Questions have persisted on the usefulness of physics‐based earthquake simulators with respect to forecasting earthquakes, due mostly to the inevitable assumptions, approximations, and uncertainties. Whether any model is reliable or trustworthy depends entirely on what questions we are asking of it, so the point of this article is to outline a number of currently anticipated and desired inferences, informed largely by recent forecasting efforts in California. This article does not provide an in‐depth review of physics‐based simulators, nor does it render judgment on the usefulness question. The intent, rather, is to provide an explicit list of potential uses, or inferences, to enable more informed discussions among physics‐based modeling experts.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180299","usgsCitation":"Field, E., 2019, How physics‐based earthquake simulators might help improve earthquake forecasts: Seismological Research Letters, v. 90, no. 2A, p. 467-472, https://doi.org/10.1785/0220180299.","productDescription":"6 p.","startPage":"467","endPage":"472","ipdsId":"IP-103855","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":360766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"2A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","scienceBaseUri":"5c5022c4e4b0708288f7e807","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":755125,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70201765,"text":"70201765 - 2019 - Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat","interactions":[],"lastModifiedDate":"2019-01-29T12:37:17","indexId":"70201765","displayToPublicDate":"2019-01-09T12:37:12","publicationYear":"2019","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":"Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat","docAbstract":"Birds are essential components of most ecosystems and provide many services valued by society. However, many populations have undergone striking declines as their habitats have been lost or degraded by human activities. Terrestrial grasslands are vital habitat for birds in the North American Prairie Pothole Region (PPR), but grassland conversion and fragmentation from agriculture and energy-production activities have destroyed or degraded millions of hectares. Conservation grasslands can provide alternate habitat. In the United States, the Conservation Reserve Program (CRP) is the largest program maintaining conservation grasslands on agricultural lands, but conservation grasslands in the PPR have declined by over 1 million ha since the program’s zenith in 2007. We used an ecosystem-services model (InVEST) parameterized for the PPR to quantify grassland-bird habitat remaining in 2014 and to assess the degradation status of the remaining grassland-bird habitat as influenced by crop and energy (i.e., oil, natural gas, and wind) production. We compared our resultant habitat-quality ratings to grassland-bird abundance data from the North American Breeding Bird Survey to confirm that ratings were related to grassland-bird abundance. Of the grassland-bird habitat remaining in 2014, about 19% was degraded by crop production that occurred within 0.1 km of grassland habitats, whereas energy production degraded an additional 16%. We further quantified the changes in availability of grassland-bird habitat under various land-cover scenarios representing incremental losses (10%, 25%, 50%, 75%, and 100%) of CRP grasslands from 2014 levels. Our model identified 1 million ha (9%) of remaining grassland-bird habitat in the PPR that would be lost or degraded if all CRP conservation grasslands were returned to crop production. Grassland regions world-wide face similar challenges in maintaining avian habitat in the face of increasing commodity and energy production to sate the food and energy needs of a growing world population. Identifying ways to model the impacts of the tradeoff between food and energy production and wildlife production is an important step in creating solutions.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0198382","usgsCitation":"Shaffer, J.A., Roth, C.L., and Mushet, D.M., 2019, Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat: PLoS ONE, v. 14, no. 1, p. 1-17, https://doi.org/10.1371/journal.pone.0198382.","productDescription":"e0198382; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-089961","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468001,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0198382","text":"Publisher Index Page"},{"id":437609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72J69RM","text":"USGS data release","linkHelpText":"Modeling effects of crop production, energy development and conservation-grassland loss on avian habitat: dataset of BBS data, ND, with habitat rankings"},{"id":360786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","volume":"14","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":755278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223857,"text":"70223857 - 2019 - To what extent is drought-induced tree mortality a natural phenomenon?","interactions":[],"lastModifiedDate":"2021-09-10T15:02:02.695241","indexId":"70223857","displayToPublicDate":"2019-01-09T09:36:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"To what extent is drought-induced tree mortality a natural phenomenon?","docAbstract":"Catastrophic forest mortality due to more extreme rainfall deficits and higher temperatures under future climate scenarios has been predicted. The aim of this study is to explore the magnitude of historical drought-induced tree mortality under pre-warming conditions.
North-eastern Australia.
1845–2017.
Trees.
Field survey, historical analysis and climate analysis.
We present evidence of 18%–30% tree mortality from recent droughts across three regions of north-eastern Australia with rainfall deficits less severe than earlier historical droughts. The corrected temperature record represents modest warming at the stations with long records in the vicinity of the study areas. In terms of rainfall deficit the most severe drought on record occurred in the early 20th century, and historical evidence confirms that this drought and earlier droughts before the advent of pastoralism coincided with substantial tree mortality.
Dramatic declines in woody biomass in response to drought historically occurred more than once a century and are a natural phenomenon in semi-arid Australia. The magnitude of drought-induced tree mortality under natural climate fluctuations requires further investigation in other continents. Widespread drought-induced tree mortality is not just a recent global change phenomenon and has been underestimated as a natural ecological process. However, even more severe forest die-off events from more extreme hotter droughts are predicted if Earth’s warming proceeds as currently projected.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.12858","usgsCitation":"Fensham, R., Laffineur, B., and Allen, C.D., 2019, To what extent is drought-induced tree mortality a natural phenomenon?: Global Ecology and Biogeography, v. 287, no. 3801, p. 365-373, https://doi.org/10.1111/geb.12858.","productDescription":"9 p.","startPage":"365","endPage":"373","ipdsId":"IP-080198","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":389057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 142.3828125,\n -27.098253906137884\n ],\n [\n 148.359375,\n -27.098253906137884\n ],\n [\n 148.359375,\n -17.518344187852207\n ],\n [\n 142.3828125,\n -17.518344187852207\n ],\n [\n 142.3828125,\n -27.098253906137884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"287","issue":"3801","noUsgsAuthors":false,"publicationDate":"2019-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Fensham, R.","contributorId":68124,"corporation":false,"usgs":true,"family":"Fensham","given":"R.","affiliations":[],"preferred":false,"id":823005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laffineur, Boris","contributorId":265580,"corporation":false,"usgs":false,"family":"Laffineur","given":"Boris","email":"","affiliations":[],"preferred":false,"id":823006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":823007,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227779,"text":"70227779 - 2019 - A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems","interactions":[],"lastModifiedDate":"2022-01-31T14:52:59.91393","indexId":"70227779","displayToPublicDate":"2019-01-09T08:48:49","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":"A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems","docAbstract":"Minimizing fishing impacts on seafloor ecosystems is a growing focus of ocean management; however, few quantitative tools exist to guide seascape-scale habitat management. To meet these needs, we developed a model to assess benthic ecosystem impacts from fishing gear contact. The habitat impacts model is cast in discrete time and can accommodate overlapping fisheries as well as incorporate gear-specific contact dynamics. We implemented the model in the North Pacific using fishing data from 2003 to 2017, estimating that habitat in 3.1% of the 1.2 million km2 study area was disturbed at the end of the simulation period. A marked decline in habitat disturbance was evident since 2010, attributable to a single regulatory gear change that lifted trawl gear components off the seafloor. Running scenarios without these gear modifications showed these policies might have contributed to a 24% reduction in habitat disturbance since their implementation. Ultimately, model outputs provide direct estimates of the spatial and temporal trends of habitat effects from fishing — a key component of regulatory policies for many of the world’s fisheries.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0243","usgsCitation":"Smeltz, T.S., Harris, B., Olson, J., and Sethi, S., 2019, A seascape-scale habitat model to support management of fishing impacts on benthic ecosystems: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 10, p. 1836-1844, https://doi.org/10.1139/cjfas-2018-0243.","productDescription":"9 p.","startPage":"1836","endPage":"1844","ipdsId":"IP-092665","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468002,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0243","text":"External Repository"},{"id":395132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smeltz, T. Scott","contributorId":272598,"corporation":false,"usgs":false,"family":"Smeltz","given":"T.","email":"","middleInitial":"Scott","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":832207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Bradley","contributorId":272599,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":832208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olson, John","contributorId":272600,"corporation":false,"usgs":false,"family":"Olson","given":"John","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":832209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832206,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215987,"text":"70215987 - 2019 - Improving estimates and forecasts of lake carbon dynamics using data assimilation","interactions":[],"lastModifiedDate":"2020-11-03T14:07:26.459331","indexId":"70215987","displayToPublicDate":"2019-01-09T08:04:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Improving estimates and forecasts of lake carbon dynamics using data assimilation","docAbstract":"Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite successful use of this technique in other fields. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill observation gaps. In this article, we highlight the utility of data assimilation in lake carbon cycling research by using the ensemble Kalman filter to combine simple lake carbon models with observations of lake carbon pools and fluxes. We demonstrate that data assimilation helps reduce uncertainty in estimates of lake carbon pools and fluxes and more accurately estimate the true carbon pool size compared to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.
Commensurate valuation of market and nonmarket public goods allows for a more valid benefit-cost analysis. Economic methods for valuing nonmarket public goods include actual behavior-based revealed preference methods, such as the hedonic property method for urban-suburban public goods and travel cost models for outdoor recreation. For valuing proposed public goods for which there is no current behavior, or valuing the existence or passive use values of public goods, economists can rely on stated preference methods. While there is skepticism among some economists for relying on what people say they will pay rather than what their actual behavior suggests they will pay, there is general acceptance of stated preference methods. These stated preference methods include the well-known contingent valuation method and choice experiments (sometimes called conjoint analysis). Lastly, in situations where there is neither time nor money to conduct an original revealed or stated preference study, economists can rely on benefit transfers from existing revealed preference and stated preference studies to provide rough estimates of the values of public goods such as water quality, air quality, wetlands, recreation, and endangered species.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of Regional Science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer Link","doi":"10.1007/978-3-642-36203-3","isbn":"9783642362033","usgsCitation":"Loomis, J.B., Huber, C., and Richardson, L., 2019, Methods of environmental valuation, chap. of Handbook of Regional Science, 25 p., https://doi.org/10.1007/978-3-642-36203-3.","productDescription":"25 p.","onlineOnly":"Y","ipdsId":"IP-102704","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":365069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Loomis, John B.","contributorId":197268,"corporation":false,"usgs":false,"family":"Loomis","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":757238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":757236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":757237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205031,"text":"70205031 - 2019 - Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015","interactions":[],"lastModifiedDate":"2019-08-29T09:18:55","indexId":"70205031","displayToPublicDate":"2019-01-07T09:14:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015","docAbstract":"Air pollution and dust storms are associated with increased cardiovascular hospital admissions. The aim of this study was to investigate the association between short-term exposure to ambient air pollutants and CVD (cardiovascular disease) events in a long-term observational period. The study included the events of cardiovascular diseases (namely coronary artery disease, ischemic heart disease, myocardial infarction, and pneumo thrombo embolism) within the population of Shiraz, from March 21, 2009 to March 20, 2015. Also, each patient’s demographics were recorded. Main meteorological variables and five ambient pollutants (CO, O3, SO2, NO2, and PM10) were recorded. Statistical analysis was performed using linear regression (GLM) and a generalized additive model (GAM) estimating Poisson distribution and adjusted for the main risk factors and ambient meteorological variables. A mild prevalence (51.5%) of coronary artery disease (CAD) was registered in 6425 events. In GLM analysis, we observed an association among the pollutants with the coronary artery disease hospital admissions which was in the order of CO, NO2, and PM10. The highest association of each pollutant with hospital admission was observed as PM10 at lag 4 (RR = 1.08; 95% CI 1.02, 1.14 and p < 0.05), NO2 at lag 0 (RR = 1.22; 95% CI 1.00, 1.48), and CO at lag 0 (RR = 1.52 95% CI = (1.16, 1.99)). However, on dusty days, there were significantly higher numbers of referrals of cardiovascular patients (mean = 7.54 ± 4.44 and p = 0.002,) than on non-dusty days. According to these data, dust storms and some types of pollutants in the air are responsible for more admissions to hospitals for cardiovascular problems.
","language":"English","publisher":"Springer","doi":"10.1007/s11356-018-3952-4","usgsCitation":"Soleimani, Z., Boloorani, A.D., Khalifeh, R., Griffin, D.W., and Mesdaghinia, A., 2019, Short-term effects of ambient air pollution and cardiovascular events in Shiraz, Iran, 2009 to 2015: Environmental Science and Pollution Research, v. 26, no. 7, p. 6359-6367, https://doi.org/10.1007/s11356-018-3952-4.","productDescription":"9 p.","startPage":"6359","endPage":"6367","ipdsId":"IP-097671","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":367056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","city":"Shiraz","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 52.397918701171875,\n 29.476067910657175\n ],\n [\n 52.6959228515625,\n 29.476067910657175\n ],\n [\n 52.6959228515625,\n 29.742916942840562\n ],\n [\n 52.397918701171875,\n 29.742916942840562\n ],\n [\n 52.397918701171875,\n 29.476067910657175\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Soleimani, Zahra","contributorId":218616,"corporation":false,"usgs":false,"family":"Soleimani","given":"Zahra","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boloorani, Ali Darvishi","contributorId":218617,"corporation":false,"usgs":false,"family":"Boloorani","given":"Ali","email":"","middleInitial":"Darvishi","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khalifeh, Reza","contributorId":218618,"corporation":false,"usgs":false,"family":"Khalifeh","given":"Reza","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mesdaghinia, Alireza","contributorId":218619,"corporation":false,"usgs":false,"family":"Mesdaghinia","given":"Alireza","affiliations":[{"id":39870,"text":"Tehran University","active":true,"usgs":false}],"preferred":false,"id":769649,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204053,"text":"70204053 - 2019 - A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario","interactions":[],"lastModifiedDate":"2025-02-07T15:26:06.265811","indexId":"70204053","displayToPublicDate":"2019-01-04T10:06:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario","docAbstract":"Stock assessments are critical to modern fisheries management, supporting the calculation of key reference variables used to make informed management decisions. However, there is still considerable uncertainty as to which class of assessment models is appropriate to use under different circumstances. A common class of models used when age data are available are statistical catch-at-age assessment (SCAA) models, which track annual cohorts through time. When age data are unavailable, as is often the case in invertebrate fisheries where the lack of a bony structure such as otoliths makes aging difficult, statistical catch-at-size assessment (SCSA) models are more often employed, tracking fish or invertebrates through time by size-classes rather than ages. Do SCAA models actually perform better than SCSA models when age data are available, or is this just an assumption we make in fisheries research and management? We examined this question by evaluating the effectiveness of both SCAA and SCSA models in characterizing cisco, Coregonus artedi, population dynamics in Thunder Bay, Ontario. Both models were fit using an integrated framework with multiple sources of data including hydroacoustic estimates of spawning stock, fishery-dependent and -independent age/length compositions, and harvest data. Our results suggest that for cisco in Thunder Bay, data-limitations related to lack of size-composition data over the size range for which cisco growth is rapid resulted in difficulty estimating relative year-class strength within a SCSA. This led to parameter confounding and ultimately the inability to estimate natural mortality within a SCSA. This hampered the utility of a SCSA model in comparison with a SCAA model when age-composition data were available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2018.09.014","usgsCitation":"Fisch, N.C., Bence, J., Myers, J., Berglund, E.K., and Yule, D., 2019, A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario: Fisheries Research, v. 209, p. 86-100, https://doi.org/10.1016/j.fishres.2018.09.014.","productDescription":"15 p.","startPage":"86","endPage":"100","ipdsId":"IP-096832","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":365245,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Ontario","city":"Thunder Bay","otherGeospatial":"Thunder Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.77159118652344,\n 48.57524422229134\n ],\n [\n -89.14237976074219,\n 48.48430069812584\n ],\n [\n -89.22203063964844,\n 48.43512327303003\n ],\n [\n -89.20829772949219,\n 48.30923114039641\n ],\n [\n -89.23919677734375,\n 48.307404328381544\n ],\n [\n -89.27627563476562,\n 48.2338208530875\n ],\n [\n -89.27902221679688,\n 48.204998474152255\n ],\n [\n -89.26666259765625,\n 48.193098793553624\n ],\n [\n -89.088134765625,\n 48.22284281261854\n ],\n [\n -88.934326171875,\n 48.30512072140391\n ],\n [\n -88.87115478515625,\n 48.3617240221937\n ],\n [\n -88.8409423828125,\n 48.40185599006367\n ],\n [\n -88.74206542968749,\n 48.55297816440071\n ],\n [\n -88.77159118652344,\n 48.57524422229134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fisch, Nicholas C","contributorId":216152,"corporation":false,"usgs":false,"family":"Fisch","given":"Nicholas","email":"","middleInitial":"C","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":765293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":765294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Jared T. 0009-0004-9362-8792","orcid":"https://orcid.org/0009-0004-9362-8792","contributorId":44055,"corporation":false,"usgs":false,"family":"Myers","given":"Jared T.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":765295,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berglund, Eric K.","contributorId":115926,"corporation":false,"usgs":false,"family":"Berglund","given":"Eric","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":765296,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yule, Daniel 0000-0002-0117-5115 dyule@usgs.gov","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":139532,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227788,"text":"70227788 - 2019 - Main stem and off-channel habitat use by juvenile Chinook salmon in a sub-Arctic riverscape","interactions":[],"lastModifiedDate":"2022-01-31T14:38:35.685981","indexId":"70227788","displayToPublicDate":"2019-01-04T08:28:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Main stem and off-channel habitat use by juvenile Chinook salmon in a sub-Arctic riverscape","docAbstract":"Tephra from the early Hawaiian fountaining episodes of the ongoing eruption of Pu'u 'Ō'ō in the East Rift Zone (ERZ) of Kīlauea provides an opportunity to study the vesicle microtextures of pyroclasts erupted from a single vent over a prolonged period of time. We report the results of microtextural analysis of pyroclasts from five of Pu'u 'Ō'ō's high (>200 m) Hawaiian fountaining episodes (episodes 32, 37, 40, 44 and 45) erupted during 1985–1986. This analysis was carried out to constrain the parameters that led to large variations in fountain height at Pu'u 'Ō'o, and the extent to which pyroclast residence times in the fountain modified microtextures. Our results confirm the finding of Stovall et al., 2011, Stovall et al., 2012 that pyroclasts from a single Hawaiian fountain can vary greatly in texture (from bubbly to foamy), and have vesicle volume densities (Nmv) and vesicle to melt ratios (VG/VL) that vary by an order of magnitude. This range in vesicle texture and population is due to extensive growth and coalescence of vesicles within the fountain after fragmentation. Only one pyroclast from four of five episodes was found to have textures interpreted as indicative of the vesicle population near the moment of fragmentation: bubbly texture, high density (typically >500 kg m−3), high Nmv (2.2 × 106 to 4.4 × 106), and low VG/VL of 2.06 to 4.65. We demonstrate a linear correlation between Δ(VG/VL) and peak fountain height across a range of Hawaiian fountains from Kilauea. This correlation could be used to infer peak heights of unobserved Hawaiian fountaining eruptions after further testing using well-recorded events.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.11.011","usgsCitation":"Holt, S.J., Carey, R.J., Houghton, B.F., Orr, T.R., McPhie, J., and Feig, S., 2019, Eruption and fountaining dynamics of selected 1985–1986 high fountaining episodes at Kīlauea volcano, Hawai'i, from quantitative vesicle microtexture analysis: Journal of Volcanology and Geothermal Research, v. 369, p. 21-34, https://doi.org/10.1016/j.jvolgeores.2018.11.011.","productDescription":"14 p.","startPage":"21","endPage":"34","ipdsId":"IP-093103","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":460531,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2018.11.011","text":"Publisher Index Page"},{"id":360795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.31646728515625,\n 19.263507501734075\n ],\n [\n -155.03562927246094,\n 19.263507501734075\n ],\n [\n -155.03562927246094,\n 19.46432633709043\n ],\n [\n -155.31646728515625,\n 19.46432633709043\n ],\n [\n -155.31646728515625,\n 19.263507501734075\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"369","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Holt, S. J.","contributorId":211902,"corporation":false,"usgs":false,"family":"Holt","given":"S.","email":"","middleInitial":"J.","affiliations":[{"id":38349,"text":"University of Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":755183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, R. J. 0000-0003-2015-6419","orcid":"https://orcid.org/0000-0003-2015-6419","contributorId":211903,"corporation":false,"usgs":false,"family":"Carey","given":"R.","email":"","middleInitial":"J.","affiliations":[{"id":38349,"text":"University of Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":755184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Houghton, B. F.","contributorId":211904,"corporation":false,"usgs":false,"family":"Houghton","given":"B.","email":"","middleInitial":"F.","affiliations":[{"id":38350,"text":"University of Hawaii at Manoa, USA","active":true,"usgs":false}],"preferred":false,"id":755185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":755182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McPhie, J.","contributorId":211905,"corporation":false,"usgs":false,"family":"McPhie","given":"J.","affiliations":[{"id":38349,"text":"University of Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":755186,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Feig, S.","contributorId":211906,"corporation":false,"usgs":false,"family":"Feig","given":"S.","email":"","affiliations":[{"id":38349,"text":"University of Tasmania, Australia","active":true,"usgs":false}],"preferred":false,"id":755187,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203811,"text":"70203811 - 2019 - Satellite tracking of hawksbill turtles nesting at Buck Island Reef National Monument, US Virgin Islands: Inter-nesting and foraging period movements and migrations","interactions":[],"lastModifiedDate":"2019-10-09T15:32:49","indexId":"70203811","displayToPublicDate":"2019-01-01T13:58:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Satellite tracking of hawksbill turtles nesting at Buck Island Reef National Monument, US Virgin Islands: Inter-nesting and foraging period movements and migrations","docAbstract":"To conserve imperiled marine species, an understanding of high-density use zones is necessary prior to designing and evaluating management strategies that improve their survival. We satellite-tracked turtles captured after nesting at Buck Island ReefNational Monument (BIRNM), St. Croix, US Virgin Islands to determine habitat-use patterns of endangered adult female hawksbills (Eretmochelys imbricata). For 31 turtles captured between 2011 and 2014, switching state-space modeling and home range analyses showed that inter-nesting (IN) core-use areas (i.e., 50% kernel density estimates [KDEs]) were 9.6 to 77.7 km2 in area, occupied for 21 to 85 days, and in shallow water(21 of 26 centroids > −10 m). The IN zones overlapped with areas both within the protected borders of BIRNM, and outside BIRNM (32% of turtle-tracking days outside during IN). Turtles migrated to their foraging grounds between July and October with path lengths ranging from 52 to 3524 km; foraging areas included 14 countries. Core-use foraging areas (50% KDEs) where turtles took up residence were 6.3 to 95.4 km2, occupied for 22 to 490 days, with mean centroid depth − 66 m. Our results show previously unknown habitat-use patterns and highlight concentrated areas of use both within and adjacent to a US protected area during the breeding season. Further, our results clearly demonstrate the need for international conservation to protect hawksbills, as migrating turtles crossed between two and eight different jurisdictions. Our results provide critical spatial and temporal information for managers charged with designing strategies to minimize human impact to and maximize survival for this globally imperiled species.
The National Park Service’s (NPS) Resource Protection Branch (RPB) works with parks under the authority of the System Unit Resource Protection Act (SURPA) and the Oil Pollution Act, among others, to conduct damage assessment and restoration activities for NPS resources that have been injured. Funds used for restoration support jobs in local economies across the Nation. This report demonstrates the economic impacts associated with RPB-administered restoration projects through an analysis of small-scale (less than $1,000,000 spent per project) and large-scale (more than $1,000,000 spent per project) projects. Using a national-level economic input-output model, direct and secondary jobyears, labor income, value added, and total economic output were estimated for a sample of restoration projects; impacts from these sampled projects were used to estimate average economicimpacts-per-million-dollars-spent on RPB restoration. In 2017 RPB administered 49 small-scale projects; expenditures for these projects ranged in cost from $200 to $800,000 and totaled $1,686,000 ($923,000 in cultural resource projects, $618,000 in natural resource projects, and $145,000 in facilities projects). Based on the economic-impacts-per million estimates, small-scale RPB projects were found to support an estimated total of 29 job-years, $1,963,000 in labor income, $2,690,000 in value added, and $4,458,000 in total economic output within the national economy in 2017. Economic impacts were also calculated for two large-scale projects: one a $3,900,000 (2017$) hillside stabilization project and the other a $5,574,000 (2017$) ferries (two) fabrication project.
","language":"English","publisher":"National Park Service","collaboration":"National Park Service","usgsCitation":"Cullinane Thomas, C., Van Gilder, N., and VanMouwerik, M., 2019, Economic Impacts of Restoration in National Parks, 18 p.","productDescription":"18 p.","ipdsId":"IP-096843","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":363902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363408,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2258766"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Gilder, Noah","contributorId":215219,"corporation":false,"usgs":false,"family":"Van Gilder","given":"Noah","email":"","affiliations":[{"id":39207,"text":"Department of the Interior","active":true,"usgs":false}],"preferred":false,"id":761847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"VanMouwerik, Mark","contributorId":215220,"corporation":false,"usgs":false,"family":"VanMouwerik","given":"Mark","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":761848,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200539,"text":"70200539 - 2019 - Using remote sensing to quantify ecosystem site potential community structure and deviation in the Great Basin, United States","interactions":[],"lastModifiedDate":"2024-05-17T15:01:47.161889","indexId":"70200539","displayToPublicDate":"2019-01-01T11:35:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using remote sensing to quantify ecosystem site potential community structure and deviation in the Great Basin, United States","docAbstract":"The semi-arid Great Basin region in the Northwest U.S. is impacted by a suite of change agents including fire, grazing, and climate variability to which native vegetation can have low resilience and resistance. Assessing ecosystem condition in relation to these change agents is difficult due to a lack of a consistent and objective Site Potential (SP) information of the conditions biophysically possible at each site. Our objectives were to assess and quantify patterns in ecosystem condition, based on actual fractional component cover and a SP map and to evaluate drivers of change. We used long-term 90th percentile Landsat NDVI(Normalized Difference Vegetation Index) and biophysical variables to produce a map of SP. Ecosystem condition was assessed using two methods, first we integrated fractional components into an index which was regressed against SP. Regression confidence intervals were used to segment the study area into normal, over-, and under-performing relative to SP. Next, the relationships between SP and fractional component cover produced SP expected component cover, from which we mapped the actual cover deviation. Much of the study area is within the range of conditions expected by the SP model, but degraded conditions are more common than those above SP expectations. We found that shrub cover deviation is more positive at higher elevation, while herbaceous cover deviation has the opposite pattern, supporting the hypothesis that more resistant and resilient sites are less likely to change from the shrub dominated legacy. Another key finding was that regions with significant annual herbaceous invasions tend to have lower than expected bare ground and shrub cover.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2018.09.037","usgsCitation":"Rigge, M.B., Homer, C.G., Wylie, B.K., Gu, Y., Shi, H., Xian, G.Z., Meyer, D.K., and Bunde, B., 2019, Using remote sensing to quantify ecosystem site potential community structure and deviation in the Great Basin, United States: Ecological Indicators, v. 96, no. 1, p. 516-531, https://doi.org/10.1016/j.ecolind.2018.09.037.","productDescription":"16 p.","startPage":"516","endPage":"531","ipdsId":"IP-101049","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468010,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2018.09.037","text":"Publisher Index Page"},{"id":358741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","volume":"96","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8dde4b034bf6a7e4d89","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":749407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":749408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":749409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gu, Yingxin 0000-0002-3544-1856","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":209983,"corporation":false,"usgs":false,"family":"Gu","given":"Yingxin","affiliations":[],"preferred":false,"id":749410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":749411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":749412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, Debra K. 0000-0002-8841-697X dkmeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":3145,"corporation":false,"usgs":true,"family":"Meyer","given":"Debra","email":"dkmeyer@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":749414,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bunde, Brett 0000-0003-0228-779X brett.bunde.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":198821,"corporation":false,"usgs":true,"family":"Bunde","given":"Brett","email":"brett.bunde.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":749413,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201723,"text":"70201723 - 2019 - Conceptualizing ecological responses to dam removal: If you remove it, what's to come?","interactions":[],"lastModifiedDate":"2020-09-01T14:01:11.187775","indexId":"70201723","displayToPublicDate":"2019-01-01T11:20:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Conceptualizing ecological responses to dam removal: If you remove it, what's to come?","docAbstract":"One of the desired outcomes of dam decommissioning and removal is the recovery of aquatic and riparian ecosystems. To investigate this common objective, we synthesized information from empirical studies and ecological theory into conceptual models that depict key physical and biological links driving ecological responses to removing dams. We define models for three distinct spatial domains: upstream of the former reservoir, within the reservoir, and downstream of the removed dam. Emerging from these models are response trajectories that clarify potential pathways of ecological transitions in each domain. We illustrate that the responses are controlled by multiple causal pathways and feedback loops among physical and biological components of the ecosystem, creating recovery trajectories that are dynamic and nonlinear. In most cases, short-term effects are typically followed by longer-term responses that bring ecosystems to new and frequently predictable ecological condition, which may or may not be similar to what existed prior to impoundment.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biy152","usgsCitation":"Bellmore, J., Pess, G.R., Duda, J.J., O'Connor, J., East, A.E., Foley, M.M., Wilcox, A.C., Major, J.J., Shafroth, P.B., Morley, S.A., Magirl, C.S., Anderson, C.W., Evans, J.E., Torgersen, C.E., and Craig, L.S., 2019, Conceptualizing ecological responses to dam removal: If you remove it, what's to come?: BioScience, v. 69, no. 1, p. 26-39, https://doi.org/10.1093/biosci/biy152.","productDescription":"14 p.","startPage":"26","endPage":"39","ipdsId":"IP-076483","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biy152","text":"Publisher Index Page"},{"id":360721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-10","publicationStatus":"PW","scienceBaseUri":"5c5022c4e4b0708288f7e80c","contributors":{"authors":[{"text":"Bellmore, J. Ryan jbellmore@usgs.gov","contributorId":4527,"corporation":false,"usgs":true,"family":"Bellmore","given":"J. Ryan","email":"jbellmore@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":755008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":755007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":755009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":755010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":755011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":755006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilcox, Andrew C. 0000-0002-6241-8977","orcid":"https://orcid.org/0000-0002-6241-8977","contributorId":195613,"corporation":false,"usgs":false,"family":"Wilcox","given":"Andrew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":755012,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":755013,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":755014,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":755020,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755015,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755016,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Evans, James E.","contributorId":194435,"corporation":false,"usgs":false,"family":"Evans","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":755017,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","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":755018,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Craig, Laura S.","contributorId":195611,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":755019,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70227889,"text":"70227889 - 2019 - Improving conservation policy with genomics: A guide to integrating adaptive potential into U.S. Endangered Species Act decisions for conservation practitioners and geneticists","interactions":[],"lastModifiedDate":"2022-02-01T16:53:35.256014","indexId":"70227889","displayToPublicDate":"2019-01-01T10:44:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Improving conservation policy with genomics: A guide to integrating adaptive potential into U.S. Endangered Species Act decisions for conservation practitioners and geneticists","docAbstract":"Rapid environmental change makes adaptive potential—the capacity of populations to evolve genetically based changes in response to selection—more important than ever for long-term persistence of at-risk species. At the same time, advances in genomics provide unprecedented power to test for and quantify adaptive potential, enabling consideration of adaptive potential in estimates of extinction risk and laws protecting endangered species. The U.S. Endangered Species Act (ESA) is one of the most powerful environmental laws in the world, but so far, the full potential of genomics in ESA listing and recovery decisions has not been realized by the federal agencies responsible for implementing the ESA or by conservation geneticists. The goal of our paper is to chart a path forward for integrating genomics into ESA decision making to facilitate full consideration of adaptive potential in evaluating long-term risk of extinction. For policy makers, managers, and other conservation practitioners, we outline why adaptive potential is important for population persistence and what genomic tools are available for quantifying it. For conservation geneticists, we discuss how federal agencies can integrate information on the effect of adaptive potential on extinction risk—and the related uncertainty—into decisions, and suggest next steps for advancing understanding of the effect of adaptive potential on extinction risk. The mechanisms and consequences of adaptation are incredibly complex, and we may never have a complete understanding of adaptive potential for any organism. Nevertheless, we argue that the best available evidence regarding adaptive potential should be incorporated by federal agencies into modeling and decision making processes now, while at the same time conserving genome-wide variation and striving for a deeper understanding of adaptive potential and its effects on population persistence to improve decision-making into the future.","language":"English","publisher":"Springer","doi":"10.1007/s10592-018-1096-1","usgsCitation":"Funk, W., Forester, B.R., Converse, S.J., Darst, C., and Morey, S., 2019, Improving conservation policy with genomics: A guide to integrating adaptive potential into U.S. Endangered Species Act decisions for conservation practitioners and geneticists: Conservation Genetics, v. 20, p. 115-134, https://doi.org/10.1007/s10592-018-1096-1.","productDescription":"20 p.","startPage":"115","endPage":"134","ipdsId":"IP-093259","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","noUsgsAuthors":false,"publicationDate":"2018-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Funk, W.C.","contributorId":29934,"corporation":false,"usgs":true,"family":"Funk","given":"W.C.","email":"","affiliations":[],"preferred":false,"id":832470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forester, Brenna R.","contributorId":261215,"corporation":false,"usgs":false,"family":"Forester","given":"Brenna","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":832471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":832472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darst, Catherine","contributorId":273035,"corporation":false,"usgs":false,"family":"Darst","given":"Catherine","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":832473,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morey, Steve","contributorId":147048,"corporation":false,"usgs":false,"family":"Morey","given":"Steve","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":832474,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227618,"text":"70227618 - 2019 - Guadalupe Bass flow-ecology relationships; with emphasis on the impact of flow on recruitment","interactions":[],"lastModifiedDate":"2024-03-22T15:45:37.362867","indexId":"70227618","displayToPublicDate":"2019-01-01T10:32:05","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"144-2019","title":"Guadalupe Bass flow-ecology relationships; with emphasis on the impact of flow on recruitment","docAbstract":"Guadalupe Bass Micropterus treculii is an economically and ecologically important black bass species endemic to the Edwards Plateau ecoregion and the lower portions of the Colorado River in central Texas. It is considered a fluvial specialist and as such, there are concerns that the increasing demands being placed upon the water resources of central Texas by growing human populations have the potential to negatively impact Guadalupe Bass populations. Therefore, this study assessed the relationship between Guadalupe Bass growth, feeding ecology, and streamflow. Sagittal otoliths were removed from Guadalupe Bass collected from throughout their range during 2015-2017 and used to estimate the age and back-calculate the growth trajectory of each individual. Additionally, young-of-year (YOY) Guadalupe Bass were collected every 10-14 days from two second-order streams, the North Llano River and South Llano River, in the Colorado Basin on the Edwards Plateau. Stomach contents of these individuals were identified and the effect of streamflow on the occurrence of the taxa comprising the stomach contents assessed.
Guadalupe Bass growth was greater in the Colorado and Guadalupe River basins, independent of stream order, and tended to increase with increasing stream order within a basin. Growth was higher in higher stream orders and during years with stable and lower spring and summer monthly median flows, lower minimum and maximum flows, slower rise and fall rates, and higher baseflows. Growth was not influenced by years with higher monthly median flows in winter. These results would seem to contradict previous research, but more likely represent a fuller picture of how Guadalupe Bass respond to flow conditions. The disagreement between the current study and past studies seem to be attributable, at least in part, to the fact that previous studies were conducted during a period of extensive drought, while the current study was conducted during relatively wet conditions. Taken together with previous studies, the current study suggests that Guadalupe Bass growth is sensitive to flow conditions and is lower in years with flow conditions that fall outside a basin- and stream order-specific optimal range for the species.
A total of 21 unique taxonomic groups were recovered from the stomachs of YOY Guadalupe Bass collected from the North Llano River and South Llano River. Aquatic insects, especially larval mayflies (Ephemeroptera), damselflies (Odanata: Zygoptera), and caddisflies (Trichoptera), were the most frequently encountered taxa. While there was no difference between the two rivers in stomach content composition, there was a strong longitudinal gradient in both systems with aquatic insects predominating at upstream sample sites and fishes being more common at downstream sites. Stream discharge during the 24 hours prior to collection did not have any influence on the probability of a taxa being found in Guadalupe Bass stomachs.
The results of this study support efforts to manage Guadalupe Bass populations at a sub-watershed scale and suggests that populations occupying the same stream order within a basin are likely to have similar responses to annual flow conditions. In addition, these results indicate that the lower Colorado River population may inhabit a unique set of conditions that has supported the development of a trophy Guadalupe Bass fishery. Further, this study highlights the need to incorporate a sufficient range of annual flow conditions to ensure that the influence of stream flow on fish growth is adequately assessed. While interannual variation in growth rates seem to be capable of serving as a proxy for recruitment and year-class strength, long-term monitoring of recruitment paired with assessment of growth is necessary to further clarify the relationship between population density, flow regime, recruitment and growth and allow the construction of predictive models.
No abstract available.
","language":"English","publisher":"The Wildlife Society","usgsCitation":"Organ, J.F., Mahoney, S.P., and Geist, V., 2019, Our precious wildlife resources: Further thoughts on the North American model: The Wildlife Professional, v. 13, no. 1, p. 30-33.","productDescription":"4 p.","startPage":"30","endPage":"33","ipdsId":"IP-101857","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":482338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":189047,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":928124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahoney, Shane P.","contributorId":199084,"corporation":false,"usgs":false,"family":"Mahoney","given":"Shane","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":928125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geist, Valerius","contributorId":351189,"corporation":false,"usgs":false,"family":"Geist","given":"Valerius","affiliations":[{"id":83935,"text":"University of Calgary (Emeritus)","active":true,"usgs":false}],"preferred":false,"id":928126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216093,"text":"70216093 - 2019 - Relationships between wildfire burn severity, cavity-nesting bird assemblages and habitat in an eastern ponderosa pine forest","interactions":[],"lastModifiedDate":"2020-11-05T15:05:12.51435","indexId":"70216093","displayToPublicDate":"2019-01-01T08:54:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between wildfire burn severity, cavity-nesting bird assemblages and habitat in an eastern ponderosa pine forest","docAbstract":"Historically, eastern ponderosa pine (Pinus ponderosa) forests were described as sparse patches of old-growth trees maintained by frequent, low-severity fires; however, in recent decades, there have been a number of large mixed-severity wildfires throughout the range of these forests. Wildlife responses to severe fire disturbance in eastern ponderosa pine forests are not well understood. Our study investigates how cavity-nesting bird species in an eastern ponderosa pine forest are impacted by burn severity. The objectives of our study were to: (1) identify the community composition of cavity-nesting birds in a 27 y old burn of mixed severity, (2) assess how habitat variables important to cavity-nesting birds differ in the mixed-severity fire, and (3) determine what habitat variables best predict bird occurrence 27 y after mixed-severity fire. We surveyed 56 sites across four burn severity classes, ranging from unburned to severely burned forest, in the Pine Ridge region of Nebraska. We measured multiple habitat characteristics (tree and snag diameter at breast height (DBH), coarse woody debris (CWD), tree and snag density, shrub height, and shrub cover) in May–August 2016 and conducted bird count surveys between 25 May and 8 June 2016. Cavity-nesting bird species' occurrence varied among the burn severity variables. Burn severity class (unburned, low severity, moderate severity, high severity) was a significant predictor of habitat characteristics for cavity-nesting birds, including tree density, snag density, mean snag DBH, variance in DBH, and CWD, which also was the best indicator of cavity-nesting bird community composition. We report evidence that mixed-severity wildfires in eastern ponderosa pine forests create variation in habitat characteristics and cavity-nesting bird occurrence.
","language":"English","publisher":"BioOne","doi":"10.1674/0003-0031-181.1.1","usgsCitation":"Keele, E.C., Donovan, V.M., Roberts, C.P., Nodskov, S.M., Wonkka, C., Allen, C.R., Powell, L., Wedin, D.A., Angeler, D., and Twidwell, D., 2019, Relationships between wildfire burn severity, cavity-nesting bird assemblages and habitat in an eastern ponderosa pine forest: American Midland Naturalist, v. 18, no. 16, p. 1-17, https://doi.org/10.1674/0003-0031-181.1.1.","productDescription":"17 p.","startPage":"1","endPage":"17","ipdsId":"IP-091278","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":380191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Fort Robinson State Park, Peterson Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.6505126953125,\n 42.63118026854378\n ],\n [\n -103.40229034423828,\n 42.63118026854378\n ],\n [\n -103.40229034423828,\n 42.725325908230396\n ],\n [\n -103.6505126953125,\n 42.725325908230396\n ],\n [\n -103.6505126953125,\n 42.63118026854378\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"16","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keele, E. C.","contributorId":244489,"corporation":false,"usgs":false,"family":"Keele","given":"E.","email":"","middleInitial":"C.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, V. M.","contributorId":244281,"corporation":false,"usgs":false,"family":"Donovan","given":"V.","email":"","middleInitial":"M.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, C. P.","contributorId":189791,"corporation":false,"usgs":false,"family":"Roberts","given":"C.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":804046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nodskov, S. M.","contributorId":244490,"corporation":false,"usgs":false,"family":"Nodskov","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wonkka, C. L.","contributorId":244491,"corporation":false,"usgs":false,"family":"Wonkka","given":"C. L.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","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":804049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powell, L.","contributorId":244283,"corporation":false,"usgs":false,"family":"Powell","given":"L.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804050,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wedin, David A.","contributorId":17898,"corporation":false,"usgs":true,"family":"Wedin","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":804143,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Angeler, D. G.","contributorId":240686,"corporation":false,"usgs":false,"family":"Angeler","given":"D. G.","affiliations":[{"id":12665,"text":"University of Cape Town","active":true,"usgs":false}],"preferred":false,"id":804051,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Twidwell, D.","contributorId":244285,"corporation":false,"usgs":false,"family":"Twidwell","given":"D.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":804052,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70215268,"text":"70215268 - 2019 - Stable pack abundance and distribution in a harvested wolf population","interactions":[],"lastModifiedDate":"2020-10-14T13:53:14.524014","indexId":"70215268","displayToPublicDate":"2018-12-27T08:50:06","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":"Stable pack abundance and distribution in a harvested wolf population","docAbstract":"Harvesting gray wolves (Canis lupus) could affect the abundance and distribution of packs, but the frequency of change in pack occurrence (i.e., turnover) and relative effects of harvest compared to environmental factors is unclear. We used noninvasive genetic sampling, hunter surveys, and occupancy models to evaluate the effect of harvest on occurrence and turnover of packs in a population of wolves managed with intensive harvest in the Canadian Rocky Mountains, 2012–2014. We tested 2 alternative hypotheses: the abundance and distribution of wolf packs were dynamic because of harvest or the abundance and distribution of wolf packs were generally stable regardless of harvest. We found the mean annual probability for wolf pack occupancy ranged 0.72–0.74 and the estimated distribution of wolf packs was consistent over time, 2012–2014. Our top model indicated wolf pack occupancy was positively associated with forest cover and the probability of detecting a wolf pack was positively associated with the intensity of harvest for wolves in that area. We observed frequent turnover of individuals within packs that were genetically sampled consecutive years but not of entire packs. Because turnover of packs occurred infrequently during our study, we could not reject our hypothesis that occurrence of packs was generally stable in a harvested population of wolves. Our results suggest environmental factors have a stronger effect than harvest on the abundance and distribution of wolf packs in southwestern Alberta, but harvest appears to strongly influence turnover of individuals within packs. We hypothesize local dispersal from within the study area and neighboring packs on the periphery of the study area helped promote pack stability. © 2018 The Wildlife Society.
Anthropogenic development of floodplains and alteration to natural hydrological regimes have resulted in extensive loss of off-channel habitat. Interest has grown in restoring these habitats as an effective conservation strategy for numerous aquatic species. This study developed a process to reproducibly identify areas of former stream meanders to assist future off-channel restoration site selections. Three watersheds in Iowa and Minnesota where off-channel restorations are currently being conducted to aid the conservation of the Topeka Shiner (Notropis topeka) were selected as the study area. Floodplain depressions were identified with LiDAR-derived digital elevation models, and their morphologic and topographic characteristics were described. Classification tree models were developed to distinguish relic streams and oxbows from other landscape features. All models demonstrated a strong ability to distinguish between target and non-target features with area under the receiver operator curve (AUC) values ≥ 0.82 and correct classification rates ≥ 0.88. Solidity, concavity, and mean height above channel metrics were among the first splits in all trees. To compensate for the noise associated with the final model designation, features were ranked by their conditional probability. The results of this study will provide conservation managers with an improved process to identify candidate restoration sites.
","language":"English","publisher":"MDPI","doi":"10.3390/rs11010012","usgsCitation":"Zambory, C.L., Ellis, H., Pierce, C., Roe, K., Weber, M.J., Schilling, K.E., and Young, N.C., 2019, The development of a GIS methodology to identify oxbows and former stream meanders from LiDAR-derived digital elevation models: Remote Sensing, v. 11, no. 1, 12, 16 p., https://doi.org/10.3390/rs11010012.","productDescription":"12, 16 p.","ipdsId":"IP-099039","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11010012","text":"Publisher Index Page"},{"id":395216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","otherGeospatial":"Boone River watershed, North Raccoon River watershed, Rock River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.45996093749999,\n 41.11246878918088\n ],\n [\n -93.01025390625,\n 41.11246878918088\n ],\n [\n -93.01025390625,\n 44.36313311380771\n ],\n [\n -96.45996093749999,\n 44.36313311380771\n ],\n [\n -96.45996093749999,\n 41.11246878918088\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Zambory, Courtney L.","contributorId":264754,"corporation":false,"usgs":false,"family":"Zambory","given":"Courtney","email":"","middleInitial":"L.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Harvest","contributorId":273018,"corporation":false,"usgs":false,"family":"Ellis","given":"Harvest","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":832462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roe, Kevin J.","contributorId":264758,"corporation":false,"usgs":false,"family":"Roe","given":"Kevin J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Michael J.","contributorId":83799,"corporation":false,"usgs":true,"family":"Weber","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":832464,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schilling, Keith E.","contributorId":106429,"corporation":false,"usgs":false,"family":"Schilling","given":"Keith","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":832465,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Nathan C.","contributorId":273025,"corporation":false,"usgs":false,"family":"Young","given":"Nathan","email":"","middleInitial":"C.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":832466,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201645,"text":"70201645 - 2019 - Efficient hydrogeological characterization of remote stream corridors using drones","interactions":[],"lastModifiedDate":"2019-01-28T08:22:18","indexId":"70201645","displayToPublicDate":"2018-12-19T15:25:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Efficient hydrogeological characterization of remote stream corridors using drones","docAbstract":"This project demonstrates the successful use of small unoccupied aircraft system (sUASs) for hydrogeological characterization of a remote stream reach in a rugged mountain terrain. Thermal infrared, visual imagery, and derived digital surface models are used to inform conceptual models of groundwater/surface‐water exchange and efficiently geolocate zones of preferential groundwater discharge that can be quantified using various ground‐based methodology.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13332","usgsCitation":"Briggs, M.A., Dawson, C.B., Holmquist-Johnson, C., Williams, K.H., and Lane, J.W., 2019, Efficient hydrogeological characterization of remote stream corridors using drones: Hydrological Processes, v. 33, no. 2, p. 316-319, https://doi.org/10.1002/hyp.13332.","productDescription":"4 p.","startPage":"316","endPage":"319","ipdsId":"IP-102696","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1491213","text":"Publisher Index Page"},{"id":360579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-19","publicationStatus":"PW","scienceBaseUri":"5c1b66e5e4b0708288c71d28","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":754691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dawson, Cian B. cbdawson@usgs.gov","contributorId":1890,"corporation":false,"usgs":true,"family":"Dawson","given":"Cian","email":"cbdawson@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":754692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmquist-Johnson, Christopher 0000-0002-2782-7687 h-johnsonc@usgs.gov","orcid":"https://orcid.org/0000-0002-2782-7687","contributorId":168648,"corporation":false,"usgs":true,"family":"Holmquist-Johnson","given":"Christopher","email":"h-johnsonc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":754693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Kenneth H. 0000-0002-3568-1155","orcid":"https://orcid.org/0000-0002-3568-1155","contributorId":176791,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":754694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":754695,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204242,"text":"70204242 - 2019 - Estimating occurrence, prevalence, and detection of amphibian pathogens: Insights from occupancy models","interactions":[],"lastModifiedDate":"2019-07-16T10:40:25","indexId":"70204242","displayToPublicDate":"2018-12-19T10:26:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occurrence, prevalence, and detection of amphibian pathogens: Insights from occupancy models","docAbstract":"Understanding the distribution of pathogens across landscapes and their prevalence within host populations is a common aim of wildlife managers. Despite the need for unbiased estimates of pathogen occurrence and prevalence for planning effective management interventions, many researchers fail to account for imperfect pathogen detection. Instead raw data are often reported, which may lead to ineffective, or even detrimental, management actions. We illustrate the utility of occupancy models for generating unbiased estimates of disease parameters by 1) providing a written tutorial describing how to fit these models in Program PRESENCE and 2) presenting a case study with the pathogen ranavirus. We analyzed ranavirus detection data from a wildlife refuge (Maryland, US) using occupancy modeling, which yields unbiased estimates of pathogen occurrence and prevalence. We found ranavirus prevalence was underestimated by up to 30% if imperfect pathogen detection was ignored. The unbiased estimate of ranavirus prevalence in larval wood frog (Lithobates sylvaticus; 0.73) populations was higher than in larval spotted salamander (Ambystoma maculatum; 0.56) populations. In addition, the odds of detecting ranavirus in tail samples were 6.7 times higher than detecting ranavirus in liver samples. Therefore, tail samples presented a nonlethal sampling method for ranavirus that may be able to detect early (nonsystemic) infections.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-02-042","usgsCitation":"Mosher, B.A., Brand, A., Wiewel, A., Miller, D., Gray, M., Miller, D.L., and Campbell Grant, E.H., 2019, Estimating occurrence, prevalence, and detection of amphibian pathogens: Insights from occupancy models: Journal of Wildlife Diseases, v. 55, no. 3, p. 563-575, https://doi.org/10.7589/2018-02-042.","productDescription":"13 p.","startPage":"563","endPage":"575","ipdsId":"IP-074863","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":365579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Patuxent Research Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.82807922363281,\n 39.06571441680544\n ],\n [\n -76.82275772094727,\n 39.06371515917004\n ],\n [\n -76.82842254638672,\n 39.05958318062962\n ],\n [\n -76.82292938232422,\n 39.0518517325806\n ],\n [\n -76.82533264160156,\n 39.0487855791302\n ],\n [\n -76.8244743347168,\n 39.04438608298337\n ],\n [\n -76.83134078979492,\n 39.04065296228084\n ],\n [\n -76.82481765747069,\n 39.03371950048907\n ],\n [\n -76.82172775268555,\n 39.013715318365406\n ],\n [\n -76.81159973144531,\n 39.00904686141452\n ],\n [\n -76.80610656738281,\n 39.01144782062009\n ],\n [\n -76.80438995361328,\n 39.016649619293\n ],\n [\n -76.79924011230469,\n 39.01398207802642\n ],\n [\n -76.79683685302734,\n 39.01798335219163\n ],\n [\n -76.78104400634766,\n 39.022117764305015\n ],\n [\n -76.77572250366211,\n 39.028652309716236\n ],\n [\n -76.75718307495117,\n 39.0374529875311\n ],\n [\n -76.75134658813477,\n 39.03558626866692\n ],\n [\n -76.7398452758789,\n 39.04638588792801\n ],\n [\n -76.73709869384766,\n 39.05518435709179\n ],\n [\n -76.72164916992188,\n 39.07291127545158\n ],\n [\n -76.72525405883789,\n 39.07984089017707\n ],\n [\n -76.72319412231445,\n 39.08703630823101\n ],\n [\n -76.7530632019043,\n 39.08783575382141\n ],\n [\n -76.74568176269531,\n 39.08663658203791\n ],\n [\n -76.74808502197266,\n 39.08290569500107\n ],\n [\n -76.75975799560547,\n 39.08397168286113\n ],\n [\n -76.76422119140625,\n 39.08050716342113\n ],\n [\n -76.7705726623535,\n 39.08543738986714\n ],\n [\n -76.76799774169922,\n 39.091832845856075\n ],\n [\n -76.78258895874023,\n 39.08890166718027\n ],\n [\n -76.80490493774414,\n 39.092499005837915\n ],\n [\n -76.83065414428711,\n 39.06838000557286\n ],\n [\n -76.82807922363281,\n 39.06571441680544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mosher, B. 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Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.","language":"English","publisher":"ESA","doi":"10.1002/ecy.2583","usgsCitation":"Marino, J.A., Peacor, S.D., Bunnell, D., Vanderploeg, H.A., Pothoven, S.A., Elgin, A.K., Bence, J., Jiao, J., and Ionides, E.L., 2019, Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data: Ecology, v. 100, no. 3, Article e02583, 14 p., https://doi.org/10.1002/ecy.2583.","productDescription":"Article e02583, 14 p.","ipdsId":"IP-096682","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488820,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/148243","text":"External Repository"},{"id":364584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marino, John A.","contributorId":216168,"corporation":false,"usgs":false,"family":"Marino","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":17862,"text":"Bradley University","active":true,"usgs":false}],"preferred":false,"id":764074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacor, Scott D.","contributorId":216169,"corporation":false,"usgs":false,"family":"Peacor","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":764073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderploeg, Henry A.","contributorId":195891,"corporation":false,"usgs":false,"family":"Vanderploeg","given":"Henry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":764076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":764077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elgin, Ashley K.","contributorId":216170,"corporation":false,"usgs":false,"family":"Elgin","given":"Ashley","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":764078,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764079,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiao, J.","contributorId":216171,"corporation":false,"usgs":false,"family":"Jiao","given":"J.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764080,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ionides, Edward L.","contributorId":216172,"corporation":false,"usgs":false,"family":"Ionides","given":"Edward","email":"","middleInitial":"L.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":764081,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211910,"text":"70211910 - 2019 - Congruent population genetic structure but differing depths of divergence for three alpine stoneflies with similar ecology and geographic distributions","interactions":[],"lastModifiedDate":"2020-08-11T18:24:44.733885","indexId":"70211910","displayToPublicDate":"2018-12-17T13:14:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Congruent population genetic structure but differing depths of divergence for three alpine stoneflies with similar ecology and geographic distributions","docAbstract":"