Predictions of habitat suitability for invasive plant species can guide risk assessments at regional and national scales and inform early detection and rapid-response strategies at local scales. We present a general approach to invasive species modeling and mapping that meets objectives at multiple scales. Our methodology is designed to balance trade-offs between developing highly customized models for few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions and relied on human input based on natural history knowledge to further narrow the variable set for each species before developing habitat suitability models. To ensure efficiency, we used largely automated modeling approaches and human input only at key junctures. We explore and present uncertainty by using two alternative sources of background samples, including five statistical algorithms, and constructing model ensembles. We demonstrate the use and efficiency of the Software for Assisted Habitat Modeling [SAHM 2.1.2], a package in VisTrails, which performs the majority of the modeling analyses. Our workflow includes solicitation of expert feedback on model outputs such as spatial prediction results and variable response curves, and iterative improvement based on new data availability and directed field validation of initial model results. We highlight the utility of the models for decision-making at regional and local scales with case studies of two plant species that invade natural areas: fountain grass (Pennisetum setaceum) and goutweed (Aegopodium podagraria). By balancing model automation with human intervention, we can efficiently provide land managers with mapped predicted distributions for multiple invasive species to inform decisions across spatial scales.
We introduced a multilevel model of value shift to describe the changing social context of wildlife conservation. Our model depicts how cultural-level processes driven by modernization (e.g., increased wealth, education, and urbanization) affect changes in individual-level cognition that prompt a shift from domination to mutualism wildlife values. Domination values promote beliefs that wildlife should be used primarily to benefit humans, whereas mutualism values adopt a view that wildlife are part of one's social network and worthy of care and compassion. Such shifts create emergent effects (e.g., new interest groups) and challenges to wildlife management organizations (e.g., increased conflict) and dramatically alter the sociopolitical context of conservation decisions. Although this model is likely applicable to many modernized countries, we tested it with data from a 2017–2018 nationwide survey (mail and email panel) of 43,949 residents in the United States. We conducted hierarchical linear modeling and correlational analysis to examine relationships. Modernization variables had strong state-level effects on domination and mutualism. Higher levels of education, income, and urbanization were associated with higher percentages of mutualists and lower percentages of traditionalists, who have strong domination values. Values affected attitudes toward wildlife management challenges; for example, states with higher proportions of mutualists were less supportive of lethal control of wolves (Canis lupus) and had lower percentages of active hunters, who represent the traditional clientele of state wildlife agencies in the United States. We contend that agencies will need to embrace new strategies to engage and represent a growing segment of the public with mutualism values. Our model merits testing for application in other countries.
Sediment contamination of freshwater streams in urban areas is a recognized and growing concern. As a part of a comprehensive regional stream‐quality assessment, stream‐bed sediment was sampled from streams spanning a gradient of urban intensity in the Piedmont ecoregion of the southeastern United States. We evaluated relations between a broad suite of sediment contaminants (metals, current‐use pesticides, organochlorine pesticides, polychlorinated biphenyls, brominated diphenyl ethers, and polycyclic aromatic hydrocarbons), ambient sediment toxicity, and macroinvertebrate communities from 76 sites. Sediment toxicity was evaluated by conducting whole‐sediment laboratory toxicity testing with the amphipod Hyalella azteca (for 28 d) and the midge Chironomus dilutus (for 10 d). Approximately one‐third of the sediment samples were identified as toxic for at least one test species endpoint, although concentrations of contaminants infrequently exceeded toxicity benchmarks. Ratios of contaminant concentrations relative to their benchmarks, both individually and as summed benchmark quotients, were explored on a carbon‐normalized and a dry‐weight basis. Invertebrate taxa measures from ecological surveys tended to decline with increasing urbanization and with sediment contamination. Toxicity test endpoints were more strongly related to sediment contamination than invertebrate community measures were. Sediment chemistry and sediment toxicity provided moderate and weak, respectively, explanatory power for the similarity/dissimilarity of invertebrate communities. The results indicate that current single‐chemical sediment benchmarks may underestimate the effects from mixtures of sediment contaminants experienced by lotic invertebrates.
Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k-fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset (n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.
Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Global warming is thought to affect phytoplankton production both directly, by impacting their photosynthetic metabolism, and indirectly by modifying the physical environment in which they grow. In this respect, the Bermuda Atlantic Time-series Study (BATS) in the Sargasso Sea (North Atlantic gyre) provides a unique opportunity to explore effects of warming on phytoplankton production across the vast oligotrophic ocean regions because it is one of the few multidecadal records of measured net primary productivity (NPP). We analysed the time series of phytoplankton primary productivity at BATS site using machine learning techniques (ML) to show that increased water temperature over a 27-year period (1990–2016), and the consequent weakening of vertical mixing in the upper ocean, induced a negative feedback on phytoplankton productivity by reducing the availability of essential resources, nitrogen and light. The unbalanced availability of these resources with warming, coupled with ecological changes at the community level, is expected to intensify the oligotrophic state of open-ocean regions that are far from land-based nutrient sources.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-020-59989-y","usgsCitation":"D’Alelio, D., Rampone, S., Cusano, L.M., Morfino, V., Russo, L., Sanseverino, N., Cloern, J.E., and Lomas, M.W., 2020, Machine learning identifies a strong association between warming and reduced primary productivity in an oligotrophic ocean gyre: Scientific Reports, v. 10, 3287, 12 p., https://doi.org/10.1038/s41598-020-59989-y.","productDescription":"3287, 12 p.","ipdsId":"IP-111898","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-59989-y","text":"Publisher Index Page"},{"id":387061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North Atlantic Gyre","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.3359375,\n 23.885837699862005\n ],\n [\n -38.84765625,\n 28.613459424004414\n ],\n [\n -19.51171875,\n 34.016241889667015\n ],\n [\n -17.75390625,\n 41.11246878918088\n ],\n [\n -26.3671875,\n 47.754097979680026\n ],\n [\n -41.66015625,\n 46.6795944656402\n ],\n [\n -61.17187499999999,\n 39.639537564366684\n ],\n [\n -69.78515625,\n 35.31736632923788\n ],\n [\n -76.9921875,\n 31.203404950917395\n ],\n [\n -75.41015624999999,\n 26.902476886279832\n ],\n [\n -71.54296874999999,\n 23.563987128451217\n ],\n [\n -64.3359375,\n 23.885837699862005\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Alelio, Domenico","contributorId":260813,"corporation":false,"usgs":false,"family":"D’Alelio","given":"Domenico","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rampone, Salvatore","contributorId":260814,"corporation":false,"usgs":false,"family":"Rampone","given":"Salvatore","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cusano, Luigi Maria","contributorId":260815,"corporation":false,"usgs":false,"family":"Cusano","given":"Luigi","email":"","middleInitial":"Maria","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morfino, Valerio","contributorId":260816,"corporation":false,"usgs":false,"family":"Morfino","given":"Valerio","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russo, Luca","contributorId":260817,"corporation":false,"usgs":false,"family":"Russo","given":"Luca","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanseverino, Nadia","contributorId":260818,"corporation":false,"usgs":false,"family":"Sanseverino","given":"Nadia","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":818889,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lomas, Michael W.","contributorId":260819,"corporation":false,"usgs":false,"family":"Lomas","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":13692,"text":"Bigelow Laboratory for Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":818890,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70208834,"text":"70208834 - 2020 - Amphibian responses in the aftermath of extreme climate events","interactions":[],"lastModifiedDate":"2020-03-03T08:11:04","indexId":"70208834","displayToPublicDate":"2020-02-25T08:08:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Amphibian responses in the aftermath of extreme climate events","docAbstract":"Climate change-induced extinctions are estimated to eliminate one in six known species by the end of the century. One major factor that will contribute to these extinctions is extreme climatic events. Here, we show the ecological impacts of recent record warm air temperatures and simultaneous peak drought conditions in California. From 2008–2016, the southern populations of a wide-ranging endemic amphibian (the California newt, Taricha torosa) showed a 20% reduction to mean body condition and significant losses to variation in body condition linked with extreme climate deviations. However, body condition in northern populations remained relatively unaffected during this period. Range-wide population estimates of change to body condition under future climate change scenarios within the next 50 years suggest that northern populations will mirror the loss of body condition recently observed in southern populations. This change is predicated on latter 21st century climate deviations that resemble recent conditions in Southern California. Thus, the ecological consequences of climate change have already occurred across the warmer, drier regions of Southern California, and our results suggest that predicted climate vulnerable regions in the more mesic northern range likely will not provide climate refuge for numerous amphibian communities.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-020-60122-2","usgsCitation":"Bucciarelli, G.M., Clark, M., Delaney, K.S., Riley, S.P., Shaffer, H.B., Fisher, R.N., Honeycutt, R., and Kats, L.B., 2020, Amphibian responses in the aftermath of extreme climate events: Scientific Reports, v. 10, 3409, 7 p., https://doi.org/10.1038/s41598-020-60122-2.","productDescription":"3409, 7 p.","ipdsId":"IP-115754","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-60122-2","text":"Publisher Index 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A recent intense episode of volcanic degassing associated with severe impacts on air quality accompanied the 2018 lower East Rift Zone (LERZ) eruption of Kīlauea volcano, Hawai'i. This resulted in a major increase in gas emission rates with respect to usual emission values for this volcano, along with a shift in the source of the dominant plume to a populated area on the lower flank of the volcano. This led to reduced air quality in downwind communities. We analyse open-access data from the permanent air quality monitoring networks operated by the Hawai'i Department of Health (HDOH) and National Park Service (NPS), and report on measurements of atmospheric sulfur dioxide (SO2) between 2007 and 2018 and PM2.5 (aerosol particulate matter with diameter <2.5 μm) between 2010 and 2018. Additional air quality data were collected through a community-operated network of low-cost PM2.5 sensors during the 2018 LERZ eruption. From 2007 to 2018 the two most significant escalations in Kīlauea's volcanic emissions were: the summit eruption that began in 2008 (Kīlauea emissions averaged 5–6 kt/day SO2 from 2008 until summit activity decreased in May 2018) and the LERZ eruption in 2018 when SO2 emission rates reached a monthly average of 200 kt/day during June. In this paper we focus on characterizing the airborne pollutants arising from the 2018 LERZ eruption and the spatial distribution and severity of volcanic air pollution events across the Island of Hawai'i. The LERZ eruption caused the most frequent and severe exceedances of the Environmental Protection Agency (EPA) PM2.5 air quality threshold (35 μg/m3 as a daily average) in Hawai'i in the period 2010–2018. In Kona, for example, the maximum 24-h-mean mass concentration of PM2.5 was recorded as 59 μg/m3 on the twenty-ninth of May 2018, which was one of eight recorded exceedances of the EPA air quality threshold during the 2018 LERZ eruption, where there had been no exceedances in the previous 8 years as measured by the HDOH and NPS networks. SO2 air pollution during the LERZ eruption was most severe in communities in the south and west of the island, as measured by selected HDOH and NPS stations in this study, with a maximum 24-h-mean mass concentration of 728 μg/m3 recorded in Ocean View (100 km west of the LERZ emission source) in May 2018. Data from the low-cost sensor network correlated well with data from the HDOH PM2.5 instruments, confirming that these low-cost sensors provide a robust means to augment reference-grade instrument networks.
Natural bedrock rivers have various bedforms created by erosion. Flow‐parallel incisional grooves formed longitudinally in bedrock are one common example of such bedforms. Although several studies have been conducted regarding these grooves, their formation processes are not well understood. In this study, we conducted a flume experiment to investigate the relationship between the flow structure and longitudinal grooves. The experimental results strongly suggest that longitudinal grooves are formed by moving sediment concentrated in multiple longitudinal pathways by turbulence‐driven secondary flows. The sediment preferentially abrades the bedrock along these flow‐parallel pathways resulting in longitudinal grooves in the bedrock. Measurements of the flow velocity distribution show that the positions of secondary flow cells producing the initial formation of the grooves are altered by the formation of those grooves. Because displaced secondary flows tend to make the sediment collide with the sidewalls of the longitudinal grooves, the grooves grow wider over time and some grooves partially combine with other adjacent grooves. The initial maximum number of longitudinal grooves Nmax strongly depends on the river width‐depth ratio B/D, which defines the number of secondary flow cells, and can be expressed as Nmax = 0.5B/D. However, because some grooves coalesce with other grooves due to the effects of the displacement of secondary flows, the average number of grooves showed a relationship that can be expressed as N = 0.41B/D. Based on this relationship, we inversely estimated the flow discharge of the Abashiri River using the number of longitudinal grooves observed in the river. The result was consistent with the observed annual maximum flow discharge of the river. This suggests that the number of longitudinal grooves can be used as an indicator for estimation of the formative flow discharge in bedrock rivers.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR025410","usgsCitation":"Inoue, T., and Nelson, J.M., 2020, An experimental study of longitudinal incisional grooves in a mixed bedrock-alluvial channel: Water Resources Research, v. 56, no. 3, e2019WR025410, 16 p., https://doi.org/10.1029/2019WR025410.","productDescription":"e2019WR025410, 16 p.","ipdsId":"IP-107443","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":487492,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr025410","text":"Publisher Index Page"},{"id":373013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Inoue, Takuya","contributorId":173794,"corporation":false,"usgs":false,"family":"Inoue","given":"Takuya","email":"","affiliations":[{"id":27295,"text":"Civil Engineering Research Institute, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":784200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":784199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209323,"text":"70209323 - 2020 - The NASA hydrological forecast system for food and water security applications","interactions":[],"lastModifiedDate":"2020-08-05T13:51:35.378688","indexId":"70209323","displayToPublicDate":"2020-02-21T16:42:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"The NASA hydrological forecast system for food and water security applications","docAbstract":"Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning System Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multi-model, remote sensing-based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage); and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean-land-atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multi-model ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its one-to-five month forecasts successfully capture known historic drought events. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-18-0264.1","usgsCitation":"Arsenault, K., Shukla, S., Hazra, A., Getirana, A., McNally, A., Kumar, S., Koster, R., Peters-Lidard, C., Zaitchik, B., Badr, H., Jung, H.C., Narapusetty, B., , N., Wang, S., Mocko, D.M., Funk, C., Harrison, L., Husak, G.J., Adoum, A., Galu, G., Magadzire, T., Roningen, J., Shaw, M.J., Eylander, J., Bergaoui, K., McDonnell, R.A., and Verdin, J., 2020, The NASA hydrological forecast system for food and water security applications: Bulletin of the American Meteorological Society, v. 101, no. 7, p. 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This biodiversity is declining dramatically: Globally, wetlands are vanishing three times faster than forests, and freshwater vertebrate populations have fallen more than twice as steeply as terrestrial or marine populations. Threats to freshwater biodiversity are well documented but coordinated action to reverse the decline is lacking. We present an Emergency Recovery Plan to bend the curve of freshwater biodiversity loss. Priority actions include accelerating implementation of environmental flows; improving water quality; protecting and restoring critical habitats; managing the exploitation of freshwater ecosystem resources, especially species and riverine aggregates; preventing and controlling nonnative species invasions; and safeguarding and restoring river connectivity. We recommend adjustments to targets and indicators for the Convention on Biological Diversity and the Sustainable Development Goals and roles for national and international state and nonstate actors.","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaa002","usgsCitation":"Tickner, D., Opperman, J., Abell, R., Acreman, M., Arthington, A., Bunn, S.E., Cooke, S.J., Darwall, W., Edwards, G., Harrison, I., Hughes, K., Jones, T., Leclere, D., Lynch, A., Leonard, P., McClain, M., McIntyre, P., Muruven, D., Olden, J.D., Ormerod, S., Robinson, J., Tharme, R., Thieme, M., Tockner, K., Wright, M., and Young, L., 2020, Bending the curve of global freshwater biodiversity loss: An emergency recovery plan: BioScience, v. 4, no. 70, p. 330-342, https://doi.org/10.1093/biosci/biaa002.","productDescription":"13 p.","startPage":"330","endPage":"342","ipdsId":"IP-109080","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science 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Fund","active":true,"usgs":false}],"preferred":false,"id":787219,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Tockner, Klement","contributorId":224174,"corporation":false,"usgs":false,"family":"Tockner","given":"Klement","email":"","affiliations":[{"id":40838,"text":"FWF Austrian Science Fund","active":true,"usgs":false}],"preferred":false,"id":787220,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Wright, Mark","contributorId":224175,"corporation":false,"usgs":false,"family":"Wright","given":"Mark","email":"","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":787221,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Young, Lucy","contributorId":224176,"corporation":false,"usgs":false,"family":"Young","given":"Lucy","email":"","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":787222,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70208700,"text":"70208700 - 2020 - Formation criteria for hyporheic anoxic microzones: Assessing interactions of hydraulics, nutrients and biofilms","interactions":[],"lastModifiedDate":"2020-03-11T15:59:43","indexId":"70208700","displayToPublicDate":"2020-02-15T08:52:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Formation criteria for hyporheic anoxic microzones: Assessing interactions of hydraulics, nutrients and biofilms","docAbstract":"Recent experimental studies have detected the presence of anoxic microzones in hyporheic sediments. These microzones are small‐scale anoxic pores, embedded within oxygen‐rich porous media and can act as anaerobic reaction sites producing reduction compounds such as nitrous oxide, a potent greenhouse gas. Microbes are a key control on nutrient transformation in hyporheic sediment, but their associated biomass growth is also capable of altering hydraulic flux, leading to potential bioclogging. Here, we developed one of the first computational modeling approaches that combined hydraulics and microbial conditions to explore the continuous evolution of microzones in stream sediments. The model assessed stream and sediment conditions with different hydraulic flux (0.1–1.0 m/day Darcy flux), nutrient concentrations (O2 = 8 mg/L, OrgC = 20 mg/L, NO−3 = 1.5–3 mg/L, and NH3 = 0.5–1 mg/L), and biomass scenarios (with and without). The model domain is a pore network model with random sized pore‐throat radii creating heterogeneous and anisotropic flow that is representative of a natural streambed composed of medium sand with a hydraulic conductivity of 0.8 m/day. Results from 30 day simulations indicate that hyporheic microzone formation will occur and microzone distributions are not simply controlled by residence time alone, rather by the complex interactions of hydraulic flux, nutrient concentrations, and biomass, with bioclogging having strong feedbacks on both hydraulics and nutrients. Under all conditions with biomass growth, anoxic microzones were unstable, perishing a few days after formation, because bioclogging primarily occurs near the influent (downwelling) area of the hyporheic zone. In turn, this bioclogging shifts transport conditions from advection‐dominated to diffusion‐dominated transport, removing all oxic regions in the hyporheic zone. Overall, results from the modeling show that anoxic microzones are likely to form under many hyporheic zone conditions, and be dynamic through space and time as they are dependent on both hydraulic flux and nutrient transport.
","language":"English","publisher":"Wiley","doi":"10.1029/2019WR025971","usgsCitation":"Chowdhury, S.R., Zarnetske, J., Phanikumar, M., Briggs, M.A., Day-Lewis, F.D., and Singha, K., 2020, Formation criteria for hyporheic anoxic microzones: Assessing interactions of hydraulics, nutrients and biofilms: Water Resources Research, v. 56, no. 3, e2019WR025971, 15 p., https://doi.org/10.1029/2019WR025971.","productDescription":"e2019WR025971, 15 p.","ipdsId":"IP-113836","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":372602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Chowdhury, S. R.","contributorId":222748,"corporation":false,"usgs":false,"family":"Chowdhury","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":783075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarnetske, J.","contributorId":222749,"corporation":false,"usgs":false,"family":"Zarnetske","given":"J.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":783076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phanikumar, M.S.","contributorId":222750,"corporation":false,"usgs":false,"family":"Phanikumar","given":"M.S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":783077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":783074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":783078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singha, K.","contributorId":201025,"corporation":false,"usgs":false,"family":"Singha","given":"K.","email":"","affiliations":[],"preferred":false,"id":783079,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208575,"text":"70208575 - 2020 - Does Lake Erie still have sufficient oxythermal habitat for cisco Coregonus artedi?","interactions":[],"lastModifiedDate":"2020-04-06T21:58:32.077746","indexId":"70208575","displayToPublicDate":"2020-02-15T06:15:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Does Lake Erie Still Have Sufficient Oxythermal Habitat for Cisco Coregonus artedi?","title":"Does Lake Erie still have sufficient oxythermal habitat for cisco Coregonus artedi?","docAbstract":"In Lake Erie, cisco Coregonus artedi once supported one of the most valuable freshwater fisheries on earth, yet overfishing caused their eventual extirpation from the lake. With warming lake temperatures, some have questioned whether Lake Erie still contains suitable oxythermal conditions for cisco. Using published oxythermal thresholds for cisco and oxythermal profiles from Lake Erie, we sought to answer two questions critical to cisco restoration science. First, is cisco habitat still available during the most restrictive periods? Second, what is the distribution of cisco habitat during these times? Beta regression was used to determine that cisco habitat was most limited during the month of August, and that August of 2010 was the most restrictive period in the time series. We then used Empirical Bayesian Kriging (EBK) to map the spatial extent of cisco habitat during these times. EBK maps revealed large areas of summer refugia for cisco in Lake Erie, even during the least favorable periods. Most of the Central and East Basins contain suitable habitat during the average August, yet during August of 2010, suitable conditions were limited to the eastern edge of the Central Basin and the deep waters of the East Basin. These findings align well with historical accounts of cisco landings. While suitable oxythermal habitat still exists for cisco in Lake Erie, future restoration efforts, if attempted, will partially depend on: 1) better management of nutrient inputs, 2) the realization of future climate scenarios, and 3) the ability of cisco to adapt to a changing lake.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.01.019","usgsCitation":"Schmitt, J., Vandergoot, C.S., O’Malley, B.P., and Kraus, R., 2020, Does Lake Erie still have sufficient oxythermal habitat for cisco Coregonus artedi?: Journal of Great Lakes Research, v. 46, no. 2, p. 330-338, https://doi.org/10.1016/j.jglr.2020.01.019.","productDescription":"9 p.","startPage":"330","endPage":"338","ipdsId":"IP-112702","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":372406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Erie ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.21044921875,\n 42.13082130188811\n ],\n [\n -83.507080078125,\n 41.68932225997044\n ],\n [\n -82.4853515625,\n 41.36031866306708\n ],\n [\n -81.968994140625,\n 41.48389104267175\n ],\n [\n -81.650390625,\n 41.48389104267175\n ],\n [\n -81.419677734375,\n 41.68111756290652\n ],\n [\n -80.540771484375,\n 41.94314874732696\n ],\n [\n -79.27734374999999,\n 42.374778361114195\n ],\n [\n -78.826904296875,\n 42.827638636242284\n ],\n [\n -78.837890625,\n 42.90011265525328\n ],\n [\n -79.1015625,\n 42.91620643817353\n ],\n [\n -79.541015625,\n 42.924251753870685\n ],\n [\n -80.013427734375,\n 42.827638636242284\n ],\n [\n -80.299072265625,\n 42.80346172417078\n ],\n [\n -80.562744140625,\n 42.62587560259137\n ],\n [\n -80.91430664062499,\n 42.67435857693381\n ],\n [\n -81.2109375,\n 42.69858589169842\n ],\n [\n -81.45263671875,\n 42.69051116998238\n ],\n [\n -81.82617187499999,\n 42.431565872579185\n ],\n [\n -82.0458984375,\n 42.342305278572816\n ],\n [\n -82.518310546875,\n 42.09007006868398\n ],\n [\n -82.891845703125,\n 42.01665183556825\n ],\n [\n -83.21044921875,\n 42.13082130188811\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmitt, Joseph","contributorId":222565,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":782571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergoot, Christoper S.","contributorId":222566,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christoper","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":782572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Malley, Brian P. bomalley@usgs.gov","contributorId":5615,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":782573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":782574,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209093,"text":"70209093 - 2020 - Mapping metabolic activity at single cell resolution in intact volcanic fumarole soil","interactions":[],"lastModifiedDate":"2020-03-16T06:49:17","indexId":"70209093","displayToPublicDate":"2020-02-14T06:46:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1620,"text":"FEMS Microbiology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mapping metabolic activity at single cell resolution in intact volcanic fumarole soil","docAbstract":"Interactions among microorganisms and their mineralogical substrates govern the structure, function, and emergent properties of microbial communities. These interactions are predicated on spatial relationships, which dictate metabolite exchange and access to key substrates. To quantitatively assess links between spatial relationships and metabolic activity, this study presents a novel approach to map all organisms, the metabolically active subset, and associated mineral grains, all while maintaining spatial integrity of an environmental microbiome. We applied this method at an outgassing fumarole of Vanuatu’s Marum Crater, one of the largest point sources of several environmentally relevant gaseous compounds, including H2O, CO2, and SO2. With increasing distance from the soil-air surface and from mineral grain outer boundaries, organism abundance decreased but the proportion of metabolically active organisms often increased. These protected niches may provide more stable conditions that promote consistent metabolic activity of a streamlined community. Conversely, mineral exteriors accumulate more organisms that may cover a wider range of preferred conditions, implying that only a subset of the community will be active under any particular environmental regime. More broadly, the approach presented here allows investigators to see microbial communities “as they really are” and explore determinants of metabolic activity across a range of microbiomes.","language":"English","publisher":"Oxford Academic","doi":"10.1093/femsle/fnaa031","usgsCitation":"Marlow, J., Colocci, I., Jungbluth, S., Weber, N.M., Gartman, A., and Kallmeyer, J., 2020, Mapping metabolic activity at single cell resolution in intact volcanic fumarole soil: FEMS Microbiology Letters, v. 367, no. 1, fnaa031, https://doi.org/10.1093/femsle/fnaa031.","productDescription":"fnaa031","ipdsId":"IP-114025","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457717,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://gfzpublic.gfz-potsdam.de/pubman/item/item_5001483","text":"External Repository"},{"id":373282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"367","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Marlow, Jeffrey J. 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","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":784908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colocci, Isabella","contributorId":223381,"corporation":false,"usgs":false,"family":"Colocci","given":"Isabella","email":"","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":784909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jungbluth, Sean ","contributorId":223382,"corporation":false,"usgs":false,"family":"Jungbluth","given":"Sean ","affiliations":[{"id":40704,"text":"Department of Energy, Joint Genome Institute","active":true,"usgs":false}],"preferred":false,"id":784910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Nils Moritz","contributorId":223383,"corporation":false,"usgs":false,"family":"Weber","given":"Nils","email":"","middleInitial":"Moritz","affiliations":[{"id":39797,"text":"GFZ German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":784911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":784907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kallmeyer, Jens","contributorId":223384,"corporation":false,"usgs":false,"family":"Kallmeyer","given":"Jens","email":"","affiliations":[{"id":39797,"text":"GFZ German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":784912,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208510,"text":"70208510 - 2020 - Spatial and temporal trends in Potomac River fish abundance linked to species traits","interactions":[],"lastModifiedDate":"2020-02-14T06:24:45","indexId":"70208510","displayToPublicDate":"2020-02-12T08:57:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal trends in Potomac River fish abundance linked to species traits","docAbstract":"Analysis of species abundance trends can inform an understanding of the underlying mechanisms. We evaluated spatial and temporal trends in fish species abundance in the non-tidal Potomac River (USA) from a dataset comprising 2841 seine-hauls with > 250,000 individual fish records across 10 sites and 43 years (1975-2017). The dataset contained 47 species from 7 taxonomic families, with species richness and abundance dominated by leuciscids, centrarchids, and percids (85% and 95% of the total dataset, respectively). We used linear modeling and bootstrapping techniques to estimate spatial and temporal trends in abundance (CPUE) for 38 species, excluding the rarest taxa (< 30 individuals). Spatial trends in abundance were detected for 22 species (58%), of which 15 were more abundant downstream than upstream and 7 were more abundant upstream than downstream. Temporal trends in abundance were detected for 25 species (66%), of which 15 increased over time and 10 decreased over time. Spatial trends were associated with reproductive life history strategies: egg-attachers and viviparous fishes generally increased in a downstream direction, whereas species with other reproductive modes and relatively short spawning durations (< ~2 months) showed the opposite spatial trend. Temporal trends were associated with reproductive guilds and range area (a surrogate for environmental tolerance): egg-attachers and nest-associates generally increased in abundance over time, whereas broadcast spawners, clean-gravel spawners, and nest-guarders with relatively small range areas (< ~ 1.2 million km2) tended to decrease over time. This study provides an analysis of one of the largest systematic collections of freshwater fishes to our knowledge and provides a framework to evaluate mechanisms underlying observed trends.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3026","usgsCitation":"Hitt, N.P., Rogers, K., Kelly, Z.A., Henesy, J., and Mullican, J.E., 2020, Spatial and temporal trends in Potomac River fish abundance linked to species traits: Ecosphere, v. 11, no. 2, e03026, 17 p., https://doi.org/10.1002/ecs2.3026.","productDescription":"e03026, 17 p.","ipdsId":"IP-107694","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3026","text":"Publisher Index Page"},{"id":372312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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E.","contributorId":203245,"corporation":false,"usgs":false,"family":"Mullican","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":782204,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208837,"text":"70208837 - 2020 - Timing, frequency, and duration of incubation recesses in dabbling ducks","interactions":[],"lastModifiedDate":"2020-04-06T23:08:58.299679","indexId":"70208837","displayToPublicDate":"2020-02-12T07:41:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Timing, frequency, and duration of incubation recesses in dabbling ducks","docAbstract":"Nest attendance is an important determinant of avian reproductive success, and identifying factors that influence the frequency and duration of incubation recesses furthers our understanding of how incubating birds balance their needs with those of their offspring. We characterized the frequency and timing (start time, end time, and duration) of incubation recesses for mallard (Anas platyrhynchos) and gadwall (Mareca strepera) hens breeding in Suisun Marsh, California, USA, and examined the influences of day of year, ambient temperature at the nest, incubation day, and clutch size on recess frequency and timing using linear mixed models. Mallard, on average, took more recesses per day (1.69 ± 0.80, mean ± standard deviation) than did gadwall (1.39 ± 0.69), and 45% of mallard nest-days were characterized by two recesses, while only 27% of gadwall nest-days were characterized by two recesses. Mallard morning recesses started at 06:14 ± 02:46, and lasted 106.11 ± 2.01 minutes, whereas mallard afternoon recesses started at 16:39 ± 02:11 and lasted 155.39 ± 1.99 minutes. Gadwall morning recesses started at 06:30 ± 02:46 and lasted 91.28 ± 2.32 minutes, and gadwall afternoon recesses started at 16:31 ± 01:57 and lasted 192.69 ± 1.89 minutes. Mallard and gadwall started recesses earlier in the day with increasing ambient temperature, but later in the day as the season progressed. Recess duration decreased as the season progressed and as clutch size increased, and increased with ambient temperature at the nest. The impending darkness of sunset appeared to be a strong cue for ending a recess and returning to the nest, because hens returned to their nests earlier than expected when recesses were expected to end after sunset. Within hens, the timing of incubation recesses was repeatable across incubation days, and was most repeatable for mallard afternoon recesses and on days in which hens took only one recess. Hens were most likely to be away from nests between 04:00 and 07:00 and between 16:00 and 19:00, therefore, investigators should search for nests between 07:00 and 16:00. Our analyses identified important factors influencing incubation recess timing in dabbling ducks, and have important implications for nest monitoring programs.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.6078","usgsCitation":"Croston, R., Hartman, C.A., Herzog, M.P., Casazza, M.L., Feldheim, C.L., and Ackerman, J., 2020, Timing, frequency, and duration of incubation recesses in dabbling ducks: Ecology and Evolution, v. 10, no. 5, p. 2513-2529, https://doi.org/10.1002/ece3.6078.","productDescription":"17 p.","startPage":"2513","endPage":"2529","ipdsId":"IP-108815","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457746,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.6078","text":"Publisher Index Page"},{"id":437116,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P981DMHZ","text":"USGS data release","linkHelpText":"Incubation recess times for mallard and gadwall hens nesting in Grizzly Island Wildlife Area 2015 - 2017"},{"id":372830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Suisun Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.18856811523436,\n 38.06485174812299\n ],\n [\n -122.18101501464844,\n 38.028622234587964\n ],\n [\n -122.13569641113281,\n 38.016722066763116\n ],\n [\n -122.07115173339844,\n 38.031867399480674\n ],\n [\n -122.02171325683595,\n 38.04322434446539\n ],\n [\n -121.87477111816406,\n 38.019426820061696\n ],\n [\n -121.79306030273438,\n 38.01131226070673\n ],\n [\n -121.82052612304688,\n 38.067554724225275\n ],\n [\n -121.86035156249999,\n 38.135636748588574\n ],\n [\n -121.87545776367186,\n 38.21930139874194\n ],\n [\n -121.94549560546875,\n 38.23332605954002\n ],\n [\n -122.0306396484375,\n 38.24249456800328\n ],\n [\n -122.08763122558594,\n 38.170733619349654\n ],\n [\n -122.09655761718749,\n 38.098901948321256\n ],\n [\n -122.18856811523436,\n 38.06485174812299\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Croston, Rebecca","contributorId":222932,"corporation":false,"usgs":true,"family":"Croston","given":"Rebecca","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":783575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":783570,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216195,"text":"70216195 - 2020 - Infectious hematopoietic necrosis virus specialization in a multihost salmonid system","interactions":[],"lastModifiedDate":"2020-11-10T13:15:05.55733","indexId":"70216195","displayToPublicDate":"2020-02-12T07:11:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Infectious hematopoietic necrosis virus specialization in a multihost salmonid system","docAbstract":"Many pathogens interact and evolve in communities where more than one host species is present, yet our understanding of host–pathogen specialization is mostly informed by laboratory studies with single species. Managing diseases in the wild, however, requires understanding how host–pathogen specialization affects hosts in diverse communities. Juvenile salmonid mortality in hatcheries caused by infectious hematopoietic necrosis virus (IHNV) has important implications for salmonid conservation programs. Here, we evaluate evidence for IHNV specialization on three salmonid hosts and assess how this influences intra‐ and interspecific transmission in hatchery‐reared salmonids. We expect that while more generalist viral lineages should pose an equal risk of infection across host types, viral specialization will increase intraspecific transmission. We used Bayesian models and data from 24 hatcheries in the Columbia River Basin to reconstruct the exposure history of hatcheries with two IHNV lineages, MD and UC, allowing us to estimate the probability of juvenile infection with these lineages in three salmonid host types. Our results show that lineage MD is specialized on steelhead trout and perhaps rainbow trout (both Oncorhynchus mykiss), whereas lineage UC displayed a generalist phenotype across steelhead trout, rainbow trout, and Chinook salmon. Furthermore, our results suggest the presence of specialist–generalist trade‐offs because, while lineage UC had moderate probabilities of infection across host types, lineage MD had a small probability of infection in its nonadapted host type, Chinook salmon. Thus, in addition to quantifying probabilities of infection of socially and economically important salmonid hosts with different IHNV lineages, our results provide insights into the trade‐offs that viral lineages incur in multihost communities. Our results suggest that knowledge of the specialist/generalist strategies of circulating viral lineages could be useful in salmonid conservation programs to control disease.
The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01063","usgsCitation":"McGowan, C.P., Angeli, N., Beisler, W., Snyder, C., Rankin, N., Woodrow, J., Wilson, J., Rivenbark, E., Schwarzer, A., Hand, C., Anthony, R., Griffin, R., Barrett, K., Haverland, A., Roach, N., Schneider, T., Smith, A.J., Smith, F., Tolliver, J., and Watts, B.D., 2020, Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment: Endangered Species Research, v. 43, p. 209-222, https://doi.org/10.3354/esr01063.","productDescription":"14 p.","startPage":"209","endPage":"222","ipdsId":"IP-111624","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01063","text":"Publisher Index 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We analyze Pacific Northwest Seismic Network and U.S. Geological Survey strong‐motion recordings of five local earthquakes (M 3.9–6.8), including the 2001 Nisqually earthquake, to characterize sedimentary basin effects within the Seattle and Tacoma basins. We observe basin‐edge generated surface waves at sites within the Seattle basin for most ray paths that cross the Seattle fault zone. We also note previously undocumented basin‐edge surface waves in the Tacoma basin during one of the local earthquakes. To place quantitative constraints on basin amplification, we determine amplification factors by computing the spectral ratios of inside‐basin sites to outside‐basin sites at 1, 2, 3, and 5 s periods. Ground shaking is amplified in the Seattle basin for all the earthquakes analyzed and for a subset of events in the Tacoma basin. We find that the largest amplification factors in the Seattle basin are produced by a shallow earthquake located to the southwest of the basin. Our observation suggests that future shallow crustal and megathrust earthquakes rupturing west of the Puget Lowland will produce greater amplification within the Seattle basin than has been seen for intraslab events. We also perform ground‐motion simulations using a finite‐difference method to validate a 3D Cascadia velocity model (CVM) by comparing properties of observed and synthetic waveforms up to a frequency of 1 Hz. Basin‐edge effects are well reproduced in the Seattle basin, but are less well resolved in the Tacoma basin. Continued study of basin effects in the Tacoma basin would improve the CVM.