Aquatic organisms have adapted over evolutionary time-scales to hydrologic variability represented by the natural flow regime of rivers and streams in their unimpaired state. Rapid landscape change coupled with growing human demand for water have altered natural flow regimes of many rivers and streams on a global scale. Climate non-stationarity is expected to further intensify hydrologic variability, placing increased pressure on aquatic communities. Using a machine learning approach and georeferenced species occurrence data, we modeled and mapped spatial patterns of hydrologic disturbance for streams in Arkansas, Missouri, and eastern Oklahoma. Random forest (RF) models trained on fish community data, hydrologic, and landscape metrics for gaged streams in the National Hydrography (NHDPlusV2) database were used to predict a hydrologic disturbance index (HDI) for ungaged streams. The HDI is part of the USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGESII) database and is a composite index of watershed-scale disturbance from anthropogenic stressors. Fish presence/absence data had similar overall model prediction accuracy (77%; 95% CI: 0.74, 0.80) as flow variables (76%; CI: 0.73, 0.80). Including topographic variables increased the RF prediction accuracy of both the fish (90%; CI: 0.88, 0.92) and flow models (86%; CI: 0.84, 0.89). Spatial patterns of hydrologic disturbance suggest distinct ecohydrological regions exist where conservation actions may be focused. Streams with low HDI were predominately located in the Ozark Highlands, Boston Mountains, and Ouachita Mountains. Correlation analysis of HDI by flow regime showed groundwater stable streams had the lowest disturbance frequency, with over 50% of stream reaches with low HDI located in forested land cover. HDI was highest for big rivers, intermittent runoff streams and streams in areas of agricultural land use. Our results show long-term georeferenced biological data can provide a valuable resource for predictive modeling of hydrologic disturbance for ungaged rivers and streams.
We evaluated relationships among hydrogeomorphology, vegetation structure and composition, and avian communities among three subreaches of the San Acacia Reach of the Middle Rio Grande (MRG) River of New Mexico. The subreaches varied in degradation, with Subreach 1 being severely entrenched and hydrologically disconnected, Subreach 2 being the least impacted, and Subreach 3 being intermediately disturbed. Avian point count and habitat surveys were conducted to determine avian community structure and abundance, geomorphic feature, surface flooding, and vegetation structure and composition. Ground-nesting birds and low shrub-nesting birds were insensitive to hydrogeomorphic changes as they do not rely on native understory but can use exotic understory or woody debris. In contrast, canopy-nesting birds required native overstory; therefore, they were sensitive to hydrogeomorphic changes as native overstory species require surface floods to germinate and establish. Additionally, native overstory did not vary as expected as the moderately impacted subreach, Subreach 3, had more native overstory (
Avian avulavirus (commonly known as avian paramyxovirus-1 or APMV-1) can cause disease of varying severity in both domestic and wild birds. Understanding how viruses move among hosts and geography would be useful for informing prevention and control efforts. A Bayesian statistical framework was employed to estimate the evolutionary history of 1602 complete fusion gene APMV-1 sequences collected from 1970 to 2016 in order to infer viral transmission between avian host orders and diffusion among geographic regions. Ancestral states were estimated with a non-reversible continuous-time Markov chain model, allowing transition rates between discrete states to be calculated. The evolutionary analyses were stratified by APMV-1 classes I (n = 198) and II (n = 1404), and only those sequences collected between 2006 and 2016 were allowed to contribute host and location information to the viral migration networks.
While the current data was unable to assess impact of host domestication status on APMV-1 diffusion, these analyses supported the sharing of APMV-1 among divergent host taxa. The highest supported transition rate for both classes existed from domestic chickens to Anseriformes (class I:6.18 transitions/year, 95% highest posterior density (HPD) 0.31–20.02, Bayes factor (BF) = 367.2; class II:2.88 transitions/year, 95%HPD 1.9–4.06, BF = 34,582.9). Further, among class II viruses, domestic chickens also acted as a source for Columbiformes (BF = 34,582.9), other Galliformes (BF = 34,582.9), and Psittaciformes (BF = 34,582.9). Columbiformes was also a highly supported source to Anseriformes (BF = 322.0) and domestic chickens (BF = 402.6). Additionally, our results provide support for the diffusion of viruses among continents and regions, but no interhemispheric viral exchange between 2006 and 2016. Among class II viruses, the highest transition rates were estimated from South Asia to the Middle East (1.21 transitions/year; 95%HPD 0.36–2.45; BF = 67,107.8), from Europe to East Asia (1.17 transitions/year; 95%HPD 0.12–2.61; BF = 436.2) and from Europe to Africa (1.06 transitions/year, 95%HPD 0.07–2.51; BF = 169.3).
While migration appears to occur infrequently, geographic movement may be important in determining viral diversification and population structure. In contrast, inter-order transmission of APMV-1 may occur readily, but most events are transient with few lineages persisting in novel hosts.
Groundwater inundation (GWI) is a particularly challenging consequence of sea-level rise (SLR), as it progressively inundates infrastructure located above and below the ground surface. Paths of flooding by GWI differ from other types of SLR flooding (i.e., wave overwash, storm-drain backflow) such that it is more difficult to mitigate, and thus requires a separate set of highly innovative adaptation strategies to manage. To spur consideration of GWI in planning, data-intensive numerical modeling methods have been developed that produce locally specific visualizations of GWI, though the accessibility of such methods is limited by extensive data requirements. Conversely, the hydrostatic (or 'bathtub') modeling approach is widely used in adaptation planning owing to easily accessed visualizations (i.e., NOAA SLR Viewer), yet its capacity to simulate GWI has never been tested. Given the separate actions necessary to mitigate GWI relative to marine overwash, this is a significant gap. Here we compare a simple hydrostatic modeling method with a more deterministic, dynamic and robust 3D numerical modeling approach to explore the effectiveness of the hydrostatic method in simulating equilibrium aquifer effects of multi-decadal sea-level rise, and in turn GWI for Honolulu, Hawai'i. We find hydrostatic modeling in the Honolulu area and likely other settings may yield similar results to numerical modeling when referencing the local mean higher-high water tide datum (generally typical of flood studies). These findings have the potential to spur preliminary understanding of GWI impacts in municipalities that lack the required data to conduct rigorous groundwater-modeling investigations. We note that the methods explored here for Honolulu do not simulate dynamic coastal processes (i.e., coastal erosion, sediment accretion or changes in land cover) and thus are most appropriately applied to regions that host heavily armored shorelines behind which GWI can develop.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/2515-7620/ab21fe","usgsCitation":"Habel, S., Fletcher, C., Rotzoll, K., El-Kadi, A.I., and Oki, D., 2019, Comparison of a simple hydrostatic and a data-intensive 3D numerical modeling method of simulating sea-level rise induced groundwater inundation for Honolulu, Hawai'i, USA: Environmental Research Letters, v. 1, no. 4, 041005, 12 p., https://doi.org/10.1088/2515-7620/ab21fe.","productDescription":"041005, 12 p.","ipdsId":"IP-102017","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":467598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/2515-7620/ab21fe","text":"Publisher Index Page"},{"id":385147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.04931640625,\n 21.289374355860424\n ],\n [\n -157.9010009765625,\n 21.289374355860424\n ],\n [\n -157.9010009765625,\n 21.4121622297254\n ],\n [\n -158.04931640625,\n 21.4121622297254\n ],\n [\n -158.04931640625,\n 21.289374355860424\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Habel, Shellie 0000-0001-9295-0596","orcid":"https://orcid.org/0000-0001-9295-0596","contributorId":257499,"corporation":false,"usgs":false,"family":"Habel","given":"Shellie","email":"","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":814397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fletcher, Charles H.","contributorId":257500,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles H.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":814398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rotzoll, Kolja 0000-0002-5910-888X","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":201087,"corporation":false,"usgs":false,"family":"Rotzoll","given":"Kolja","affiliations":[],"preferred":false,"id":814399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"El-Kadi, Aly I. 0000-0002-9623-5458","orcid":"https://orcid.org/0000-0002-9623-5458","contributorId":257501,"corporation":false,"usgs":false,"family":"El-Kadi","given":"Aly","email":"","middleInitial":"I.","affiliations":[{"id":35886,"text":"University of Hawaii at Manoa, Water Resources Research Center","active":true,"usgs":false}],"preferred":false,"id":814400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oki, Delwyn S. 0000-0002-6913-8804","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":207735,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814401,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203942,"text":"70203942 - 2019 - Planning for ecological drought: Integrating ecosystem services and vulnerability assessment","interactions":[],"lastModifiedDate":"2019-12-22T14:31:16","indexId":"70203942","displayToPublicDate":"2019-05-23T16:41:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Planning for ecological drought: Integrating ecosystem services and vulnerability assessment","docAbstract":"As research recognizes the importance of ecological impacts of drought to natural and human communities, drought planning processes need to better incorporate ecological impacts. Drought planning currently recognizes the vulnerability of some ecological impacts from drought (e.g., loss of instream flow affecting fish populations). However, planning often does not identify all the ecological aspects in a landscape that stakeholders value, nor does it examine the extent to which those aspects are vulnerable to drought. One approach for identifying ecological aspects is ecosystem services (ES) -- i.e., the benefits humans receive from nature. To incorporate ecological impacts into drought planning in the Upper Missouri Headwaters region (Montana, USA), we combined ES elicitation using the Common International Classification of Ecosystem Services and a vulnerability assessment using semi-structured interviews. We juxtaposed results from the interviews and the ES elicitation to assess which ES might be vulnerable to drought and which impacts from interviews were associated with losses of ES. While both methods suggested common drought vulnerabilities, each method also suggested drought vulnerabilities not reported using the other method. The ES elicitation produced more detail about services present in the UMH ecosystem today while interviews resulted in more discussion about ecological transformation from future droughts. Results suggest that some combination of open-ended vulnerability assessment methods and ES elicitation using a structured framework can result in greater understanding of ecological drought vulnerability in a given region.","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1352","usgsCitation":"Raheem, N., Cravens, A.E., Cross, M.S., Crausbay, S.D., Ramirez, A.R., McEvoy, J., Zoanni, D., Bathke, D.J., Hayes, M., Carter, S., Rubenstein, M., Schwend, A., Hall, K.R., and Suberu, P., 2019, Planning for ecological drought: Integrating ecosystem services and vulnerability assessment: WIREs Water, v. 6, no. 4, e1352; 12 p., https://doi.org/10.1002/wat2.1352.","productDescription":"e1352; 12 p.","ipdsId":"IP-094688","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":364973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Upper Missouri Headwaters Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.13720703125,\n 44.94924926661153\n ],\n [\n -110.72021484375,\n 44.94924926661153\n ],\n [\n -110.72021484375,\n 46.89023157359399\n ],\n [\n -113.13720703125,\n 46.89023157359399\n ],\n [\n -113.13720703125,\n 44.94924926661153\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Raheem, Nejem","contributorId":197227,"corporation":false,"usgs":false,"family":"Raheem","given":"Nejem","email":"","affiliations":[],"preferred":false,"id":764860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":764859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Molly S. 0000-0002-4238-9208","orcid":"https://orcid.org/0000-0002-4238-9208","contributorId":149216,"corporation":false,"usgs":false,"family":"Cross","given":"Molly","middleInitial":"S.","affiliations":[{"id":17674,"text":"Wildlife Conservation Society, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":764861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crausbay, Shelley D.","contributorId":197220,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":764863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramirez, Aaron R.","contributorId":149780,"corporation":false,"usgs":false,"family":"Ramirez","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":17824,"text":"UC Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":764864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McEvoy, Jamie","contributorId":204581,"corporation":false,"usgs":false,"family":"McEvoy","given":"Jamie","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":764865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zoanni, Dionne 0000-0003-3988-984X","orcid":"https://orcid.org/0000-0003-3988-984X","contributorId":216494,"corporation":false,"usgs":true,"family":"Zoanni","given":"Dionne","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":764872,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bathke, Deborah J.","contributorId":197224,"corporation":false,"usgs":false,"family":"Bathke","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":764862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayes, Michael","contributorId":192358,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael","affiliations":[],"preferred":false,"id":764870,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carter, Shawn 0000-0002-0045-4681","orcid":"https://orcid.org/0000-0002-0045-4681","contributorId":216490,"corporation":false,"usgs":true,"family":"Carter","given":"Shawn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":764866,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rubenstein, Madeleine 0000-0001-8569-781X","orcid":"https://orcid.org/0000-0001-8569-781X","contributorId":216491,"corporation":false,"usgs":false,"family":"Rubenstein","given":"Madeleine","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":764867,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schwend, Ann","contributorId":216492,"corporation":false,"usgs":false,"family":"Schwend","given":"Ann","email":"","affiliations":[{"id":39458,"text":"Montana Department of Natural Resources and Conservation","active":true,"usgs":false}],"preferred":false,"id":764868,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hall, Kimberly R.","contributorId":197221,"corporation":false,"usgs":false,"family":"Hall","given":"Kimberly","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":764871,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Suberu, Paul","contributorId":216493,"corporation":false,"usgs":false,"family":"Suberu","given":"Paul","email":"","affiliations":[{"id":39459,"text":"Bennington College","active":true,"usgs":false}],"preferred":false,"id":764869,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70203310,"text":"sim3434 - 2019 - Drilling, construction, water chemistry, water levels, and regional potentiometric surface of the upper carbonate-rock aquifer in Clark County, Nevada, 2009–2015","interactions":[],"lastModifiedDate":"2019-05-24T09:10:16","indexId":"sim3434","displayToPublicDate":"2019-05-23T15:22:52","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3434","displayTitle":"Drilling, Construction, Water Chemistry, Water Levels, and Regional Potentiometric Surface of the Upper Carbonate-Rock Aquifer in Clark County, Nevada, 2009–2015","title":"Drilling, construction, water chemistry, water levels, and regional potentiometric surface of the upper carbonate-rock aquifer in Clark County, Nevada, 2009–2015","docAbstract":"The U.S. Geological Survey (USGS) and the Bureau of Land Management (BLM) initiated a cooperative study through the Southern Nevada Public Land Management Act (Bureau of Land Management, 1998) to install six wells in the carbonate-rock and basin-fill aquifers of Clark County, Nevada, in areas of sparse groundwater data. This map uses water levels from these new wells, water levels from existing wells, and altitudes of spring discharge points to update a regional potentiometric map of the carbonate-rock aquifer and provide evidence to interpret the direction of regional groundwater flow. This potentiometric surface map is accompanied by drilling and borehole geophysical logs, well construction information, lithology, water chemistry, and water levels from the newly drilled wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3434","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Wilson, J.W., 2019, Drilling, construction, water chemistry, water levels, and regional potentiometric surface of the upper carbonate-rock aquifer in Clark County, Nevada, 2009–2015: U.S. Geological Survey Scientific Investigations Map 3434, scale 1:500,000, https://doi.org/10.3133/sim3434.","productDescription":"1 Sheet: 59.00 x 32.00 in.; Data Release","onlineOnly":"Y","ipdsId":"IP-050214","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":364132,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3434/sim3434.pdf","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Map 3434"},{"id":364131,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3434/coverthb_.jpg"},{"id":364136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K73T7Q","linkHelpText":"Supplemental data for drilling, construction, water chemistry, water levels, and regional potentiometric surface of the upper carbonate-rock aquifer in Clark County, Nevada, 2009-2015"}],"contact":"Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Monitoring riparian vegetation cover and species richness is an important component of assessing change and understanding ecosystem processes. Vegetation sampling methods determined to be the best option in other ecosystems (e.g., desert grasslands and arctic tundra) may not be the best option in multilayered, species rich, heterogeneous riparian vegetation. This study examines the strengths and weaknesses of two common vegetation sampling methods, line‐point intercept and ocular quadrat estimates. Permutational analysis of variance analyses indicate that cover estimates among observers did not differ significantly for either line‐point intercept or ocular quadrat estimates. Line‐point intercept cover estimates resulted in lower coefficient of variation among observers than ocular quadrat estimates, but the ocular quadrat estimates recorded significantly more species. Line‐point estimates of cover were generally larger than ocular quadrat estimates. Ocular quadrat estimates are appropriate when assessment of richness is important, in areas with heterogeneous geomorphology and hydrology where fine‐scale measurements are most useful, and in areas where continuous sampling transects are impracticable. Line‐point intercept estimates are useful when minimum variation among observers is necessary, continuous transects are logical and practicable for the sampling area, woody cover does not present a logistical complication, and species richness is not a priority.
Mosquito vectors play a crucial role in the distribution of avian Plasmodium parasites worldwide. At northern latitudes, where climate warming is most pronounced, there are questions about possible changes in the abundance and distribution of Plasmodium parasites, their vectors, and their impacts to avian hosts. To better understand the transmission of Plasmodium among local birds and to gather baseline data on potential vectors, we sampled a total of 3,909 mosquitoes from three locations in south‐central Alaska during the summer of 2016. We screened mosquitoes for the presence of Plasmodium parasites using molecular techniques and estimated Plasmodium infection rates per 1,000 mosquitoes using maximum likelihood methods. We found low estimated infection rates across all mosquitoes (1.28 per 1,000), with significantly higher rates in Culiseta mosquitoes (7.91 per 1,000) than in Aedes mosquitoes (0.57 per 1,000). We detected Plasmodium in a single head/thorax sample of Culiseta, indicating potential for transmission of these parasites by mosquitoes of this genus. Plasmodium parasite DNA isolated from mosquitoes showed a 100% identity match to the BT7 Plasmodium lineage that has been detected in numerous avian species worldwide. Additionally, microscopic analysis of blood smears collected from black‐capped chickadees (Poecile atricapillus) at the same locations revealed infection by parasites preliminarily identified as Plasmodium circumflexum. Results from our study provide the first information on Plasmodium infection rates in Alaskan mosquitoes and evidence that Culiseta species may play a role in the transmission and maintenance of Plasmodium parasites in this region.
Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Dams disrupt the flow of water and sediment and thus have the potential to affect the downstream geomorphic characteristics of a river. Though there are some well‐known and common geomorphic responses to dams, such as bed armouring, the response downstream from any particular dam is dependent on local conditions. Herein, we investigate the response of the upper Santa Ana River in southern California, USA, to the construction of a large dam at the transition from mountains to valley, using calculations of bedload transport capacity on the mainstem below the dam and for major tributaries. Approximate sediment budgets were constructed for downstream reaches to estimate deposition and erosion rates for sand, gravel, and cobble particle sizes. Our results indicate that the classical response of bed armouring and erosion is likely limited to a short reach immediately below the dam. Farther downstream, though transport capacity is reduced by flow regulation by the dam, the channel reaches are likely to remain depositional but with reduced deposition rates. Persistent deposition, as opposed to erosion, is the result of the replenishment of flow and sediment supply by large downstream tributaries. In addition, the calculations indicate that the composition of the bed is unlikely to change substantially in downstream reaches. A Monte Carlo approach was employed to estimate the uncertainty in the sediment budget predictions. The impacts of the dam on the geomorphic character of the river downstream could have implications for native fish that rely on coarse substrate that supports their food base.
Turbidity currents are generated when denser river water plunges and flows along the bottom of a lake, reservoir, or ocean. The plunging and downstream movement are driven by density differences due to temperature and/or suspended sediment, and currents have been observed to move slowly over long distances. This study presents observations of multiple turbidity currents in a large reservoir in California, United States, during runoff events following a major wildfire in the upstream watershed. Several aspects of the currents are documented and discussed, including the conditions leading to plunging, the vertical and longitudinal structure of turbidity within the currents, the velocity of the currents, and the development of a muddy lake upstream from an old submerged dam in the reservoir.
2018 marked the 10-year anniversary of the establishment of the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center! With the passage of the fiscal year 2018 budget on March 23, 2018, our program name was changed from the National Climate Change and Wildlife Science Center to the National Climate Adaptation Science Center (NCASC). The eight regional Department of the Interior (DOI) Climate Science Centers were renamed Climate Adaptation Science Centers (CASCs). The name changes more clearly align the national and regional centers and emphasize their focus on meeting natural resource adaptation needs. Although the program has a new name, our mission has not changed. We are still hard at work delivering science to help fish, wildlife, water, land, and people adapt to a changing climate.
During the past 10 years, the NCASC and the eight regional CASCs funded over 425 science projects and built a network of research partners, resource management stakeholders, interdisciplinary staff, fellows, and early career researchers. In celebration of our work and accomplishments over the last 10 years, the NCASC began a monthly web post series on “10 Things You May Not Know” about topics our science has focused on, including drought, glaciers, and wildfire.
Additionally, CASCs that had completed their initial hosting agreement with the USGS underwent a formal review and recompetition process. New hosting agreements were awarded to the Southwest and North Central CASCs in 2018. Read the 2018 annual report to learn more about the CASCs' great science, partnerships, capacity building, and more from 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191041","usgsCitation":"Varela Minder, E., 2019, Climate Adaptation Science Centers—Annual report for 2018: U.S. Geological Survey Open-File Report 2019–1041, 14 p., https://doi.org/10.3133/ofr20191041.","productDescription":"14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103920","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":364065,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1041/ofr20191041.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1041"},{"id":364064,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1041/coverthb2.jpg"}],"contact":"Director, National Climate Adaptation Science Center
U.S. Geological Survey
Mail Stop 516
12201 Sunrise Valley Drive
Reston, VA 20192
The coccidium Goussia bayae infects the gallbladder and bile ducts of white perch Morone americana from Chesapeake Bay, USA. Seasonal changes in coccidian infections were analyzed from bile specimens of 1588 fish from the Choptank River during 2016-2018 using wet mount preparations with a Sedgwick-Rafter counting chamber. Histopathology of the gallbladder and liver was analyzed from a subset (n = 480) of these fish. Maximum parasite prevalence (100%) and intensities in the gallbladder occurred during the fish spawning season in March and April. Asynchronous coccidian development and prevalence of infections in fish increased gradually during autumn and winter, but coccidian intensity increased sharply 2-4 wk prior to the onset of fish spawning activity and decreased after spawning activity concluded. Sporulation was internal, and the gallbladder was the primary reservoir for oocysts. Two previously undescribed species of coccidia were observed in the intestine. Lesions in the gallbladder were rare and included cholecystitis and epithelial necrosis. Intrahepatic bile duct lesions were more common and included distension, cholangitis, epithelial erosion and necrosis, cholestasis, hyperplasia, and neoplasia. Cholangitis and necrosis of intrahepatic bile ducts were significantly associated with coccidial infections, while plasmodia of a myxosporean (spore morphology consistent with the genera Myxidium and Zschokella) were significantly associated with bile duct hyperplasia. Biliary neoplasia included cholangiomas (5% prevalence) and cholangiocarcinomas (1% prevalence). No association was detected between G. bayae and biliary neoplasms, but an association may exist between these lesions and the myxosporean plasmodia.
","language":"English","publisher":"Inter-Research Science Center","doi":"10.3354/dao03353","usgsCitation":"Matsche, M.A., Blazer, V., and Mazik, P.M., 2019, Seasonal development of the coccidian parasite Goussia bayae and hepatobiliary histopathology in white perch Morone americana from Chesapeake Bay: Diseases of Aquatic Organisms, v. 134, no. 2, p. 113-135, https://doi.org/10.3354/dao03353.","productDescription":"13 p.","startPage":"113","endPage":"135","ipdsId":"IP-104101","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":376944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.04736328125,\n 36.914764288955936\n ],\n [\n -75.673828125,\n 37.814123701604466\n ],\n [\n -75.82763671875,\n 38.57393751557591\n ],\n [\n -75.904541015625,\n 39.64799732373418\n ],\n [\n -76.640625,\n 39.29179704377487\n ],\n [\n -76.75048828125,\n 38.47939467327645\n ],\n [\n -77.178955078125,\n 38.74551518488265\n ],\n [\n -77.332763671875,\n 38.44498466889473\n ],\n [\n -77.36572265625,\n 38.30718056188316\n ],\n [\n -76.981201171875,\n 38.272688535980976\n ],\n [\n -77.025146484375,\n 38.12591462924157\n ],\n [\n -77.04711914062499,\n 37.142803443716836\n ],\n [\n -76.256103515625,\n 36.730079507078415\n ],\n [\n -76.04736328125,\n 36.914764288955936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":794689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":794691,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249342,"text":"70249342 - 2019 - Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections","interactions":[],"lastModifiedDate":"2023-10-04T12:12:32.70824","indexId":"70249342","displayToPublicDate":"2019-05-23T07:09:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections","docAbstract":"Atrazine is presently one of the most abundantly used herbicides in the United States, and a common contaminant of natural water bodies and drinking waters in high-use areas. Dysregulation of reproductive processes has been demonstrated in atrazine exposed fish, including alteration of key endocrine pathways on hypothalamic-pituitary-gonadal (HPG) axis. However, the potential for atrazine-induced transgenerational inheritance of reproductive effects in fish has not been investigated. The present study examined the effects of early developmental atrazine exposure on transgenerational reproductive dysregulation in Japanese medaka (Oryzias latipes). F0 medaka were exposed to atrazine (ATZ, 5 or 50 μg/L), 17α-ethinylestradiol (EE2, 0.002 or 0.05 μg/L), or solvent control during the first twelve days of development with no subsequent exposure over three generations. This exposure overlapped with the critical developmental window for embryonic germ cell development, gonadogenesis, and sex determination. Exposed males and females of the F0 generation were bred to produce an F1 generation, and this was continued until the F2 generation. Sperm count and motility were not affected in F0 males; however, both parameters were significantly reduced in the males from F2 Low EE2 (0.002 μg/L), Low ATZ (5 μg/L), and High ATZ (50 μg/L) lineages. Fecundity was unaffected by atrazine or EE2 in F0 through F2 generations; however, fertilization rate was decreased in low atrazine and EE2 exposure lineages in the F2 generation. There were significant transgenerational differences in expression of the genes involved in steroidogenesis and DNA methylation. These results suggest that although early life exposure to atrazine did not cause significant phenotypes in the directly exposed F0 generation, subsequent generations of fish were at greater risk of reproductive dysfunction.
Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\\or small farms with mixed signatures from different crop types and\\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R2 = 0.95 for South Korea and R2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281.
Little is known about prey use by the orangebelly darter, Etheostoma radiosum, and what is known has been described from relatively large river systems. We examined prey use by orangebelly darters from first- and second-order tributaries in the Lower Mountain Fork River of southeastern Oklahoma. Adult darters (n = 141) were captured from five tributaries in 2015, and stomach contents were examined to determine prey use. Aquatic isopods were the most frequently consumed organism. This differs notably from previous reports that insects, primarily dipterans, were the predominant prey for the species.
","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-63-2-146","usgsCitation":"Reed, M.L., Hoback, W., and Long, J.M., 2019, Winter and spring diet of the orangebelly darter, Etheostoma radiosum, among tributaries of the Lower Mountain Fork River: Southwestern Naturalist, v. 63, no. 2, p. 146-148, https://doi.org/10.1894/0038-4909-63-2-146.","productDescription":"3 p.","startPage":"146","endPage":"148","ipdsId":"IP-092269","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":382522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Lower Mountain Fork River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.72274780273438,\n 33.95589097690208\n ],\n [\n -94.53907012939453,\n 33.95589097690208\n ],\n [\n -94.53907012939453,\n 34.15499986715356\n ],\n [\n -94.72274780273438,\n 34.15499986715356\n ],\n [\n -94.72274780273438,\n 33.95589097690208\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"63","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, M. L.","contributorId":243520,"corporation":false,"usgs":false,"family":"Reed","given":"M.","email":"","middleInitial":"L.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":802463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoback, W. W.","contributorId":243288,"corporation":false,"usgs":false,"family":"Hoback","given":"W. W.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":802464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":802465,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203600,"text":"70203600 - 2019 - The importance of groundwater flow to the formation of modern thrombolitic microbialites","interactions":[],"lastModifiedDate":"2019-05-23T15:16:41","indexId":"70203600","displayToPublicDate":"2019-05-22T15:12:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1751,"text":"Geobiology","active":true,"publicationSubtype":{"id":10}},"title":"The importance of groundwater flow to the formation of modern thrombolitic microbialites","docAbstract":"Modern microbialites are often located within groundwater discharge zones, yet the role of groundwater in microbialite accretion has yet to be resolved. To understand relationships between groundwater, microbialites, and associated microbial communities, we quantified and characterized groundwater flow and chemistry in active thrombolitic microbialites in Lake Clifton, Western Australia, and compared these observations to inactive thrombolites and lakebed sediments. Groundwater flows upward through an interconnected network of pores within the microstructure of active thrombolites, discharging directly from thrombolite heads into the lake. This upwelling groundwater is fresher than lake water and is hypothesized to support microbial mat growth by reducing salinity and providing limiting nutrients in an osmotically stressful and oligotrophic habitat. This is in contrast to inactive thrombolites that show no evidence of microbial mat colonization and are infiltrated by hypersaline lake water. Groundwater discharge through active thrombolites contrasts with the surrounding lakebed, where hypersaline lake water flows downward through sandy sediments at very low rates. Based on an appreciation for the role of microorganisms in thrombolite accretion, our findings suggest conditions favorable to thrombolite formation still exist in certain locations of Lake Clifton despite increasing lake water salinity. This study is the first to characterize groundwater flow rates, paths, and chemistry within a microbialite‐forming environment and provides new insight into how groundwater can support microbial mats believed to contribute to microbialite formation in modern and ancient environments.