Bees are the predominant pollinating taxa, providing a critical ecosystem service upon which many angiosperms rely for successful reproduction. Available data suggests that bee populations worldwide are declining, but scarce data in tropical regions precludes assessing their status and distribution, impact on ecological services, and response to management actions. Herein, we reviewed >150 papers that used six common sampling methods (pan traps, baits, Malaise traps, sweep nets, timed observations and aspirators) to better understand their strengths and weaknesses, and help guide method selection to meet research objectives and development of multi-species monitoring approaches. Several studies evaluated the effectiveness of sweep nets, pan traps, and malaise traps, but only one evaluated timed observations, and none evaluated aspirators. Only five studies compared two or more of the remaining four sampling methods to each other. There was little consensus regarding which method would be most reliable for sampling multiple species. However, we recommend that if the objective of the study is to estimate abundance or species richness, malaise traps, pan traps and sweep nets are the most effective sampling protocols in open tropical systems; conversely, malaise traps, nets and baits may be the most effective in forests. Declining bee populations emphasize the critical need in method standardization and reporting precision. Moreover, we recommend reporting a catchability coefficient, a measure of the interaction between the resource (bee) abundance and catching effort. Melittologists could also consider existing methods, such as occupancy models, to quantify changes in distribution and abundance after modeling heterogeneity in trapping probability, and consider the possibility of developing monitoring frameworks that draw from multiple sources of data.
","language":"English","publisher":"Springer","doi":"10.1007/s10841-017-0018-8","usgsCitation":"Prado, S.G., Ngo, H.T., Florez, J.A., and Collazo, J., 2017, Sampling bees in tropical forests and agroecosystems: A review: Journal of Insect Conservation, v. 21, no. 5-6, p. 753-770, https://doi.org/10.1007/s10841-017-0018-8.","productDescription":"18 p.","startPage":"753","endPage":"770","ipdsId":"IP-082870","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10841-017-0018-8","text":"Publisher Index Page"},{"id":353848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"5-6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-22","publicationStatus":"PW","scienceBaseUri":"5afee79de4b0da30c1bfc30c","contributors":{"authors":[{"text":"Prado, Sara G.","contributorId":204504,"corporation":false,"usgs":false,"family":"Prado","given":"Sara","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":734202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ngo, Hien T.","contributorId":204505,"corporation":false,"usgs":false,"family":"Ngo","given":"Hien","email":"","middleInitial":"T.","affiliations":[{"id":36950,"text":"United Nations, Bonn","active":true,"usgs":false}],"preferred":false,"id":734203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Florez, Jaime A.","contributorId":204506,"corporation":false,"usgs":false,"family":"Florez","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":734204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":734201,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194677,"text":"70194677 - 2017 - How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction","interactions":[],"lastModifiedDate":"2018-01-08T14:36:50","indexId":"70194677","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"displayTitle":"How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction","title":"How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction","docAbstract":"Wildlife managers often request a simple approach to monitor the status of species of concern. In response to that need, we used eight years of monitoring data to estimate population size and test the validity of an index for monitoring accurately the abundance of reintroduced, endangered Laysan Teal Anas laysanensis. The population was established at Midway Atoll in the Hawaiian archipelago after 42 wild birds were translocated from Laysan Island during 2004–2005. We fitted 587 birds with unique markers during 2004–2015, recorded 21,309 sightings until March 2016, and conducted standardised survey counts during 2007–2015. A modified Lincoln-Petersen mark-resight estimator and ANCOVA models were used to test the relationship between survey counts, seasonal detectability, and population abundance. Differences were found between the breeding and non-breeding seasons in detection and how maximum counts recorded related to population estimates. The results showed strong, positive correlations between the seasonal maximum counts and population estimates. The ANCOVA models supported the use of standardised bi-monthly counts of unmarked birds as a valid index to monitor trends among years within a season at Midway Atoll. The translocated population increased to 661 adult and juvenile birds (95% CI = 608–714) by 2010, then declined by 38% between 2010 and 2012 after the Toˉhoku Japan earthquake-generated tsunami inundated 41% of the atoll and triggered an Avian Botulism type C Clostridium botulinum outbreak. Following another severe botulism outbreak during 2015, the population experienced a 37% decline. Data indicated that the Midway Atoll population, like the founding Laysan Island population, is susceptible to catastrophic population declines. Consistent standardised monitoring using simple counts, in place of mark-recapture and resightings surveys, can be used to evaluate population status over the long-term. We estimate there were 314–435 Laysan Teal (95% CI for population estimate; point estimate = 375 individuals) at Midway Atoll in 2015; c. 50% of the global population. In comparison, the most recent estimate for numbers on Laysan Island was of 339 individuals in 2012 (95% CI = 265–413). We suggest that this approach can be used to validate a survey index for any marked, reintroduced resident wildlife population.
","language":"English","publisher":"Wildfowl & Wetlands Trust","usgsCitation":"Reynolds, M.H., Courtot, K., and Hatfield, J., 2017, How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction: Wildfowl, v. 67, p. 60-71.","productDescription":"12 p.","startPage":"60","endPage":"71","ipdsId":"IP-079986","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":349950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349942,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2664/1781"}],"otherGeospatial":"Midway Atoll","volume":"67","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf6e4b06e28e9c22a22","contributors":{"authors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","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":724869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Courtot, Karen 0000-0002-8849-4054 kcourtot@usgs.gov","orcid":"https://orcid.org/0000-0002-8849-4054","contributorId":140002,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen","email":"kcourtot@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":724870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatfield, Jeffrey 0000-0002-6517-2925 jhatfield@usgs.gov","orcid":"https://orcid.org/0000-0002-6517-2925","contributorId":139261,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeffrey","email":"jhatfield@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":724871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194680,"text":"70194680 - 2017 - Interactions among invasive plants: Lessons from Hawai‘i","interactions":[],"lastModifiedDate":"2018-01-03T13:06:42","indexId":"70194680","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":808,"text":"Annual Review of Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Interactions among invasive plants: Lessons from Hawai‘i","docAbstract":"Most ecosystems have multiple-plant invaders rather than single-plant invaders, yet ecological studies and management actions focus largely on single invader species. There is a need for general principles regarding invader interactions across varying environmental conditions, so that secondary invasions can be anticipated and managers can allocate resources toward pretreatment or postremoval actions. By reviewing removal experiments conducted in three Hawaiian ecosystems (a dry tropical forest, a seasonally dry mesic forest, and a lowland wet forest), we evaluate the roles environmental harshness, priority effects, productivity potential, and species interactions have in influencing secondary invasions, defined here as invasions that are influenced either positively (facilitation) or negatively (inhibition/priority effects) by existing invaders. We generate a conceptual model with a surprise index to describe whether long-term plant invader composition and dominance is predictable or stochastic after a system perturbation such as a removal experiment. Under extremely low resource availability, the surprise index is low, whereas under intermediate-level resource environments, invader dominance is more stochastic and the surprise index is high. At high resource levels, the surprise index is intermediate: Invaders are likely abundant in the environment but their response to a perturbation is more predictable than at intermediate resource levels. We suggest further testing across environmental gradients to determine key variables that dictate the predictability of postremoval invader composition.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-ecolsys-110316-022620","usgsCitation":"D’Antonio, C.M., Ostertag, R., Cordell, S., and Yelenik, S.G., 2017, Interactions among invasive plants: Lessons from Hawai‘i: Annual Review of Ecology, Evolution, and Systematics, v. 48, p. 521-541, https://doi.org/10.1146/annurev-ecolsys-110316-022620.","productDescription":"21 p.","startPage":"521","endPage":"541","ipdsId":"IP-087888","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":469266,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-ecolsys-110316-022620","text":"Publisher Index Page"},{"id":349949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","volume":"48","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf6e4b06e28e9c22a20","contributors":{"authors":[{"text":"D’Antonio, Carla M.","contributorId":196690,"corporation":false,"usgs":false,"family":"D’Antonio","given":"Carla","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":724878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostertag, Rebecca","contributorId":197840,"corporation":false,"usgs":false,"family":"Ostertag","given":"Rebecca","email":"","affiliations":[],"preferred":false,"id":724879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cordell, Susan","contributorId":197818,"corporation":false,"usgs":false,"family":"Cordell","given":"Susan","email":"","affiliations":[],"preferred":false,"id":724880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":724877,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195197,"text":"70195197 - 2017 - Decaying lava extrusion rate at El Reventador Volcano, Ecuador measured using high-resolution satellite radar","interactions":[],"lastModifiedDate":"2018-02-07T12:57:06","indexId":"70195197","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Decaying lava extrusion rate at El Reventador Volcano, Ecuador measured using high-resolution satellite radar","docAbstract":"Lava extrusion at erupting volcanoes causes rapid changes in topography and morphology on the order of tens or even hundreds of meters. Satellite radar provides a method for measuring changes in topographic height over a given time period to an accuracy of meters, either by measuring the width of radar shadow cast by steep sided features, or by measuring the difference in radar phase between two sensors separated in space. We measure height changes, and hence estimate extruded lava volume flux, at El Reventador, Ecuador, between 2011 and 2016, using data from the RADARSAT-2 and TanDEM-X satellite missions. We find that 39 new lava flows were extruded between 9 February 2012 and 24 August 2016, with a cumulative volume of 44.8M m3 dense rock equivalent and a gradually decreasing eruption rate. The average dense rock rate of lava extrusion during this time is 0.31 ± 0.02 m3 s−1, which is similar to the long-term average from 1972 to 2016. Apart from a volumetrically small dyke opening event between 9 March and 10 June 2012, lava extrusion at El Reventador is not accompanied by any significant magmatic ground deformation. We use a simple physics-based model to estimate that the volume of the magma reservoir under El Reventador is greater than 3 km3. Our lava extrusion data can be equally well fit by models representing a closed reservoir depressurising during the eruption with no magma recharge, or an open reservoir with a time-constant magma recharge rate of up to 0.35 ± 0.01 m3 s−1.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014580","usgsCitation":"Arnold, D.W., Biggs, J., Anderson, K.R., Vallejo Vargas, S., Wadge, G., Ebmeier, S.K., Naranjo, M.F., and Mothes, P., 2017, Decaying lava extrusion rate at El Reventador Volcano, Ecuador measured using high-resolution satellite radar: Journal of Geophysical Research B: Solid Earth, v. 122, no. 12, p. 9966-9988, https://doi.org/10.1002/2017JB014580.","productDescription":"23 p.","startPage":"9966","endPage":"9988","ipdsId":"IP-088140","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb014580","text":"Publisher Index Page"},{"id":351244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"El Reventador Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.6083,\n -0.1083\n ],\n [\n -77.6667,\n -0.1083\n ],\n [\n -77.6667,\n -0.0667\n ],\n [\n -77.6083,\n -0.0667\n ],\n [\n -77.6083,\n -0.1083\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-29","publicationStatus":"PW","scienceBaseUri":"5a7c1e77e4b00f54eb22930e","contributors":{"authors":[{"text":"Arnold, D. 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K.","contributorId":202023,"corporation":false,"usgs":false,"family":"Ebmeier","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":36323,"text":"COMET, School of Earth Sciences, University of Bristol, Bristol, UK","active":true,"usgs":false}],"preferred":false,"id":727395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Naranjo, M. F.","contributorId":202024,"corporation":false,"usgs":false,"family":"Naranjo","given":"M.","email":"","middleInitial":"F.","affiliations":[{"id":36324,"text":"Instituto Geofísico, Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":727396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mothes, P.","contributorId":202025,"corporation":false,"usgs":false,"family":"Mothes","given":"P.","email":"","affiliations":[{"id":36326,"text":"COMET, School of Earth and Environment, University of Leeds, Leeds, UK","active":true,"usgs":false}],"preferred":false,"id":727397,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196280,"text":"70196280 - 2017 - Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska","interactions":[],"lastModifiedDate":"2022-04-22T15:45:51.011946","indexId":"70196280","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska","docAbstract":"Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator (R2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI (R2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study demonstrates the importance of matching the scale of NDVI measurements to the vegetation properties of biomass and nitrogen phenology.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9121234","usgsCitation":"Hogrefe, K.R., Patil, V.P., Ruthrauff, D.R., Meixell, B.W., Budde, M.E., Hupp, J.W., and Ward, D.H., 2017, Normalized difference vegetation index as an estimator for abundance and quality of avian herbivore forage in arctic Alaska: Remote Sensing, v. 9, no. 12, 1234; 21 p., https://doi.org/10.3390/rs9121234.","productDescription":"1234; 21 p.","ipdsId":"IP-088696","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469282,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9121234","text":"Publisher Index Page"},{"id":438135,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M907KT","text":"USGS data release","linkHelpText":"Normalized Difference Vegetation Index, Biomass, and Nitrogen Content of Goose Forage, Northern Alaska, 2011-2018"},{"id":352986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.79,\n 70.455\n ],\n [\n -150.75,\n 70.455\n ],\n [\n -150.75,\n 70.467\n ],\n [\n -150.79,\n 70.467\n ],\n [\n -150.79,\n 70.455\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-29","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc316","contributors":{"authors":[{"text":"Hogrefe, Kyle R. 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mbudde@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":3007,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","email":"mbudde@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":732078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196276,"text":"70196276 - 2017 - Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule","interactions":[],"lastModifiedDate":"2018-03-30T10:46:58","indexId":"70196276","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule","docAbstract":"The evolutionary trajectory of populations through time is influenced by the interplay of forces (biological, evolutionary, and anthropogenic) acting on the standing genetic variation. We used microsatellite and mitochondrial loci to examine the influence of population declines, of varying severity, on genetic diversity within two Hawaiian endemic waterbirds, the Hawaiian coot and Hawaiian gallinule, by comparing historical (samples collected in the late 1800s and early 1900s) and modern (collected in 2012–2013) populations. Population declines simultaneously experienced by Hawaiian coots and Hawaiian gallinules differentially shaped the evolutionary trajectory of these two populations. Within Hawaiian coot, large reductions (between −38.4% and −51.4%) in mitochondrial diversity were observed, although minimal differences were observed in the distribution of allelic and haplotypic frequencies between sampled time periods. Conversely, for Hawaiian gallinule, allelic frequencies were strongly differentiated between time periods, signatures of a genetic bottleneck were detected, and biases in means of the effective population size were observed at microsatellite loci. The strength of the decline appears to have had a greater influence on genetic diversity within Hawaiian gallinule than Hawaiian coot, coincident with the reduction in census size. These species exhibit similar life history characteristics and generation times; therefore, we hypothesize that differences in behavior and colonization history are likely playing a large role in how allelic and haplotypic frequencies are being shaped through time. Furthermore, differences in patterns of genetic diversity within Hawaiian coot and Hawaiian gallinule highlight the influence of demographic and evolutionary processes in shaping how species respond genetically to ecological stressors.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3530","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Underwood, J.G., 2017, Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule: Ecology and Evolution, v. 7, no. 23, p. 9925-9934, https://doi.org/10.1002/ece3.3530.","productDescription":"10 p.","startPage":"9925","endPage":"9934","ipdsId":"IP-085014","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3530","text":"Publisher Index Page"},{"id":352990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"23","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc318","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":732031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":732032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Underwood, Jared G.","contributorId":198606,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":732033,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196267,"text":"70196267 - 2017 - Vectors, hosts, and control measures for Zika virus in the Americas","interactions":[],"lastModifiedDate":"2018-03-29T10:19:09","indexId":"70196267","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Vectors, hosts, and control measures for Zika virus in the Americas","docAbstract":"We examine Zika virus (ZIKV) from an ecological perspective and with a focus on the Americas. We assess (1) the role of wildlife in ZIKV disease ecology, (2) how mosquito behavior and biology influence disease dynamics, and (3) how nontarget species and ecosystems may be impacted by vector control programs. Our review suggests that free-ranging, non-human primates may be involved in ZIKV transmission in the Old World; however, other wildlife species likely play a limited role in maintaining or transmitting ZIKV. In the Americas, a zoonotic cycle has not yet been definitively established. Understanding behaviors and habitat tolerances of Aedes aegypti and Aedes albopictus, two ZIKV competent vectors in the Americas, will allow more accurate modeling of disease spread and facilitate targeted and effective control efforts. Vector control efforts may have direct and indirect impacts to wildlife, particularly invertebrate feeding species; however, strategies could be implemented to limit detrimental ecological effects.
","language":"English","publisher":"Springer","doi":"10.1007/s10393-017-1277-2","usgsCitation":"Thompson, S.J., Pearce, J.M., and Ramey, A.M., 2017, Vectors, hosts, and control measures for Zika virus in the Americas: EcoHealth, v. 14, no. 4, p. 821-839, https://doi.org/10.1007/s10393-017-1277-2.","productDescription":"19 p.","startPage":"821","endPage":"839","ipdsId":"IP-081673","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":352921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc31c","contributors":{"authors":[{"text":"Thompson, Sarah J. 0000-0002-5733-8198 sjthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-5733-8198","contributorId":5434,"corporation":false,"usgs":true,"family":"Thompson","given":"Sarah","email":"sjthompson@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":731993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":731995,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195391,"text":"70195391 - 2017 - Northern hemisphere jet stream positions indices as diagnostic tools for climate and ecosystem dynamics","interactions":[],"lastModifiedDate":"2018-02-13T12:46:17","indexId":"70195391","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Northern hemisphere jet stream positions indices as diagnostic tools for climate and ecosystem dynamics","docAbstract":"The latitudinal position of the Northern Hemisphere jet stream (NHJ) modulates the occurrence and frequency of extreme weather events. Precipitation anomalies in particular are associated with NHJ variability; the resulting floods and droughts can have considerable societal and economic impacts. This study develops a new climatology of the 300-hPa NHJ using a bottom-up approach based on seasonally explicit latitudinal NHJ positions. Four seasons with coherent NHJ patterns were identified (January–February, April–May, July–August, and October–November), along with 32 longitudinal sectors where the seasonal NHJ shows strong spatial coherence. These 32 longitudinal sectors were then used as NHJ position indices to examine the influence of seasonal NHJ position on the geographical distribution of NH precipitation and temperature variability and their link to atmospheric circulation pattern. The analyses show that the NHJ indices are related to broad-scale patterns in temperature and precipitation variability, in terrestrial vegetation productivity and spring phenology, and can be used as diagnostic/prognostic tools to link ecosystem and socioeconomic dynamics to upper-level atmospheric patterns.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/EI-D-16-0023.1","usgsCitation":"Belmecheri, S., Babst, F., Hudson, A.R., Betancourt, J.L., and Trouet, V., 2017, Northern hemisphere jet stream positions indices as diagnostic tools for climate and ecosystem dynamics: Earth Interactions, v. 21, p. 1-23, https://doi.org/10.1175/EI-D-16-0023.1.","productDescription":"Paper no. 8; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-084452","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469283,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-16-0023.1","text":"Publisher Index Page"},{"id":351528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-15","publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc33b","contributors":{"authors":[{"text":"Belmecheri, Soumaya 0000-0003-1258-2741","orcid":"https://orcid.org/0000-0003-1258-2741","contributorId":202418,"corporation":false,"usgs":false,"family":"Belmecheri","given":"Soumaya","email":"","affiliations":[{"id":36425,"text":"Laboratory of Tree Ring Research, University of Arizona. Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":728369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Babst, Flurin","contributorId":202419,"corporation":false,"usgs":false,"family":"Babst","given":"Flurin","email":"","affiliations":[{"id":36426,"text":"Laboratory of Tree Ring Research, University of Arizona. Tucson, Arizona, USA, Dendroclimatology Group, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland, W. Szafer Institute of Botany, Polish Academy of Sciences, Krakow, Poland","active":true,"usgs":false}],"preferred":false,"id":728370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Amy R.","contributorId":202420,"corporation":false,"usgs":false,"family":"Hudson","given":"Amy","email":"","middleInitial":"R.","affiliations":[{"id":36427,"text":"Laboratory of Tree Ring Research, University of Arizona. Tucson, Arizona, USA, School of Natural Resources and the Environment, University of Arizona. Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":728371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":728368,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trouet, Valerie","contributorId":197082,"corporation":false,"usgs":false,"family":"Trouet","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":728372,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194758,"text":"70194758 - 2017 - Forecasting consequences of changing sea ice availability for Pacific walruses","interactions":[],"lastModifiedDate":"2018-08-20T17:40:05","indexId":"70194758","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting consequences of changing sea ice availability for Pacific walruses","docAbstract":"The accelerating rate of anthropogenic alteration and disturbance of environments has increased the need for forecasting effects of environmental change on fish and wildlife populations. Models linking projections of environmental change with behavioral responses and bioenergetic effects can provide a basis for these forecasts. There is particular interest in forecasting effects of projected reductions in sea ice availability on Pacific walruses (Odobenus rosmarus divergens). Declining extent of summer sea ice in the Chukchi Sea has caused Pacific walruses to increase use of coastal haulouts and decrease use of more productive offshore feeding areas. Such climate-induced changes in distribution and behavior could ultimately affect the status of the population. We developed behavioral models to relate changes in sea ice availability to adult female walrus movements and activity levels, and adapted previously developed bioenergetics models to relate those activity levels to energy requirements and the ability to meet those requirements. We then linked these models to general circulation model projections of future ice availability to forecast autumn body condition for female walruses during mid- and late-century time periods. Our results suggest that as sea ice becomes less available in the Chukchi Sea, female walruses will spend more time in the southwestern region of that sea, less time resting, and less time foraging. Median forecasted autumn body masses were 7–12% lower in future scenarios than during recent times, but posterior distributions broadly overlapped and median forecasted seasonal mass losses (15–34%) were comparable to seasonal mass losses routinely experienced by other pinnipeds. These seasonal reductions in body condition would be unlikely to result in demographic effects, but if walruses were unable to rebuild endogenous reserves while wintering in the Bering Sea, cumulative effects could have implications for reproduction and survival, ultimately affecting the status of the Pacific walrus population. Our approach provides a general framework for forecasting consequences of the broad range of environmental changes and anthropogenic disturbances that may affect bioenergetics through behavioral responses or changes in prey availability.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2014","usgsCitation":"Udevitz, M.S., Jay, C.V., Taylor, R.L., Fischbach, A., Beatty, W.S., and Noren, S.R., 2017, Forecasting consequences of changing sea ice availability for Pacific walruses: Ecosphere, v. 8, no. 11, e02014, https://doi.org/10.1002/ecs2.2014.","productDescription":"e02014","ipdsId":"IP-088005","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469275,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2014","text":"Publisher Index Page"},{"id":438140,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XG9Q2T","text":"USGS data release","linkHelpText":"Pacific Walrus Behavior Data and Associated Chukchi Sea Ice Observations and Projections for use with Bioenergetics Models to Forecast Walrus Body Condition"},{"id":350025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -189.1845703125,\n 65.56754970214311\n ],\n [\n -156.3134765625,\n 65.56754970214311\n ],\n [\n -156.3134765625,\n 74.17607298699065\n ],\n [\n -189.1845703125,\n 74.17607298699065\n ],\n [\n -189.1845703125,\n 65.56754970214311\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-29","publicationStatus":"PW","scienceBaseUri":"5a60faf6e4b06e28e9c22a12","contributors":{"authors":[{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":725121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":725124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":725125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":725126,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":725122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noren, Shawn R.","contributorId":127697,"corporation":false,"usgs":false,"family":"Noren","given":"Shawn","email":"","middleInitial":"R.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":725123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196869,"text":"70196869 - 2017 - Conservation status assessment of an endangered insular raptor: the Sharp-shinned Hawk in Puerto Rico","interactions":[],"lastModifiedDate":"2018-05-08T13:26:23","indexId":"70196869","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Conservation status assessment of an endangered insular raptor: the Sharp-shinned Hawk in Puerto Rico","docAbstract":"Sharp‐shinned Hawks (Accipiter striatus) are forest raptors that are widely distributed in the Americas. A subspecies endemic to Puerto Rico (A. s. venator) is listed as endangered and restricted to mature and old secondary montane forests and shade coffee plantations. However, recent information about the population status and distribution of Puerto Rican Sharp‐shinned Hawks is lacking. We developed a spatial geographic distribution model for Sharp‐shinned Hawks in Puerto Rico from 33 locations collected during four breeding seasons (2013–2016) using biologically relevant landscape variables (aspect, canopy closure, elevation, rainfall, slope, and terrain roughness). Elevation accounted for 89.8% of the model fit and predicted that the greatest probability of occurrence of Sharp‐shinned Hawks in Puerto Rico (> 60%) was at elevations above 900 m. Based on our model, an estimated 56.1 km2 of habitat exists in Puerto Rico with a high probability of occurrence. This total represents ~0.6% of the island's area. Public lands included 43.8% of habitat with high probability of occurrence (24.6 km2), 96% of which was located within four protected areas. Our results suggest that Sharp‐shinned Hawks are rare in Puerto Rico and restricted to the higher elevations of the Cordillera Central. Additional research is needed to identify and address ecological limiting factors, and recovery actions are needed to avoid the extinction of this endemic island raptor.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12228","usgsCitation":"Gallardo, J.C., and Vilella, F., 2017, Conservation status assessment of an endangered insular raptor: the Sharp-shinned Hawk in Puerto Rico: Journal of Field Ornithology, v. 88, no. 4, p. 349-361, https://doi.org/10.1111/jofo.12228.","productDescription":"13 p.","startPage":"349","endPage":"361","ipdsId":"IP-090401","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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model","interactions":[],"lastModifiedDate":"2017-12-15T13:29:05","indexId":"70194119","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5573,"text":"Interagency Ecological Program Technical Report","active":true,"publicationSubtype":{"id":4}},"seriesNumber":"91","title":"Food web conceptual model","docAbstract":"This chapter describes a general model of food webs within tidal wetlands and represents how physical features of the wetland affect the structure and function of the food web. This conceptual model focuses on how the food web provides support for (or may reduce support for) threatened fish species. This model is part of a suite of conceptual models designed to guide monitoring of restoration sites throughout the San Francisco Estuary (SFE), but particularly within the Sacramento-San Joaquin Delta (Delta) and Suisun Marsh. The conceptual models have been developed based on the Delta Regional Ecosystem Restoration Implementation Plan (DRERIP) models, and are designed to aid in the identification and evaluation of monitoring metrics for tidal wetland restoration projects.
Many tidal restoration sites in the Delta are being constructed to comply with environmental regulatory requirements associated with the operation of the Central Valley Project and State Water Project. These include the Biological Opinions for Delta Smelt (Hypomesus transpacificus) and salmonids (U.S. Fish and Wildlife Service 2008; National Marine Fisheries Service 2009), and the Incidental Take Permit for Longfin Smelt (Spirinchus thaleichthyes) (California Department of Fish and Wildlife 2009).
These regulatory requirements are based on the hypothesis that the decline of listed fish species is due in part to a decline in productivity of the food web (phytoplankton and zooplankton in particular) or alterations in the food web such that production is consumed by other species in the Estuary (Sommer et al. 2007; Baxter et al. 2010; Brown et al. 2016a). Intertidal wetlands and shallow subtidal habitat can be highly productive, so restoring areas of tidal wetlands may result in a net increase in productivity that will provide food web support for these fish species. However, other factors such as invasive bivalves that reduce phytoplankton and zooplankton biomass and invasive predatory fishes that may compete with or prey upon listed fishes can limit the utility of tidal wetlands for food web support (Lucas and Thompson 2012; Herbold et al. 2014).
This model utilizes information from the previous DRERIP models for Delta food webs (Durand 2008) and tidal wetlands (Kneib et al. 2008), an updated DRERIP model (Durand 2015), and the State of BayDelta Science 2016 review of recent Delta food web literature (Brown et al. 2016a).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of tidal wetland restoration on fish: A suite of conceptual models","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"California Department of Water Resources","usgsCitation":"Hartman, R., Brown, L.R., and Hobbs, J., 2017, Food web conceptual model: Interagency Ecological Program Technical Report 91, 38 p.","productDescription":"38 p.","startPage":"143","endPage":"180","ipdsId":"IP-082772","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348890,"type":{"id":11,"text":"Document"},"url":"https://www.water.ca.gov/iep/docs/tech_rpts/TR91.Wetland_CM_2Nov2017.pdf"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf8e4b06e28e9c22a45","contributors":{"authors":[{"text":"Hartman, Rosemary","contributorId":200388,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":722155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobbs, Jim","contributorId":200389,"corporation":false,"usgs":false,"family":"Hobbs","given":"Jim","email":"","affiliations":[],"preferred":false,"id":722156,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196963,"text":"70196963 - 2017 - Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","interactions":[],"lastModifiedDate":"2018-05-15T17:03:36","indexId":"70196963","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","title":"Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data","docAbstract":"Despite nearly a century of exploitation and scientific study, predicting growth and mortality rates of the eastern oyster (Crassostrea virginica) as a means to inform local harvest and management activities remains difficult. Ensuring that models reflect local population responses to varying salinity and temperature combinations requires locally appropriate models. Using long-term (1988 to 2015) monitoring data from Louisiana's public oyster reefs, we develop regionally specific models of temperature- and salinity-driven mortality (sack oysters only) and growth for spat (<25 mm), seed (25–75 mm), and sack (>75 mm) oyster size classes. The results demonstrate that the optimal combination of temperature and salinity where Louisiana oysters experience reduced mortality and fast growth rates is skewed toward lower salinities and higher water temperatures than previous models have suggested. Outside of that optimal range, oysters are commonly exposed to combinations of temperature and salinity that are correlated with high mortality and reduced growth. How these combinations affect growth, and to a lesser degree mortality, appears to be size class dependent. Given current climate predictions for the region and ongoing large-scale restoration activities in coastal Louisiana, the growth and mortality models are a critical step toward ensuring sustainable oyster reefs for long-term harvest and continued delivery of the ecological services in a changing environment.
","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.036.0318","collaboration":"National Fish and Wildlife Foundation, Louisiana,Department of Wildlife and Fisheries, Louisiana State University","usgsCitation":"Lowe, M.R., Sehlinger, T., Soniat, T.M., and LaPeyre, M.K., 2017, Interactive effects of water temperature and salinity on growth and mortality of eastern oysters, Crassostrea virginica: A meta-analysis using 40 years of monitoring data: Journal of Shellfish Research, v. 36, no. 3, p. 683-697, https://doi.org/10.2983/035.036.0318.","productDescription":"15 p.","startPage":"683","endPage":"697","ipdsId":"IP-088282","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94,\n 29\n ],\n [\n -89,\n 29\n ],\n [\n -89,\n 30.5\n ],\n [\n -94,\n 30.5\n ],\n [\n -94,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2fa","contributors":{"authors":[{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":735465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sehlinger, Troy","contributorId":204922,"corporation":false,"usgs":false,"family":"Sehlinger","given":"Troy","email":"","affiliations":[],"preferred":false,"id":735466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soniat, Thomas M.","contributorId":11109,"corporation":false,"usgs":true,"family":"Soniat","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":735149,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196136,"text":"70196136 - 2017 - Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","interactions":[],"lastModifiedDate":"2018-03-21T13:25:45","indexId":"70196136","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","title":"Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","docAbstract":"Organic sulfur compounds are ubiquitous in natural oil and gas fields and moderate-low temperature sulfide ore deposits. Previous studies have shown that organic sulfur compounds are important in enhancing the rates of thermochemical sulfate reduction (TSR) reactions, but the details of these reaction mechanisms remain unclear. In order to assess the extent of sulfate reduction in the presence of labile sulfur species at temperature conditions near to those where TSR occurs in nature, we conducted a series of experiments using the fused silica capillary capsule (FCSS) method. The tested systems containing labile sulfur species are MgSO4 + 1-pentanethiol (C5H11SH) + 1-octene (C8H16), MgSO4 + 1-octene (C8H16), MgSO4 + 1-pentanethiol (C5H11SH), 1-pentanethiol (C5H11SH)+H2O, and MgSO4 + 1-pentanethiol (C5H11SH) + ZnBr2 systems. Our results show that: (1) intermediate oxidized carbon species (ethanol and acetic acid) are formed during TSR simulation experiments when 1-pentanethiol is present; (2) in the presence of ZnBr2, 1-pentanethiol can be oxidized by sulfate to CO2 at 200 °C, which is within the temperature range observed in natural TSR; and (3) the precipitation of sulfide minerals may significantly promote the rate of TSR, indicating that the rates of in situ TSR reactions in ore deposits could be much faster than previously thought. This may be important for understanding the possibility of in situ TSR as a mechanism for the precipitation of metal sulfides in some ore deposits. These findings provide important experimental evidence for understanding the role of organic sulfur compounds in TSR reactions and the pathway of TSR reactions initiated by organic sulfur compounds under natural conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2017.11.003","usgsCitation":"Yuan, S., Ellis, G.S., Chou, I., and Burruss, R., 2017, Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits: Ore Geology Reviews, v. 91, p. 57-65, https://doi.org/10.1016/j.oregeorev.2017.11.003.","productDescription":"9 p.","startPage":"57","endPage":"65","ipdsId":"IP-059524","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":352700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc32f","contributors":{"authors":[{"text":"Yuan, Shunda","contributorId":203441,"corporation":false,"usgs":false,"family":"Yuan","given":"Shunda","email":"","affiliations":[{"id":36622,"text":"Institute of Mineral Resources, Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":731495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chou, I-Ming 0000-0001-5233-6479 imchou@usgs.gov","orcid":"https://orcid.org/0000-0001-5233-6479","contributorId":882,"corporation":false,"usgs":true,"family":"Chou","given":"I-Ming","email":"imchou@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burruss, Robert 0000-0001-6827-804X burruss@usgs.gov","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":146833,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"burruss@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197046,"text":"70197046 - 2017 - An intertebrate ecosystem engineer likely covered under the umbrella of sage-grouse conservation","interactions":[],"lastModifiedDate":"2018-05-15T16:24:59","indexId":"70197046","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"An intertebrate ecosystem engineer likely covered under the umbrella of sage-grouse conservation","docAbstract":"Conservation practitioners often rely on areas designed to protect species of greatest conservation priority to also conserve co-occurring species (i.e., the umbrella species concept). The extent to which vertebrate species may serve as suitable umbrellas for invertebrate species, however, has rarely been explored. Sage-grouse (Centrocercus spp.) have high conservation priority throughout much of the rangelands of western North America and are considered an umbrella species through which the conservation of entire rangeland ecosystems can be accomplished. Harvester ants are ecosystem engineers and play important roles in the maintenance and function of rangeland ecosystems. We compared indices of the abundance of western harvester ants (Pogonomyrmex occidentalis) and Greater Sage-Grouse (Centrocercus urophasianus) at 72 sites in central Wyoming, USA, in 2012. The abundance of harvester ant mounds was best predicted by a regression model that included a combination of local habitat characteristics and the abundance of sage-grouse. When controlling for habitat-related factors, areas with higher abundances of sage-grouse pellets (an index of sage-grouse abundance and/or habitat use) had higher abundances of ant mounds than areas with lower abundances of sage-grouse pellets. The causal mechanism underlying this positive relationship between sage-grouse and ant mound abundance at the fine scale could be indirect (e.g., both species prefer similar environmental conditions) or direct (e.g., sage-grouse prefer areas with a high abundance of ant mounds because ants are an important prey item during certain life stages). We observed no relationship between a broad-scale index of breeding sage-grouse density and the abundance of ant mounds. We suspect that consideration of the nonbreeding habitat of sage-grouse and finer-scale measures of sagegrouse abundance are critical to the utility of sage-grouse as an umbrella species for the conservation of harvester ants and their important role in rangeland ecosystems.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.077.0406","usgsCitation":"Carlisle, J.D., Stewart, D., and Chalfoun, A.D., 2017, An intertebrate ecosystem engineer likely covered under the umbrella of sage-grouse conservation: Western North American Naturalist, v. 77, no. 4, p. 450-463, https://doi.org/10.3398/064.077.0406.","productDescription":"14 p.","startPage":"450","endPage":"463","ipdsId":"IP-078783","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469269,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol77/iss4/5","text":"External Repository"},{"id":354196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee79ce4b0da30c1bfc2f6","contributors":{"authors":[{"text":"Carlisle, Jason D.","contributorId":204646,"corporation":false,"usgs":false,"family":"Carlisle","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":735450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735363,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197056,"text":"70197056 - 2017 - Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length","interactions":[],"lastModifiedDate":"2018-05-17T14:21:53","indexId":"70197056","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length","docAbstract":"We used dorsal spines and otoliths from 735 Walleye Sander vitreus collected from 35 Wisconsin water bodies to evaluate whether 1) otolith and dorsal spine cross sections provided age estimates similar to simpler methods of preparation (e.g., whole otoliths and dorsal spines, cracked otoliths); and 2) between-reader precision and differences between spine and otolith ages varied in relation to total length (TL), sex, and growth rate. Ages estimated from structures prepared using simpler techniques were generally similar to ages estimated using thin sections of dorsal spines and otoliths, suggesting that, in some instances, much of the additional processing time and specialized equipment associated with thin sectioning could be avoided. Overall, between-reader precision was higher for sectioned otoliths (mean coefficient of variation [CV] = 3.28%; standard error [SE] = 0.33%) than for sectioned dorsal spines (mean CV = 9.20%; SE = 0.56%). When using sectioned otoliths for age assignment, between-reader precision did not vary between sexes or growth categories (i.e., fast, moderate, slow), but between-reader precision was higher for females than males when using sectioned dorsal spines. Dorsal spines were generally effective at replicating otolith ages for male Walleye <450 mm TL and female Walleye <600 mm TL, suggesting that dorsal spines can be used to estimate ages for male Walleye <450 mm TL and female Walleye <600 mm TL. If sex is unknown, we suggest dorsal spines be used to estimate ages for Walleye <450 mm TL, but that otoliths be used for fish >450 mm TL. Our results provide useful guidance on structure and preparation technique selection for Walleye age estimation, thereby allowing biologists to develop sampling guidelines that could be implemented using information that is always (TL) or often (sex) available at the time of fish collection.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/052017-JFWM-038","usgsCitation":"Dembkowski, D., Isermann, D.A., and Koenigs, R.P., 2017, Walleye age estimation using otoliths and dorsal spines: Preparation techniques and sampling guidelines based on sex and total length: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 474-486, https://doi.org/10.3996/052017-JFWM-038.","productDescription":"13 p.","startPage":"474","endPage":"486","ipdsId":"IP-082128","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487229,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052017-jfwm-038","text":"Publisher Index Page"},{"id":354272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 IEEE International Conference on Data Mining (ICDM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"IEEE","doi":"10.1109/ICDM.2017.154","usgsCitation":"Yuan, S., Zhou, J., Tan, P., Fergus, E., Wagner, T., and Sorrano, P., 2017, Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data, in 2017 IEEE International Conference on Data Mining (ICDM), https://doi.org/10.1109/ICDM.2017.154.","ipdsId":"IP-084708","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1ba4","contributors":{"authors":[{"text":"Yuan, Shuai","contributorId":204925,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Jiayu","contributorId":204926,"corporation":false,"usgs":false,"family":"Zhou","given":"Jiayu","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tan, Pang-Ning","contributorId":204927,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fergus, Emi","contributorId":204928,"corporation":false,"usgs":false,"family":"Fergus","given":"Emi","email":"","affiliations":[{"id":37008,"text":"National Research Council","active":true,"usgs":false}],"preferred":false,"id":735485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sorrano, Patricia","contributorId":204929,"corporation":false,"usgs":false,"family":"Sorrano","given":"Patricia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":735486,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195381,"text":"70195381 - 2017 - Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests","interactions":[],"lastModifiedDate":"2020-09-01T14:26:56.11934","indexId":"70195381","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests","docAbstract":"For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.
","language":"English","publisher":"EGU","doi":"10.5194/bg-14-4663-2017","usgsCitation":"Clark, D., Asao, S., Fisher, R.A., Reed, S.C., Reich, P.B., Ryan, M.G., Wood, T.E., and Yang, X., 2017, Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests: Biogeosciences, v. 14, p. 4663-4690, https://doi.org/10.5194/bg-14-4663-2017.","productDescription":"28 p.","startPage":"4663","endPage":"4690","ipdsId":"IP-086986","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469257,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-14-4663-2017","text":"Publisher Index Page"},{"id":351527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc33d","contributors":{"authors":[{"text":"Clark, Deborah A.","contributorId":202368,"corporation":false,"usgs":false,"family":"Clark","given":"Deborah A.","affiliations":[{"id":36397,"text":"Department of Biology, University of Missouri-St. Louis","active":true,"usgs":false}],"preferred":false,"id":728279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asao, Shinichi","contributorId":202369,"corporation":false,"usgs":false,"family":"Asao","given":"Shinichi","email":"","affiliations":[{"id":7230,"text":"Natural Resource Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":728280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Rosie A.","contributorId":147090,"corporation":false,"usgs":false,"family":"Fisher","given":"Rosie","email":"","middleInitial":"A.","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":728281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":728278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reich, Peter B.","contributorId":202370,"corporation":false,"usgs":false,"family":"Reich","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":36398,"text":"Department of Forest Resources, University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":728282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryan, Michael G.","contributorId":202371,"corporation":false,"usgs":false,"family":"Ryan","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":33176,"text":"Rocky Mountain Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":728283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":728284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yang, Xiaojuan","contributorId":146256,"corporation":false,"usgs":false,"family":"Yang","given":"Xiaojuan","email":"","affiliations":[{"id":16649,"text":"Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN 37831-6335, USA","active":true,"usgs":false}],"preferred":false,"id":728285,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195325,"text":"70195325 - 2017 - A statistical method to predict flow permanence in dryland streams from time series of stream temperature","interactions":[],"lastModifiedDate":"2018-02-08T13:51:52","indexId":"70195325","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A statistical method to predict flow permanence in dryland streams from time series of stream temperature","docAbstract":"Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
","language":"English","publisher":"MDPI","doi":"10.3390/w9120946","usgsCitation":"Arismendi, I., Dunham, J.B., Heck, M., Schultz, L., and Hockman-Wert, D., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 1-13, https://doi.org/10.3390/w9120946.","productDescription":"Article 946; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087892","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469281,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9120946","text":"Publisher Index Page"},{"id":438137,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ0ZW2","text":"USGS data release","linkHelpText":"Stream temperature and drying data from Willow/Whitehorse watersheds, southeast Oregon, 2014-16, and Willow/Rock/Frazer watersheds, northern Nevada, 2015-2016"},{"id":351364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 42\n ],\n [\n -118,\n 42.33\n ],\n [\n -118.33,\n 42.33\n ],\n [\n -118.33,\n 42\n ],\n [\n -118,\n 42\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.33,\n 41.1667\n ],\n [\n -116.8333,\n 41.1667\n ],\n [\n -116.8333,\n 41.4167\n ],\n [\n -116.33,\n 41.4167\n ],\n [\n -116.33,\n 41.1667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-05","publicationStatus":"PW","scienceBaseUri":"5a7d6ffee4b00f54eb2441c0","contributors":{"authors":[{"text":"Arismendi, Ivan 0000-0002-8774-9350","orcid":"https://orcid.org/0000-0002-8774-9350","contributorId":202207,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":727859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Luke 0000-0002-6751-4626 lschultz@usgs.gov","orcid":"https://orcid.org/0000-0002-6751-4626","contributorId":193171,"corporation":false,"usgs":true,"family":"Schultz","given":"Luke","email":"lschultz@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@usgs.gov","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":727862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197204,"text":"70197204 - 2017 - Genomics of Arctic cod","interactions":[],"lastModifiedDate":"2018-06-12T11:15:27","indexId":"70197204","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"BOEM 2017-066","title":"Genomics of Arctic cod","docAbstract":"The Arctic cod (Boreogadus saida) is an abundant marine fish that plays a vital role in the marine food web. To better understand the population genetic structure and the role of natural selection acting on the maternally-inherited mitochondrial genome (mitogenome), a molecule often associated with adaptations to temperature, we analyzed genetic data collected from 11 biparentally-inherited nuclear microsatellite DNA loci and nucleotide sequence data from from the mitochondrial DNA (mtDNA) cytochrome b (cytb) gene and, for a subset of individuals, the entire mitogenome. In addition, due to potential of species misidentification with morphologically similar Polar cod (Arctogadus glacialis), we used ddRAD-Seq data to determine the level of divergence between species and identify species-specific markers.
Based on the findings presented here, Arctic cod across the Pacific Arctic (Bering, Chukchi, and Beaufort Seas) comprise a single panmictic population with high genetic diversity compared to other gadids. High genetic diversity was indicated across all 13 protein-coding genes in the mitogenome. In addition, we found moderate levels of genetic diversity in the nuclear microsatellite loci, with highest diversity found in the Chukchi Sea. Our analyses of markers from both marker classes (nuclear microsatellite fragment data and mtDNA cytb sequence data) failed to uncover a signal of microgeographic genetic structure within Arctic cod across the three regions, within the Alaskan Beaufort Sea, or between near-shore or offshore habitats. Further, data from a subset of mitogenomes revealed no genetic differentiation between Bering, Chukchi, and Beaufort seas populations for Arctic cod, Saffron cod (Eleginus gracilis), or Walleye pollock (Gadus chalcogrammus). However, we uncovered significant differences in the distribution of microsatellite alleles between the southern Chukchi and central and eastern Beaufort Sea samples of Arctic cod. Finally, using ddRAD-Seq data, we identified species-specific markers and in conjunction with mitogenome data, identified an Arctic cod x Polar cod hybrid in western Canadian Beaufort Sea.
Overall, the lack of genetic structure among Arctic cod within the Bering, Chukchi and Beaufort seas of Alaska is concordant with the absence of geographic barriers to dispersal and typical among marine fishes. Arctic cod may exhibit a genetic pattern of isolation-by-distance, whereby populations in closer geographic proximity are more genetically similar than more distant populations. As this signal is only found between our two fartherest localities, data from populations elsewhere in the species’ global range are needed to determine if this is a general characteristic. Further, tests for selection suggested a limited role for natural selection acting on the mitochondrial genome of Arctic cod, but do not exclude the possibility of selection on genes involved in nuclear-mitogenome interactions. Unlike previous genetic assessment of Arctic cod sampled from the Chukchi Sea, the high levels of genetic diversity found in Arctic cod assayed in this study, across regions, suggests that the species in the Beaufort and Chukchi seas does not suffer from low levels of genetic variation, at least at neutral genetic markers. The large census size of Arctic cod may allow this species to retain high levels of genetic diversity. In addition, we discovered the presence of hybridization between Arctic and Polar cod (although low in frequency). Hybridization is expected to occur when environmental changes modify species distributions that result in contact between species that were previously separated. In such cases, hybridization may be an evolutionary mechanism that promotes an increase in genetic diversity that may provide species occupying changing environments with locally-adapted genotypes and, therefore, phenotypes. Natural selection can only act on the standing genetic variation present within a population. Therefore, given its higher levels of genetic diversity in combination with a large population size, Arctic cod may be resilient to current and future environmental change, as high genetic diversity is expected to increase opportunities for positive selection to act on genetic variants beneficial in different environments, regardless of the source of that genetic variation.
","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Wilson, R.E., Sage, G.K., Sonsthagen, S.A., Gravley, M.C., Menning, D.M., and Talbot, S.L., 2017, Genomics of Arctic cod: OCS Study BOEM 2017-066, vi, 81 p.","productDescription":"vi, 81 p.","numberOfPages":"92","ipdsId":"IP-091280","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":354936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354385,"type":{"id":11,"text":"Document"},"url":"https://www.boem.gov/BOEM-2017-066-Genomics-of-Arctic-Cod/"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e62fe4b060350a15d262","contributors":{"authors":[{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":736174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":736175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gravley, Megan C. 0000-0002-4947-0236 mgravley@usgs.gov","orcid":"https://orcid.org/0000-0002-4947-0236","contributorId":202812,"corporation":false,"usgs":true,"family":"Gravley","given":"Megan","email":"mgravley@usgs.gov","middleInitial":"C.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":736176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":736177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736178,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197207,"text":"70197207 - 2017 - Translating statistical species-habitat models to interactive decision support tools","interactions":[],"lastModifiedDate":"2018-05-22T16:40:42","indexId":"70197207","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Translating statistical species-habitat models to interactive decision support tools","docAbstract":"Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0188244","usgsCitation":"Wszola, L.S., Simonsen, V.L., Stuber, E.F., Gillespie, C.R., Messinger, L.N., Decker, K.L., Lusk, J.J., Jorgensen, C.F., Bishop, A.A., and Fontaine, J.J., 2017, Translating statistical species-habitat models to interactive decision support tools: PLoS ONE, v. 12, no. 12, p. 1-13, https://doi.org/10.1371/journal.pone.0188244.","productDescription":"e0188244; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087203","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0188244","text":"Publisher Index Page"},{"id":354401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1ba2","contributors":{"authors":[{"text":"Wszola, Lyndsie S.","contributorId":205135,"corporation":false,"usgs":false,"family":"Wszola","given":"Lyndsie","email":"","middleInitial":"S.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonsen, Victoria L.","contributorId":205136,"corporation":false,"usgs":false,"family":"Simonsen","given":"Victoria","email":"","middleInitial":"L.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuber, Erica F.","contributorId":198581,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":736186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillespie, Caitlyn R.","contributorId":195835,"corporation":false,"usgs":false,"family":"Gillespie","given":"Caitlyn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":736187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Messinger, Lindsey N.","contributorId":205139,"corporation":false,"usgs":false,"family":"Messinger","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":736188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Decker, Karie L.","contributorId":51094,"corporation":false,"usgs":true,"family":"Decker","given":"Karie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":736189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lusk, Jeffrey J.","contributorId":198584,"corporation":false,"usgs":false,"family":"Lusk","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":736190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jorgensen, Christopher F.","contributorId":87444,"corporation":false,"usgs":true,"family":"Jorgensen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":736191,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bishop, Andrew A.","contributorId":93323,"corporation":false,"usgs":true,"family":"Bishop","given":"Andrew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":736192,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":736183,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197309,"text":"70197309 - 2017 - Importance of fishing as a segmentation variable in the application of a social worlds model","interactions":[],"lastModifiedDate":"2018-05-29T15:58:16","indexId":"70197309","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3176,"text":"Proceedings of the South Dakota Academy of Science","active":true,"publicationSubtype":{"id":10}},"title":"Importance of fishing as a segmentation variable in the application of a social worlds model","docAbstract":"Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.
","language":"English","publisher":"South Dakota Academy of Science","usgsCitation":"Gigliotti, L.M., and Chase, L., 2017, Importance of fishing as a segmentation variable in the application of a social worlds model: Proceedings of the South Dakota Academy of Science, v. 96, p. 58-76.","productDescription":"19 p.","startPage":"58","endPage":"76","ipdsId":"IP-054039","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354528,"type":{"id":15,"text":"Index Page"},"url":"https://sdaos.org/?s=Year%3A+2017"}],"volume":"96","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1ba0","contributors":{"authors":[{"text":"Gigliotti, Larry M. 0000-0002-1693-5113 lgigliotti@usgs.gov","orcid":"https://orcid.org/0000-0002-1693-5113","contributorId":3906,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Larry","email":"lgigliotti@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":736611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Loren","contributorId":205235,"corporation":false,"usgs":false,"family":"Chase","given":"Loren","email":"","affiliations":[{"id":37061,"text":"Arizona Fish and Game Department","active":true,"usgs":false}],"preferred":false,"id":736612,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195067,"text":"70195067 - 2017 - Using carbon dioxide in fisheries and aquatic invasive species management","interactions":[],"lastModifiedDate":"2018-02-28T14:27:19","indexId":"70195067","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Using carbon dioxide in fisheries and aquatic invasive species management","docAbstract":"To restore native fish populations, fisheries programs often depend on active removal of aquatic invasive species. Chemical removal can be an effective method of eliminating aquatic invasive species, but chemicals can induce mortality in nontarget organisms and persist in the environment. Carbon dioxide (CO2) is an emerging alternative to traditional chemical control agents because it has been demonstrated to be toxic to fish, but is naturally occurring and readily neutralized. In addition, CO2 is a commercially available gas, is highly soluble, and has high absorption efficiency. When these characteristics are paired with advances in modern, large-scale gas delivery technologies, opportunities to use CO2 in natural or artificial (e.g., canals) waters to manage fish become increasingly feasible. Our objective is to describe the history of CO2 use in fisheries and outline potential future applications of CO2 to suppress and manipulate aquatic species in field and aquaculture settings.
","language":"English","publisher":"Wiley","doi":"10.1080/03632415.2017.1383903","usgsCitation":"Treanor, H.B., Ray, A.M., Layhee, M., Watten, B.J., Gross, J.A., Gresswell, R.E., and Webb, M.A., 2017, Using carbon dioxide in fisheries and aquatic invasive species management: Fisheries, v. 42, no. 12, p. 621-628, https://doi.org/10.1080/03632415.2017.1383903.","productDescription":"8 p.","startPage":"621","endPage":"628","ipdsId":"IP-073368","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":438138,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U3X5XW","text":"USGS data release","linkHelpText":"Carbon dioxide-induced mortality of four species of North American fishes data"},{"id":351342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-12","publicationStatus":"PW","scienceBaseUri":"5a7d7001e4b00f54eb2441e9","contributors":{"authors":[{"text":"Treanor, Hilary B.","contributorId":200249,"corporation":false,"usgs":false,"family":"Treanor","given":"Hilary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":726785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":726786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Layhee, Megan J.","contributorId":201692,"corporation":false,"usgs":false,"family":"Layhee","given":"Megan J.","affiliations":[{"id":36231,"text":"Central Sierra Environmental Resource Center","active":true,"usgs":false}],"preferred":false,"id":726787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watten, Barnaby J. 0000-0002-2227-8623 bwatten@usgs.gov","orcid":"https://orcid.org/0000-0002-2227-8623","contributorId":2002,"corporation":false,"usgs":true,"family":"Watten","given":"Barnaby","email":"bwatten@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":726788,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gross, Jason A.","contributorId":201693,"corporation":false,"usgs":false,"family":"Gross","given":"Jason","email":"","middleInitial":"A.","affiliations":[{"id":27848,"text":"Smith-Root, Inc.","active":true,"usgs":false}],"preferred":false,"id":726789,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":147914,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":726784,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webb, Molly A. 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Here we try to analyze primary features of this type of event by using dynamic rupture simulations based on a multifault interface and later compare our results with space geodetic models. Our results show that starting from homogeneous prestress conditions, slip heterogeneity can be achieved as a result of variable dip angle along strike and the modulation imposed by step over segments. We also considered effects from a topographic free surface and find that although this does not produce significant first-order effects for this earthquake, even a low topographic dome such as the Cucapah range can affect the rupture front pattern and fault slip rate. Finally, we inverted available interferometric synthetic aperture radar data, using the same geometry as the dynamic rupture model, and retrieved the space geodetic slip distribution that serves to constrain the dynamic rupture models. The one to one comparison of the final fault slip pattern generated with dynamic rupture models and the space geodetic inversion show good agreement. Our results lead us to the following conclusion: in a possible multifault rupture scenario, and if we have first-order geometry constraints, dynamic rupture models can be very efficient in predicting large-scale slip heterogeneities that are important for the correct assessment of seismic hazard and the magnitude of future events. Our work contributes to understanding the complex nature of multifault systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014294","usgsCitation":"Kyriakopoulos, C., Oglesby, D.D., Funning, G.J., and Ryan, K., 2017, Dynamic rupture modeling of the M7.2 2010 El Mayor-Cucapah earthquake: Comparison with a geodetic model: Journal of Geophysical Research B: Solid Earth, v. 122, no. 12, p. 10263-10279, https://doi.org/10.1002/2017JB014294.","productDescription":"17 p.","startPage":"10263","endPage":"10279","ipdsId":"IP-085833","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb014294","text":"Publisher Index Page"},{"id":351348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.5,\n 33\n ],\n [\n -114.5,\n 33\n ],\n [\n -114.5,\n 31.5\n ],\n [\n -116.5,\n 31.5\n ],\n [\n -116.5,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-19","publicationStatus":"PW","scienceBaseUri":"5a7d7000e4b00f54eb2441db","contributors":{"authors":[{"text":"Kyriakopoulos, Christos","contributorId":201722,"corporation":false,"usgs":false,"family":"Kyriakopoulos","given":"Christos","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":726852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oglesby, David D.","contributorId":201723,"corporation":false,"usgs":false,"family":"Oglesby","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":726853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funning, Gareth J. 0000-0002-8247-0545","orcid":"https://orcid.org/0000-0002-8247-0545","contributorId":172418,"corporation":false,"usgs":false,"family":"Funning","given":"Gareth","email":"","middleInitial":"J.","affiliations":[{"id":6984,"text":"UC Riverside","active":true,"usgs":false}],"preferred":false,"id":726854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Kenneth 0000-0003-3933-3163 kryan@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-3163","contributorId":191921,"corporation":false,"usgs":true,"family":"Ryan","given":"Kenneth","email":"kryan@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726851,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195102,"text":"70195102 - 2017 - Investigating seagrass in Toxoplasma gondii transmission in Florida (Trichechus manatus latirostris) and Antillean (T. m. manatus) manatees","interactions":[],"lastModifiedDate":"2018-02-07T13:38:45","indexId":"70195102","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Investigating seagrass in Toxoplasma gondii transmission in Florida (Trichechus manatus latirostris) and Antillean (T. m. manatus) manatees","title":"Investigating seagrass in Toxoplasma gondii transmission in Florida (Trichechus manatus latirostris) and Antillean (T. m. manatus) manatees","docAbstract":"Toxoplasma gondii is a feline protozoan reported to cause morbidity and mortality in manatees and other marine mammals. Given the herbivorous nature of manatees, ingestion of oocysts from contaminated water or seagrass is presumed to be their primary mode of infection. The objectives of this study were to investigate oocyst contamination of seagrass beds in Puerto Rico and determine the seroprevalence of T. gondii in Antillean (Trichechus manatus manatus) and Florida (T. m. latirostris) manatees. Sera or plasma from Antillean (n = 5) and Florida (n = 351) manatees were tested for T. gondii antibodies using the modified agglutination test. No T. gondii DNA was detected via PCR in seagrass samples (n = 33) collected from Puerto Rico. Seroprevalence was 0%, suggesting a lower prevalence of T. gondii in these manatee populations than previously reported. This was the first study to investigate the potential oocyst contamination of the manatee diet, and similar studies are important for understanding the epidemiology of T. gondii in herbivorous marine mammals.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03181","usgsCitation":"Wyrosdick, H.M., Gerhold, R.W., Su, C., Mignucci-Giannoni, A.A., Bonde, R.K., Chapman, A., Riviera-Perez, C., Martinez, J., and Miller, D.L., 2017, Investigating seagrass in Toxoplasma gondii transmission in Florida (Trichechus manatus latirostris) and Antillean (T. m. manatus) manatees: Diseases of Aquatic Organisms, v. 127, no. 1, p. 65-69, https://doi.org/10.3354/dao03181.","productDescription":"5 p.","startPage":"65","endPage":"69","ipdsId":"IP-086147","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03181","text":"Publisher Index Page"},{"id":351276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e7ae4b00f54eb229330","contributors":{"authors":[{"text":"Wyrosdick, Heidi M.","contributorId":201769,"corporation":false,"usgs":false,"family":"Wyrosdick","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":726932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerhold, Richard W.","contributorId":201770,"corporation":false,"usgs":false,"family":"Gerhold","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":726933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Su, Chunlei","contributorId":167590,"corporation":false,"usgs":false,"family":"Su","given":"Chunlei","email":"","affiliations":[{"id":24765,"text":"University of Tennessee, Department of Microbiology, Knoxville, TN 37996-0845","active":true,"usgs":false}],"preferred":false,"id":726934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mignucci-Giannoni, Antonio A.","contributorId":201773,"corporation":false,"usgs":false,"family":"Mignucci-Giannoni","given":"Antonio","email":"","middleInitial":"A.","affiliations":[{"id":36251,"text":"Interamerican University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":726938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":726931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Alycia","contributorId":201771,"corporation":false,"usgs":false,"family":"Chapman","given":"Alycia","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":726935,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Riviera-Perez, Carla","contributorId":201774,"corporation":false,"usgs":false,"family":"Riviera-Perez","given":"Carla","affiliations":[{"id":36251,"text":"Interamerican University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":726939,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martinez, Jessica","contributorId":201772,"corporation":false,"usgs":false,"family":"Martinez","given":"Jessica","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":726936,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Debra L.","contributorId":192524,"corporation":false,"usgs":false,"family":"Miller","given":"Debra","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":726937,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}