,"corporation":false,"usgs":false,"family":"Veloz","given":"Sam","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kappes, Peter","contributorId":276374,"corporation":false,"usgs":false,"family":"Kappes","given":"Peter","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karl, Brian J.","contributorId":276377,"corporation":false,"usgs":false,"family":"Karl","given":"Brian J.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitehead, Amy L.","contributorId":276379,"corporation":false,"usgs":false,"family":"Whitehead","given":"Amy L.","affiliations":[{"id":25457,"text":"NIWA","active":true,"usgs":false}],"preferred":false,"id":834802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pech, Roger","contributorId":276381,"corporation":false,"usgs":false,"family":"Pech","given":"Roger","email":"","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834803,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cole, Theresa L.","contributorId":276383,"corporation":false,"usgs":false,"family":"Cole","given":"Theresa","email":"","middleInitial":"L.","affiliations":[{"id":12679,"text":"Landcare Research","active":true,"usgs":false}],"preferred":false,"id":834804,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ballard, Grant","contributorId":276385,"corporation":false,"usgs":false,"family":"Ballard","given":"Grant","affiliations":[{"id":48619,"text":"pbcs","active":true,"usgs":false}],"preferred":false,"id":834805,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70217211,"text":"70217211 - 2020 - Multilocus metabarcoding of terrestrial leech bloodmeal iDNA increases species richness uncovered in surveys of vertebrate host biodiversity","interactions":[],"lastModifiedDate":"2021-01-13T13:15:51.987522","indexId":"70217211","displayToPublicDate":"2020-12-31T07:13:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Multilocus metabarcoding of terrestrial leech bloodmeal iDNA increases species richness uncovered in surveys of vertebrate host biodiversity","docAbstract":"Leech-derived invertebrate DNA (iDNA) has been successfully leveraged to conduct surveys of vertebrate host biodiversity across the Indo Pacific. However, this technique has been limited methodologically, typically only targeting mammalian 16S rDNA, or both 16S and vertebrate 12S rDNA for leech host determination. To improve the taxonomic richness of vertebrate host species in iDNA surveys, we re-analyze datasets from Bangladesh, Cambodia, China, and Madagascar through metabarcoding via next generation sequencing (NGS) of 12S, 16S (2 types, one designed to target mammals and the other, residual eDNA), nicotinamide adenine dinucleotide hydride dehydrogenase 2 (ND2), and cytochrome c oxidase subunit 1 (COI). With our 5 primer sets, we identify 41 unique vertebrate hosts to the species level, among 1,200 leeches analyzed, along with an additional 13 taxa to the family rank. Within our 41 taxa, we note that adding ND2 and COI loci increased species richness detection by 25%. NGS has emerged as more efficient than Sanger sequencing for large scale metabarcoding applications and, with the decline in cost of NGS, our pooled sample multilocus protocol is an attractive option for iDNA biodiversity surveys.
The Northern Goshawk (Accipiter gentilis) is an apex predator occurring across North America and Eurasia. The species has received considerable conservation focus in late-seral conifer forests of western North America, where its habitat has been substantially reduced and altered by timber harvest and is increasingly at risk from high severity fire, drought, and forest pathogens. In the Sierra Nevada range of California, management and conservation of goshawks are hampered by a lack of knowledge of their basic space use and movement ecology. We used global positioning system (GPS) loggers to investigate space use of 20 resident, adult Northern Goshawks over 3 yr (2015–2018) in the Plumas National Forest, California. Median home range sizes of male goshawks were more than twice as large as those of females, and nonbreeding-season home ranges were three times larger than breeding-season home ranges. High resolution GPS data (location interval 1–6 min) allowed quantification of daily transit distances up to 60 km for individual goshawks and revealed long-distance forays into adjacent territories and surrounding areas. Four goshawks (three males, one female) undertook forays >8 km from their nest locations, with forays lasting up to 6 d; these forays occurred during both breeding and nonbreeding seasons for both sexes. Comparing our results to current conservation approaches, we determined that USDA Forest Service goshawk Protected Activity Centers protected <25% of both the roost locations and the area used during the daytime. Conservation efforts for Northern Goshawks in the Sierra Nevada would benefit from consideration of year-round habitat needs at larger scales than previously thought.