Aims
Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions.
Location
Southwestern United States.
Methods
We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment.
Results
Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI.
Conclusions
Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.
Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombusspp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp.and other pollinators.
","language":"English","publisher":"Wiley","doi":"10.1111/jen.12583","usgsCitation":"McNeil, D.J., Otto, C., Moser, E.L., Urban-Mead, K.R., King, D.E., Rodewald, A.D., and Larkin, J.L., 2019, Distance models as a tool for modelling detection probability and density of native bumblebees: Journal of Applied Entomology, v. 143, no. 3, p. 225-235, https://doi.org/10.1111/jen.12583.","productDescription":"11 p.","startPage":"225","endPage":"235","ipdsId":"IP-096861","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":359602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Centre County, Clinton County","otherGeospatial":"Pennsylvania 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Jr.","contributorId":37620,"corporation":false,"usgs":false,"family":"McNeil","given":"Darin","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":751537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":751536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moser, Erin L.","contributorId":210723,"corporation":false,"usgs":false,"family":"Moser","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":38138,"text":"Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urban-Mead, Katherine R.","contributorId":210724,"corporation":false,"usgs":false,"family":"Urban-Mead","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":38139,"text":"Department of Entomology, Cornell University, Ithaca, NY 14850, US","active":true,"usgs":false}],"preferred":false,"id":751539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, David E.","contributorId":210754,"corporation":false,"usgs":false,"family":"King","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":751540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":751541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202862,"text":"70202862 - 2019 - Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","interactions":[],"lastModifiedDate":"2019-04-17T10:20:15","indexId":"70202862","displayToPublicDate":"2018-11-20T10:19:53","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","docAbstract":"At over 2.5 million acres, Glacier National Park and the Bob Marshall Wilderness complex form one of the largest protected areas in the continental United States. Straddling the Continental Divide, these two areas form a vital linkage between vast areas of public land to the south towards Yellowstone, and contiguous protected areas north of the US-Canada border. However, US Highway 2 (US2) and the Burlington Northern-Santa Fe (BNSF) railroad separate Glacier National Park to the north from the Bob Marshall Wilderness complex to the south. While this narrow ribbon of development passes through primarily public land, it is bordered in some areas by narrow strips of private land. Many of these private parcels are developed as ranches, campgrounds, or seasonal and permanent home sites and businesses.
Currently, two of the defining characteristics of this portion of the US2 corridor are relatively low highway traffic volume, but relatively high railroad traffic volume. The highway had a 2017 annual average daily traffic volume (AADT) of 1859 vehicles, far less than other interstate highways around the region which often have AADTs well over 10,000. Conversely, the BNSF railroad line currently carries about 33 trains per day, making it one of the busier railroad lines in the northwestern US.
While wildlife movement patterns across this corridor have not been well studied, the existing data suggests that wildlife can still make frequent and successful crossings at current railroad and highway traffic levels. However, as the region’s human population grows, we expect that connectivity to diminish. Over the past decade (2000-2017), based on census data, Flathead County has grown by 10% and Glacier County has grown by 1.5%. A study on loss of open space found that Flathead County alone accounts for 15% of the new homes built in Montana since 2000 (https://headwaterseconomics.org/economicdevelopment/local-studies/montana-home construction/). Outdoor recreation and tourism have also been breaking participation records (source: GPI record passengers https://flatheadbeacon.com/2018/01/24/glacier-park-international-airport-sees-record-passengers-2017/, GNP record visitation https://www.usnews.com/news/best-states/montana/articles/2018-01 15/glaciernational-park-breaks-visitation-record-in-2017). This growth has been accompanied by a ~50% increase in highway traffic volume in the corridor over the past decade (Waller and Miller 2015). This increased traffic is decreasing the time available for wildlife to cross the highway and appears to be increasing the frequency of wildlife killed by vehicles (Fig. 1 and 2).
In addition, the Middle Fork of the Flathead River is a favored river for recreation, and this also appears to be growing. In the summer of 2017, researchers recorded 136 boats per day in July and 93 boats per day in August. Although the river does not extend along the entire highway, it extends along 31 miles of the highway corridor.
Accurate and precise analyses of oil and gas (O&G) wastewaters and solids (e.g., sediments and sludge) are important for the regulatory monitoring of O&G development and tracing potential O&G contamination in the environment. In this study, 15 laboratories participated in an inter-laboratory comparison on the chemical characterization of three O&G wastewaters from the Appalachian Basin and four solids impacted by O&G development, with the goal of evaluating the quality of data and the accuracy of measurements for various analytes of concern. Using a variety of different methods, analytes in the wastewaters with high concentrations (i.e., >5 mg L−1) were easily detectable with relatively high accuracy, often within ±10% of the most probable value (MPV). In contrast, often less than 7 of the 15 labs were able to report detectable trace metal(loid) concentrations (i.e., Cr, Ni, Cu, Zn, As, and Pb) with accuracies of approximately ±40%. Despite most labs using inductively coupled plasma mass spectrometry (ICP-MS) with low instrument detection capabilities for trace metal analyses, large dilution factors during sample preparation and low trace metal concentrations in the wastewaters limited the number of quantifiable determinations and likely influenced analytical accuracy. In contrast, all the labs measuring Ra in the wastewaters were able to report detectable concentrations using a variety of methods including gamma spectroscopy and wet chemical approaches following Environmental Protection Agency (EPA) standard methods. However, the reported radium activities were often greater than ±30% different to the MPV possibly due to calibration inconsistencies among labs, radon leakage, or failing to correct for self-attenuation. Reported radium activities in solid materials had less variability (±20% from MPV) but accuracy could likely be improved by using certified radium standards and accounting for self-attenuation that results from matrix interferences or a density difference between the calibration standard and the unknown sample. This inter-laboratory comparison illustrates that numerous methods can be used to measure major cation, minor cation, and anion concentrations in O&G wastewaters with relatively high accuracy while trace metal(loid) and radioactivity analyses in liquids may often be over ±20% different from the MPV.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/c8em00359a","usgsCitation":"Tasker, T.L., Burgos, W.D., Ajemigbitse, M.A., Lauer, N.E., Gusa, A.V., Kuatbek, M., May, D., Landis, J.D., Alessi, D.S., Johnsen, A.M., Kaste, J.M., Headrick, K., Wilke, F.D., McNeal, M., Engle, M.A., Jubb, A., Vidic, R., Vengosh, A., and Warner, N.R., 2019, Accuracy of methods for reporting inorganic element concentrations and radioactivity in oil and gas wastewaters from the Appalachian Basin, U.S. based on an inter-laboratory comparison.: Environmental Science: Processes and Impacts, v. 21, no. 2, p. 224-241, https://doi.org/10.1039/c8em00359a.","productDescription":"18 p.","startPage":"224","endPage":"241","ipdsId":"IP-100644","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Pittsburg","active":true,"usgs":false}],"preferred":false,"id":765150,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Vengosh, Avner","contributorId":208460,"corporation":false,"usgs":false,"family":"Vengosh","given":"Avner","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765151,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Warner, Nathaniel R.","contributorId":211458,"corporation":false,"usgs":false,"family":"Warner","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765152,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70203685,"text":"70203685 - 2019 - Linking variability in climate to wetland habitat suitability: Is it possible to forecast regional responses from simple climate measures?","interactions":[],"lastModifiedDate":"2019-06-05T15:22:28","indexId":"70203685","displayToPublicDate":"2018-11-17T15:21:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Linking variability in climate to wetland habitat suitability: Is it possible to forecast regional responses from simple climate measures?","docAbstract":"Temporary wetlands have value to both ecological and social systems. Interactions between local climate and the surrounding landscape result in patterns of hydrology that are unique to temporary wetlands. These seasonal and annual fluctuations in wetland inundation contribute to community composition and richness. Thus, predicting wetland community responses to environmental change is tied to the ability to predict wetland hydroregime. Detailed monitoring of wetland hydroregime is resource-intensive, limiting the scope and scale of forecasting. As an alternative, we determine which freely available measures of water availability best predict one component of wetland hydroregime, habitat suitability (i.e., the predictability of water in a wetland) within and among geographic regions. We used data from three North American regions to determine the climate index that best explained year-to-year variation in habitat suitability during a key phenological period—amphibian breeding. We demonstrate that simple, short-term climate indices based solely on precipitation data best predict habitat suitability in vernal pools in the northeast, montane wetlands in the west and coastal plain wetlands in the southeast. These relationships can help understand how changes in short-term precipitation patterns as a result of climate change may influence the overall hydroregime, and resulting biodiversity, of temporary wetlands across disparate biomes.","language":"English","publisher":"Springer","doi":"10.1007/s11273-018-9639-2","usgsCitation":"C, D., D, M., Campbell Grant, E.H., Halstead, B., Kleeman, P.M., Walls, S., and Barichivich, W., 2019, Linking variability in climate to wetland habitat suitability: Is it possible to forecast regional responses from simple climate measures?: Wetlands Ecology and Management, v. 27, no. 1, p. 39-53, https://doi.org/10.1007/s11273-018-9639-2.","productDescription":"15 p.","startPage":"39","endPage":"53","ipdsId":"IP-096066","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":364394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364303,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s11273-018-9639-2"}],"volume":"27","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"C, Davis","contributorId":215984,"corporation":false,"usgs":false,"family":"C","given":"Davis","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":763599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D, Miller","contributorId":215985,"corporation":false,"usgs":false,"family":"D","given":"Miller","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":763600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":763598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":763601,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":763602,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walls, Susan 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":215987,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":763603,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barichivich, William 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":215988,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":763604,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200930,"text":"70200930 - 2019 - Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems","interactions":[],"lastModifiedDate":"2018-11-16T10:54:17","indexId":"70200930","displayToPublicDate":"2018-11-16T10:54:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems","docAbstract":"Large river-floodplain systems are hotspots of biodiversity and ecosystem services but are also used for multiple human activities, making them one of the most threatened ecosystems worldwide. There is wide evidence that reconnecting river channels with their floodplains is an effective measure to increase their multi-functionality, i.e., ecological integrity, habitats for multiple species and the multiple functions and services of river-floodplain systems, although, the selection of promising sites for restoration projects can be a demanding task. In the case of the Danube River in Europe, planning and implementation of restoration projects is substantially hampered by the complexity and heterogeneity of the environmental problems, lack of data and strong differences in socio-economic conditions as well as inconsistencies in legislation related to river management. We take a quantitative approach based on best-available data to assess biodiversity using selected species and three ecosystem services (flood regulation, crop pollination, and recreation), focused on the navigable main stem of the Danube River and its floodplains. We spatially prioritize river-floodplain segments for conservation and restoration based on (1) multi-functionality related to biodiversity and ecosystem services, (2) availability of remaining semi-natural areas and (3) reversibility as it relates to multiple human activities (e.g. flood protection, hydropowerand navigation). Our approach can thus serve as a strategic planning tool for the Danube and provide a method for similar analyses in other large river-floodplain systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.10.322","usgsCitation":"Funk, A., Martinez-Lopez, J., Borgwardt, F., Traunder, D., Bagstad, K.J., Balbi, S., Magrach, A., Villa, F., and Hein, T., 2019, Identification of conservation and restoration priority areas in the Danube River based on the multi-functionality of river-floodplain systems: Science of the Total Environment, v. 654, p. 763-777, https://doi.org/10.1016/j.scitotenv.2018.10.322.","productDescription":"15 p.","startPage":"763","endPage":"777","ipdsId":"IP-099325","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.10.322","text":"Publisher Index Page"},{"id":359509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Austria, Bulgaria, Croatia, Germany, Hungary, Romania, Slovakia, Serbia, Ukraine","otherGeospatial":"Danube River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 10,\n 43\n ],\n [\n 32,\n 43\n ],\n [\n 32,\n 50\n ],\n [\n 10,\n 50\n ],\n [\n 10,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"654","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5befe5b7e4b045bfcadf7f20","contributors":{"authors":[{"text":"Funk, Andrea","contributorId":210646,"corporation":false,"usgs":false,"family":"Funk","given":"Andrea","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borgwardt, Florian","contributorId":210647,"corporation":false,"usgs":false,"family":"Borgwardt","given":"Florian","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Traunder, Daniel","contributorId":210648,"corporation":false,"usgs":false,"family":"Traunder","given":"Daniel","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":751357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751362,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magrach, Ainhoa 0000-0003-2155-7556","orcid":"https://orcid.org/0000-0003-2155-7556","contributorId":208482,"corporation":false,"usgs":false,"family":"Magrach","given":"Ainhoa","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751363,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":751364,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hein, Thomas 0000-0002-7767-4607","orcid":"https://orcid.org/0000-0002-7767-4607","contributorId":210649,"corporation":false,"usgs":false,"family":"Hein","given":"Thomas","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":751365,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70228044,"text":"70228044 - 2019 - Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates","interactions":[],"lastModifiedDate":"2022-02-03T16:07:10.658187","indexId":"70228044","displayToPublicDate":"2018-11-15T10:00:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates","docAbstract":"Low survival rates of Chinook salmon (Oncorhynchus tshawytscha) smolts in California’s Central Valley have been attributed to multiple biological and physical factors, but it is not clear which factors have the largest impact. We used 5 years of acoustic telemetry data for 1709 late-fall Chinook salmon smolts to evaluate the effect of habitat- and predation-related covariates on outmigration survival through the Sacramento River. Using a Cormack–Jolly–Seber mark–recapture model, we estimated survival rates both as a function of covariates (covariate model) and as a function of river location and release year (spatial–temporal model). Our covariate model was overwhelmingly supported as the preferred model based on model selection criteria, suggesting the covariates adequately replicated spatial and temporal patterns in smolt survival. The covariates in the selected model included individual fish covariates, habitat-specific covariates, and temporally variable physical conditions. The most important covariate affecting salmon survival was flow. We describe the importance of these parameters in the context of juvenile salmon predation risk and suggest that additional research on predator distribution and density could improve model estimates.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0212","usgsCitation":"Henderson, M., Iglesias, I.S., Michel, C.J., Ammann, A.J., and Huff, D.D., 2019, Estimating spatial–temporal differences in Chinook salmon outmigration survival with habitat- and predation-related covariates: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 9, p. 1549-1561, https://doi.org/10.1139/cjfas-2018-0212.","productDescription":"13 p.","startPage":"1549","endPage":"1561","ipdsId":"IP-097049","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501022,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/94927","text":"External Repository"},{"id":395356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3,\n 38.70265930723801\n ],\n [\n -120.9375,\n 38.70265930723801\n ],\n [\n -120.9375,\n 40.44694705960048\n ],\n [\n -122.3,\n 40.44694705960048\n ],\n [\n -122.3,\n 38.70265930723801\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":832954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iglesias, Ilysa S.","contributorId":274387,"corporation":false,"usgs":false,"family":"Iglesias","given":"Ilysa","email":"","middleInitial":"S.","affiliations":[{"id":56613,"text":"uc sc","active":true,"usgs":false}],"preferred":false,"id":832955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michel, Cyril J.","contributorId":207096,"corporation":false,"usgs":false,"family":"Michel","given":"Cyril","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ammann, Arnold J.","contributorId":207095,"corporation":false,"usgs":false,"family":"Ammann","given":"Arnold","email":"","middleInitial":"J.","affiliations":[{"id":37452,"text":"National Marine Fisheries Service, Southwest Fisheries Science Center, 110 Shaffer Rd., Santa Cruz, CA 95060","active":true,"usgs":false}],"preferred":false,"id":832957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huff, David D.","contributorId":171694,"corporation":false,"usgs":false,"family":"Huff","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832958,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203350,"text":"70203350 - 2019 - Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D","interactions":[],"lastModifiedDate":"2019-05-07T13:06:04","indexId":"70203350","displayToPublicDate":"2018-11-14T13:04:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D","docAbstract":"Seismologists have recently begun utilizing low-cost nodal sensors in dense deployments to sample the seismic wavefield at unprecedented spatial resolution. Earthquake Early Warning Systems (EEWS) and other monitoring networks (e.g. wastewater injection) would additionally benefit from network densification; however, current nodal systems lack power systems and/or real-time data transmission required for these applications. A candidate sensor for these networks may instead be a low-cost, all-in-one package such as the OSOP Raspberry Shake 4D (RS-4D). The RS-4D includes a vertical component geophone, 3-component accelerometer, digitizer, and near real-time miniSEED data transmission, and costs only a few hundred dollars per unit. Here, we step through instrument testing of three RS-4Ds at the Albuquerque Seismological Laboratory. We find the geophones have sensitivities constrained to within 4% of nominal, but that they have relatively high self-noise levels compared to the broadband sensors typically used in seismic networks. To demonstrate the impact this would have on characterizing nearby events, we estimate local magnitudes of earthquakes in Oklahoma using Trillium Compact broadband sensor data from U.S. Geological Survey (USGS) aftershock deployments as well as 23 Raspberry Shakes operated by hobbyists and private owners within Oklahoma. We find that for ML 2.0-4.0 earthquakes at distances of 20-100 km from seismic stations, the Raspberry Shakes require events of magnitude ~0.3 larger than the broadband sensors in order to reliably estimate ML at a given distance from the epicenter. We conclude that RS-4Ds are suitable for densifying backbone networks designed for studies of local and regional events.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180251","usgsCitation":"Anthony, R.E., Ringler, A.T., Wilson, D.C., and Wolin, E., 2019, Do low-cost seismographs perform well enough for your network? An overview of laboratory tests and field observations of the OSOP Raspberry Shake 4D: Seismological Research Letters, v. 90, no. 1, p. 219-228, https://doi.org/10.1785/0220180251.","productDescription":"10 p.","startPage":"219","endPage":"228","ipdsId":"IP-102210","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":363559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolin, Emily 0000-0003-1610-1191 ewolin@usgs.gov","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":198778,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","email":"ewolin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":762272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227204,"text":"70227204 - 2019 - GHR1 Zircon – A new Eocene natural reference material for microbeam U-Pb geochronology and Hf isotopic analysis of zircon","interactions":[],"lastModifiedDate":"2022-01-04T13:31:01.197038","indexId":"70227204","displayToPublicDate":"2018-11-14T07:27:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"GHR1 Zircon – A new Eocene natural reference material for microbeam U-Pb geochronology and Hf isotopic analysis of zircon","docAbstract":"We present multitechnique U-Pb geochronology and Hf isotopic data from zircon separated from rapakivi biotite granite within the Eocene Golden Horn batholith in Washington, USA. A weighted mean of twenty-five Th-corrected 206Pb/238U zircon dates produced at two independent laboratories using chemical abrasion-isotope dilution-thermal ionisation mass spectrometry (CA-ID-TIMS) is 48.106 ± 0.023 Ma (2s analytical including tracer uncertainties, MSWD = 1.53) and is our recommended date for GHR1 zircon. Microbeam 206Pb/238U dates from laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and secondary ion mass spectrometry (SIMS) laboratories are reproducible and in agreement with the CA-ID-TIMS date to within < 1.5%. Solution multi-collector ICP-MS (MC-ICP-MS) measurements of Hf isotopes from chemically purified aliquots of GHR1 yield a mean 176Hf/177Hf of 0.283050 ± 17 (2s, n = 10), corresponding to a εHf0 of +9.3. Hafnium isotopic measurements from two LA-ICP-MS laboratories are in agreement with the solution MC-ICP-MS value. The reproducibility of 206Pb/238U and 176Hf/177Hf ratios from GHR1 zircon across a variety of measurement techniques demonstrates their homogeneity in most grains. Additionally, the effectively limitless reserves of GHR1 material from an accessible exposure suggest that GHR1 can provide a useful reference material for U-Pb geochronology of Cenozoic zircon and Hf isotopic measurements of zircon with radiogenic 176Hf/177Hf.
Dietary studies on generalist predators may provide valuable information on spatial or temporal changes in the structure of ecological communities. We initiated this study to provide baseline data and determine the utility of stable isotope analysis (SIA) to evaluate the foraging strategies of an opportunistic reptilian predator, the diamondback terrapin (Malaclemys terrapin), which specializes in salt marshes and mangrove estuaries along the Atlantic and Gulf coasts. We evaluated stable carbon (δ13C) and nitrogen (δ15N) isotope values of multiple tissues from terrapins inhabiting mainland and island mangrove habitats in south Florida and potential food sources to examine spatial and temporal variations in terrapin resource use. We fit linear regression models to determine the best predictors of isotopic values for both terrapins and their prey, and Stable Isotope Bayesian Ellipses in R (SIBER) analysis to examine terrapin isotopic niche space and overlap between groups. We identified differences in terrapin isotopic δ13C and δ15N values among all sites. Blood and scute tissues revealed different isotopic compositions and niche overlap between sites, suggesting diets or foraging locations may change over time, and amount of variation is site specific. Niche overlap between size classes was larger for blood (short term) versus scute (long term), suggesting greater variability in food habits or resource isotopes over the long term versus short term. These results demonstrate the usefulness of SIA in examining the spatial and temporal variability in diamondback terrapin resource use within estuary systems and further define their niche within these dynamic food webs.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-018-0476-6","usgsCitation":"Denton, M.J., Demopoulos, A.W., Baldwin, J.D., Smith, B., and Hart, K.M., 2019, Stable isotope analysis enhances our understanding of diamondback terrapin Malaclemys terrapin foraging ecology: Estuaries and Coasts, v. 42, no. 2, p. 596-611, https://doi.org/10.1007/s12237-018-0476-6.","productDescription":"16 p.","startPage":"596","endPage":"611","ipdsId":"IP-091296","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468064,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-018-0476-6","text":"Publisher Index Page"},{"id":437621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z89BK7","text":"USGS data release","linkHelpText":"Stable isotope ratios of carbon and nitrogen from diamondback terrapins and resources within Southern Everglades and Key West National Wildlife Refuge, sampled 2012-2013"},{"id":359277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-30","publicationStatus":"PW","scienceBaseUri":"5be40822e4b0b3fc5cf7cc04","contributors":{"authors":[{"text":"Denton, Mathew J. 0000-0002-1024-3722 mdenton@usgs.gov","orcid":"https://orcid.org/0000-0002-1024-3722","contributorId":4862,"corporation":false,"usgs":true,"family":"Denton","given":"Mathew","email":"mdenton@usgs.gov","middleInitial":"J.","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":750903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":750904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, John D.","contributorId":210505,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":750888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Brian 0000-0002-0531-0492 bjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":202305,"corporation":false,"usgs":true,"family":"Smith","given":"Brian","email":"bjsmith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":750902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Kristen M. 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":210506,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":750889,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204437,"text":"70204437 - 2019 - Survival and cause-specific mortality of desert bighorn sheep lambs","interactions":[],"lastModifiedDate":"2019-07-25T12:44:25","indexId":"70204437","displayToPublicDate":"2018-10-26T12:42:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Survival and cause-specific mortality of desert bighorn sheep lambs","docAbstract":"Juvenile recruitment in desert bighorn sheep (Ovis canadensis mexicana) is highly variable, yet the mechanisms driving neonate survival are not well understood for the species. Few studies have equipped desert bighorn sheep lambs with radiocollars. As a result, definitive data on cause-specific mortality and lamb survival estimates are lacking. Our objectives were to estimate lamb survival rates and determine cause-specific mortality for desert bighorn sheep lambs during a period of mountain lion (Puma concolor) and coyote (Canis latrans) removal in southwestern New Mexico. We captured pregnant adult females each fall and fitted them with a telemetry collar and a vaginal implant transmitter to aid with neonate captures. We captured and radiocollared 12 desert bighorn sheep lambs in 2012 and 14 in 2013 within 48 hrs of parturition in the Peloncillo Mountains, New Mexico. We used the nest survival model in program MARK to estimate lamb survival to 6 months of age. Across both years there were 14 mortalities, 12 (86%) of which were due to predation. Mountain lions killed 5 lambs (2 in 2012 and 3 in 2013), coyotes killed 4 lambs (all in 2013), a gray fox (Urocyon cinereoargenteus) killed 1 lamb in 2012; 2 lambs were killed by unknown predators in 2013. Staged-based survival estimates indicated the highest mortality rates occurred in the first week post birth; 33% to 36% of all lamb mortalities occurred before 7 days of age. Lamb survival was substantially lower in 2013 (0.20 ± 0.11 [SE]) than in 2012 (0.69 ± 0.16) with the differences in survival attributed to increased coyote predation in 2013. We did not detect differences in body mass, chest girth, or neck circumference between lambs that were killed by predators and those that survived. Coyotes, mountain lions and gray fox killed lambs <8 weeks of age, but only mountain lions killed lambs > 8 weeks old. Studies that fail to capture desert bighorn lambs near parturition will likely produce negatively biased survival estimates and inaccurate appraisals of primary causes of mortality due to early mortality of lambs.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21597","usgsCitation":"Cain, J.W., KARSCH, R.C., Goldstein, E.J., Rominger, E.M., and Gould, W.R., 2019, Survival and cause-specific mortality of desert bighorn sheep lambs: Journal of Wildlife Management, v. 83, no. 2, p. 251-259, https://doi.org/10.1002/jwmg.21597.","productDescription":"9 p.","startPage":"251","endPage":"259","ipdsId":"IP-083223","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":365949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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Unfortunately, time series data are often limited to counts of adult abundance and harvest. By incorporating data from other populations and by dynamically linking the life-history stages, Bayesian life-cycle models can be used to estimate stage-specific productivities and capacities as well as abundance of breeders that produce maximum sustained yield (MSY). Using coho salmon (Oncorhynchus kisutch) as our case study, we show that incorporating information on marine survival variability from nearby populations can improve model estimates and affect management parameters such as escapement at MSY. We further show that the expected long-term average yield of a fishery managed for a spawner escapement target that produces MSY strongly depends on the average marine survival. Our results illustrate the usefulness of incorporating information from other sources and highlight the importance of accounting for variation in marine survival when making inferences about the management of Pacific salmon.
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Understanding where, when, and why animals die provides useful information for prioritizing conservation practices designed to increase survival. As part of a satellite tracking study, we identified 19 confirmed and suspected deaths of Whooping Cranes of various ages from the Aransas-Wood Buffalo Population. Of these, more occurred during winter (∼45%), compared with summer (∼40%) or migration (∼15%). Summer mortalities occurred exclusively within Wood Buffalo National Park, and all winter mortalities occurred on the primary wintering grounds along the Texas Gulf Coast. Predation was the most common cause identified; proximate cause of mortality was not known for most of the birds. Previous assessments of mortality, based on assumptions and some supporting data, speculated that most mortality occurred during migration. Although preliminary, our results are based on stronger evidence and provide a different perspective. Migration may be less risky than previously assumed and of similar risk to other seasons; thus, conservation or management efforts to reduce mortality may have greater effect when focused during breeding and wintering periods, although feasibility and efficacy of these actions will need to be determined.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Whooping Cranes: Biology and conservation","language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-803555-9.00006-2","usgsCitation":"Pearse, A.T., Brandt, D.A., Hartup, B.K., and Bidwell, M., 2019, Mortality in Aransas-Wood Buffalo Whooping Cranes: Timing, location, and causes, chap. of Whooping Cranes: Biology and conservation, p. 125-138, https://doi.org/10.1016/B978-0-12-803555-9.00006-2.","productDescription":"14 p.","startPage":"125","endPage":"138","ipdsId":"IP-070538","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":358682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8dfe4b034bf6a7e4da4","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":748410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":748411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartup, Barry K.","contributorId":209630,"corporation":false,"usgs":false,"family":"Hartup","given":"Barry","email":"","middleInitial":"K.","affiliations":[{"id":16606,"text":"International Crane Foundation","active":true,"usgs":false}],"preferred":false,"id":748412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":139204,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark T.","affiliations":[{"id":12696,"text":"Environmental Canada","active":true,"usgs":false}],"preferred":false,"id":748413,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200477,"text":"70200477 - 2019 - Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells","interactions":[],"lastModifiedDate":"2019-01-28T08:57:31","indexId":"70200477","displayToPublicDate":"2018-10-20T17:25:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells","docAbstract":"The application of horizontal and hydraulically fractured wells for producing oil from low permeability formations has changed the face of the North American oil industry. One feature of the production profile of many such wells is a transition from transient linear oil flow to boundary-dominated flow. The identification of the time of this transition is important for the calibration of models that forecast the well’s future production and the expected ultimate recovery. It is preferable that such models generally use data from the boundary-dominated flow regime for parameter calibration. Accurate well production forecasts are needed for operational decisions, long-term planning, commercial transactions, regulatory proceedings, and asset valuation. Petroleum engineers frequently make the call on the transition point based on subjective visual interpretations of log–log plots for individual wells. This is time-consuming and is generally not repeatable by other analysts. This note evaluates statistical approaches that can serve as alternatives to the subjective visual interpretations. Specifically, the predictive performance of production models calibrated with boundary-dominated data based on transition dates calculated with constrained nonlinear least squares and Bayesian regressions was very close to that obtained using the visual method, suggesting that statistical approaches may indeed be constructed to replace less objective visual approaches without loss of accuracy.
","language":"English","publisher":"Springer","doi":"10.1007/s11053-018-9389-0","usgsCitation":"Attanasi, E., Coburn, T., and Ran-McDonald, B., 2019, Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells: Natural Resources Research, v. 28, no. 1, p. 259-272, https://doi.org/10.1007/s11053-018-9389-0.","productDescription":"14 p.","startPage":"259","endPage":"272","ipdsId":"IP-091903","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468068,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-018-9389-0","text":"Publisher Index Page"},{"id":358589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-26","publicationStatus":"PW","scienceBaseUri":"5c10a91ae4b034bf6a7e4fb3","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coburn, T.C.","contributorId":209912,"corporation":false,"usgs":false,"family":"Coburn","given":"T.C.","email":"","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":749070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ran-McDonald, B.","contributorId":209913,"corporation":false,"usgs":false,"family":"Ran-McDonald","given":"B.","email":"","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":749071,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203355,"text":"70203355 - 2019 - Changing station coverage impacts temperature trends in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2019-05-09T09:03:39","indexId":"70203355","displayToPublicDate":"2018-10-19T10:09:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Changing station coverage impacts temperature trends in the Upper Colorado River Basin","docAbstract":"Over the Upper Colorado River Basin (UCRB), temperatures in widely used gridded data products do not warm as much as mean temperatures from a stable set of U.S. Historical Climatology Network (USHCN) stations, located at generally lower elevations, in most months of the year. This is contrary to expectations of elevation-dependent warming, which suggests that warming increases with elevation. These findings could reflect 1) a genuine absence of elevation-dependent warming in the region, 2) systematic non-climatic influences on either the USHCN stations or high elevation stations, including known inhomogeneities related to changes in the time of observation and instrumentation, or 3) suppression of an elevation-dependent warming signal introduced by changes in the station network. While we cannot categorically dismiss the first two possibilities, we show here that over portions of the 20th century, gridded temperatures warm less than USHCN temperatures and the difference cannot be explained by accounting for known inhomogeneities. These analyses suggest that changing station coverage in the UCRB has influenced trends in gridded temperature estimates that incorporate changing suites of stations over time. Specifically, increases in the number of high-elevation stations in the UCRB may have led to an underestimation of elevation-dependent warming, particularly during the spring and summer. This phenomenon is unlikely limited to this specific basin, and may be present in other high-elevation watersheds across the western U.S.","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.5898","usgsCitation":"McAfee, S., McCabe, G.J., Gray, S., and Pederson, G.T., 2019, Changing station coverage impacts temperature trends in the Upper Colorado River Basin: International Journal of Climatology, v. 39, no. 3, p. 1517-1538, https://doi.org/10.1002/joc.5898.","productDescription":"22 p.","startPage":"1517","endPage":"1538","ipdsId":"IP-092579","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":363584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112,\n 36.5\n ],\n [\n -106,\n 36.5\n ],\n [\n -106,\n 44\n ],\n [\n -112,\n 44\n ],\n [\n -112,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":762282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":762283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":762284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":762281,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200353,"text":"70200353 - 2019 - Assessing effects of nonnative crayfish on mosquito survival","interactions":[],"lastModifiedDate":"2019-01-28T09:02:11","indexId":"70200353","displayToPublicDate":"2018-10-15T14:59:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing effects of nonnative crayfish on mosquito survival","docAbstract":"Introductions of nonnative predators often reduce biodiversity and affect natural predator–prey relationships and may increase the abundance of potential disease vectors (e.g., mosquitoes) indirectly through competition or predation cascades. The Santa Monica Mountains (California, U.S.A.), situated in a global biodiversity hotspot, is an area of conservation concern due to climate change, urbanization, and the introduction of nonnative species. We examined the effect of nonnative crayfish (Procambarus clarkii) on an existing native predator, dragonfly nymphs (Aeshna sp.), and their mosquito larvae (Anopheles sp.) prey. We used laboratory experiments to compare the predation efficiency of both predators, separately and together, and field data on counts of dragonfly nymphs and mosquito larvae sampled from 13 local streams. We predicted a lower predation efficiency of crayfish compared with native dragonfly nymphs and a reduced predation efficiency of dragonfly nymphs in the presence of crayfish. Dragonfly nymphs were an order of magnitude more efficient predators than crayfish, and dragonfly nymph predation efficiency was reduced in the presence of crayfish. Field count data showed that populations of dragonfly nymphs and mosquito larvae were strongly correlated with crayfish presence in streams, such that sites with crayfish tended to have fewer dragonfly nymphs and more mosquito larvae. Under natural conditions, it is likely that crayfish reduce the abundance of dragonfly nymphs and their predation efficiency and thereby, directly and indirectly, lead to higher mosquito populations and a loss of ecosystem services related to disease vector control.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13198","usgsCitation":"Bucciarelli, G.M., Suh, D., Davis Lamb, A., Roberts, D., Sharpton, D., Shaffer, H.B., Fisher, R.N., and Kats, L.B., 2019, Assessing effects of nonnative crayfish on mosquito survival: Conservation Biology, v. 33, no. 1, p. 122-131, https://doi.org/10.1111/cobi.13198.","productDescription":"10 p.","startPage":"122","endPage":"131","ipdsId":"IP-096785","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.13198","text":"Publisher Index Page"},{"id":358383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"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 -119.08218383789062,\n 33.98664113654014\n ],\n [\n -118.4600830078125,\n 33.98664113654014\n ],\n [\n -118.4600830078125,\n 34.25948651450623\n ],\n [\n -119.08218383789062,\n 34.25948651450623\n ],\n [\n -119.08218383789062,\n 33.98664113654014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-28","publicationStatus":"PW","scienceBaseUri":"5c10a91fe4b034bf6a7e4ffd","contributors":{"authors":[{"text":"Bucciarelli, Gary M.","contributorId":209642,"corporation":false,"usgs":false,"family":"Bucciarelli","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":748473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suh, Daniel","contributorId":209641,"corporation":false,"usgs":false,"family":"Suh","given":"Daniel","email":"","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":748472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis Lamb, Avery","contributorId":209643,"corporation":false,"usgs":false,"family":"Davis Lamb","given":"Avery","email":"","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":748476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Dave","contributorId":150673,"corporation":false,"usgs":false,"family":"Roberts","given":"Dave","email":"","affiliations":[{"id":13655,"text":"Montana State Univ.","active":true,"usgs":false}],"preferred":false,"id":748477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharpton, Debra","contributorId":209644,"corporation":false,"usgs":false,"family":"Sharpton","given":"Debra","email":"","affiliations":[{"id":37950,"text":"Mountains Restoration Trust","active":true,"usgs":false}],"preferred":false,"id":748478,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaffer, H. Bradley","contributorId":202769,"corporation":false,"usgs":false,"family":"Shaffer","given":"H.","email":"","middleInitial":"Bradley","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":748474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":748471,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kats, Lee B.","contributorId":208330,"corporation":false,"usgs":false,"family":"Kats","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":37783,"text":"Seaver College, Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":748475,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204366,"text":"70204366 - 2019 - Microhabitat use of native fishes in the Kootenai River: A fine‐scale evaluation of large‐scale habitat rehabilitation efforts","interactions":[],"lastModifiedDate":"2019-12-22T14:47:40","indexId":"70204366","displayToPublicDate":"2018-10-05T12:22:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Microhabitat use of native fishes in the Kootenai River: A fine‐scale evaluation of large‐scale habitat rehabilitation efforts","docAbstract":"Fish and microhabitat data were collected at 542 prepositioned electrofishing sites (surface area of each site = 4 m2) in the Kootenai River, Idaho, during 2014 and 2015 to evaluate small‐scale habitat use by fishes, as it relates to large‐scale habitat rehabilitation efforts. Samples were collected from a 12‐km braided segment of river that had received localized habitat rehabilitation treatments since 2011. Fish and microhabitat data were collected to investigate habitat drivers related to the occurrence and relative abundance of fishes. Each sampling location was selected at random and characterized as “treated” (i.e., rehabilitated) or “untreated” based on proximity to habitat treatments. Fishes sampled from backwaters composed 71% of the overall catch and 84% of the catch from locally untreated areas of the river. Species‐specific regression models suggested that water depth and current velocity influenced the occurrence and abundance of fishes. In particular, shallow habitats with low current velocities were important for small‐bodied native fishes and likely serve as important rearing areas for juvenile fish. These habitat conditions typically characterize backwater and channel‐margin habitats that are vulnerable to anthropogenic perturbation. Prioritizing process‐based rehabilitation of these areas in large, regulated rivers would allow natural channel‐forming processes for the benefit of native fishes.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3366","usgsCitation":"Branigan, P.R., Quist, M.C., Bradley B. 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Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five “Tier 1” ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed.
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