Industrial chemical contamination within coastal regions of the Great Lakes can pose serious risks to wetland habitat and offshore fisheries, often resulting in fish consumption advisories that directly affect human and wildlife health. Mercury (Hg) is a contaminant of concern in many of these highly urbanized and industrialized coastal regions, one of which is the Saint Louis River estuary (SLRE), the second largest tributary to Lake Superior. The SLRE has legacy Hg contamination that drives high Hg concentrations within sediments, but it is unclear whether legacy-derived Hg actively cycles within the food web. To understand the relative contributions of legacy versus contemporary Hg sources in coastal zones, Hg, carbon, and nitrogen stable isotope ratios were measured in sediments and food webs of SLRE and the Bad River, an estuarine reference site. Hg stable isotope values revealed that legacy contamination of Hg was widespread and heterogeneously distributed in sediments of SLRE, even in areas lacking industrial Hg sources. Similar isotope values were found in benthic invertebrates, riparian spiders, and prey fish from SLRE, confirming legacy Hg reaches the SLRE food web. Direct comparison of prey fish from SLRE and the Bad River confirmed that Hg isotope differences between the sites were not attributable to fractionation associated with rapid Hg bioaccumulation at estuarine mouths, but due to the presence of industrial Hg within SLRE. The Hg stable isotope values of game fish in both estuaries were dependent on fish migration and diet within the estuaries and extending into Lake Superior. These results indicate that Hg from legacy contamination is actively cycling within the SLRE food web and, through migration, this Hg also extends into Lake Superior via game fish. Understanding sources and the movement of Hg within the estuarine food web better informs restoration strategies for other impaired Great Lakes coastal zones.
Watershed degradation due to invasion threatens downstream water flows and associated ecosystem services. While this topic has been studied across landscapes that have undergone invasive-driven state changes (e.g., native forest to invaded grassland), it is less well understood in ecosystems experiencing within-system invasion (e.g. native forest to invaded forest). To address this subject, we conducted an integrated ecological and ecohydrological study in tropical forests impacted by invasive plants and animals. We measured soil infiltration capacity in multiple fenced (i.e., ungulate-free)/unfenced and native/invaded forest site pairs along moisture and substrate age gradients across Hawaii to explore the effects of invasion on hydrological processes within tropical forests. We also characterized forest composition, structure and soil characteristics at these sites to assess the direct and vegetation-mediated impacts of invasive species on infiltration capacity. Our models show that invasive ungulates negatively affect soil infiltration capacity consistently across the wide moisture and substrate age gradients considered. Additionally, several soil characteristics known to be affected by invasive ungulates were associated with local infiltration rates, indicating that the long-term secondary effects of high ungulate densities in tropical forests may be stronger than effects observed in this study. The effect of invasive plants on infiltration was complex and likely to depend on their physiognomy within existing forest community structure. These results provide clear evidence for managers that invasive ungulate control efforts can improve ecohydrological function of mesic and wet forest systems critical to protecting downstream and nearshore resources and maintaining groundwater recharge.
We compared body morphology of two freshwater sculpin taxa that inhabit distinct environmental conditions in the Chesapeake Bay watershed of eastern North America: Potomac sculpin (C. girardi, Robins; PS) and checkered sculpin (C. sp. cf. girardi; CS). Both taxa are endemic to the study area, but PS are more broadly distributed than CS which are limited to karst groundwater-dominated streams in the central Potomac River basin. We examined preserved specimens from sites encompassing their geographic range (six sites per taxon) to evaluate taxonomic differences and environmental effects. Pelvic fin ray counts and body shape distinguished the study taxa. Morphological variation exhibited stronger relationships to environmental covariates (site elevation and basin size) in PS than CS as expected. In addition, the frequency of specimens with a united median chin pore increased with site elevation in PS (but not CS), suggesting thermal effects on preoperculomanibular canal development. However, contrary to expectation, PS did not exhibit greater among-population variation in body shape than CS, and this indicates the potential importance of unmeasured environmental differences among karst groundwater-dominated streams in the study area. Our study also indicated the utility of stream-level management units for CS, an undescribed species recognized as “critically imperiled” by state agencies.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-021-01078-8","usgsCitation":"Hitt, N.P., Kessler, K.G., Macmillan, H.E., Rogers, K.M., and Raesly, R.L., 2021, Comparative morphology of freshwater sculpin inhabiting different environmental conditions in the Chesapeake Bay headwaters: Environmental Biology of Fishes, v. 104, p. 309-324, https://doi.org/10.1007/s10641-021-01078-8.","productDescription":"16 p.","startPage":"309","endPage":"324","ipdsId":"IP-118788","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":384404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","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 -77.76123046875,\n 37.19533058280065\n ],\n [\n -74.99267578125,\n 37.19533058280065\n ],\n [\n -74.99267578125,\n 39.791654835253425\n ],\n [\n -77.76123046875,\n 39.791654835253425\n ],\n [\n -77.76123046875,\n 37.19533058280065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","noUsgsAuthors":false,"publicationDate":"2021-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":812292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kessler, Karmann G. 0000-0001-5681-4909","orcid":"https://orcid.org/0000-0001-5681-4909","contributorId":242765,"corporation":false,"usgs":true,"family":"Kessler","given":"Karmann","email":"","middleInitial":"G.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":812293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macmillan, Hannah Eisemann 0000-0002-5221-4989","orcid":"https://orcid.org/0000-0002-5221-4989","contributorId":255404,"corporation":false,"usgs":true,"family":"Macmillan","given":"Hannah","email":"","middleInitial":"Eisemann","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":812294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Karli M. 0000-0002-6188-7405","orcid":"https://orcid.org/0000-0002-6188-7405","contributorId":237955,"corporation":false,"usgs":true,"family":"Rogers","given":"Karli","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":812295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raesly, Richard L.","contributorId":172208,"corporation":false,"usgs":false,"family":"Raesly","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":13481,"text":"Department of Biology, Frostburg State University, 101 Braddock Road, Frostburg, MD","active":true,"usgs":false}],"preferred":false,"id":812296,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231651,"text":"70231651 - 2021 - Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-05-18T15:38:14.741057","indexId":"70231651","displayToPublicDate":"2021-03-12T10:34:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","docAbstract":"Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km2. Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.
","language":"English","publisher":"Springer Link","doi":"10.1007/s00267-021-01450-5","usgsCitation":"Maloney, K.O., Carlisle, D.M., Buchanan, C., Rapp, J.L., Austin, S.H., Cashman, M.J., and Young, J.A., 2021, Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed: Environmental Management, v. 67, p. 1171-1185, https://doi.org/10.1007/s00267-021-01450-5.","productDescription":"15 p.","startPage":"1171","endPage":"1185","ipdsId":"IP-121380","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-021-01450-5","text":"Publisher Index Page"},{"id":400761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay 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jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":843239,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218782,"text":"sir20215014 - 2021 - Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020","interactions":[],"lastModifiedDate":"2021-03-15T11:42:02.813757","indexId":"sir20215014","displayToPublicDate":"2021-03-12T08:09:47","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5014","displayTitle":"Extending Seasonal Discharge Records for Streamgage Sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through Water Year 2020","title":"Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020","docAbstract":"Daily mean discharge records are needed for management of selected streams in the Fortymile River Basin. The U.S. Geological Survey, in cooperation with the U.S. Bureau of Land Management, updated a technique for estimating seasonal (partial year) discharge at two short-record streamgage sites in the basin and evaluated the accuracy of the estimates. Daily mean discharge values were estimated for May 15–September 30, 1976–82 and 2006–18, for U.S. Geological Survey streamgage sites 15330000 (North Fork Fortymile River above Middle Fork near Franklin, Alaska) and 15331000 (Middle Fork Fortymile River near mouth near Chicken, Alaska). Relations between discharge for each study streamgage and an index streamgage on the main-stem Fortymile River (15348000, Fortymile River near Steele Creek, Alaska) for concurrent seasonal periods in 2019 and 2020 were developed using the maintenance of variance extension type 3 (MOVE.3) record extension technique. The MOVE.3 regressions were used to estimate daily mean discharges at the study streamgage sites for the selected season for the longer period of record of the index streamgage. Additionally, estimated records were generated from the regressions for the concurrent seasonal periods to evaluate the accuracy of the record extension techniques. The modified Nash-Sutcliffe efficiency coefficients for the estimated records were 0.53 for the North Fork Fortymile River (15330000) and 0.70 for the Middle Fork Fortymile River (15331000) streamgages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215014","collaboration":"Prepared in cooperation with the U.S. Bureau of Land Management","usgsCitation":"Curran, J.H., 2021, Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2020: U.S. Geological Survey Scientific Investigations Report 2021–5014, 11 p., https://doi.org/10.3133/sir20215014.","productDescription":"Report: v, 11 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-125266","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":384327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5014/sir20215014.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5014"},{"id":384361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VCAOEZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Extended seasonal discharge records for selected streamgage sites in the Fortymile River Basin, Alaska, 1976-2020"},{"id":384326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5014/coverthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Fork Fortymile River, Middle Fork Fortymile River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.46972656249997,\n 62.91523303947614\n ],\n [\n -141.0205078125,\n 62.91523303947614\n ],\n [\n -141.0205078125,\n 65.60387765860433\n ],\n [\n -146.46972656249997,\n 65.60387765860433\n ],\n [\n -146.46972656249997,\n 62.91523303947614\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The benthic foraminifers Bulimina denudata and Eggerelloides advenus are commonly abundant in offshore regions in the Pacific Ocean, especially in waste-discharge sites. The relationship between their abundance and standard macrofaunal sediment toxicity tests (amphipod survival and sea urchin fertilization) as well as sediment chemistry analyte measurements were determined for sediments collected in 1997 in Santa Monica Bay, California, USA, an area impacted by historical sewage input from the Hyperion Outfall primarily since the late 1950s. Very few surface samples proved to be contaminated based on either toxicity or chemistry tests and the abundance of B. denudata did not correlate with any of these. The abundance of E. advenus also did not correlate with toxicity, but positively correlated with total solids and negatively correlated with arsenic, beryllium, chromium, lead, mercury, nickel, zinc, iron, and TOC. In contrast, several downcore samples proved to be contaminated as indicated by both toxicity and chemistry data. The abundance of B. denudata positively correlated with amphipod survival and negatively correlated with arsenic, cadmium, unionized ammonia, and TOC; E. advenus negatively correlated with sea urchin fertilization success as well as beryllium, cadmium, and total PCBs. As B. denudata and E. advenus are tolerant of polluted sediments and their relative abundances appear to track those of macrofaunal toxicity tests, their use as cost- and time-effective marine sediment toxicity tests may have validity and should be further investigated.
","language":"English","publisher":"MDPI","doi":"10.3390/w13060775","usgsCitation":"McGann, M., 2021, Potential use of the benthic foraminifers Bulimina denudata and Eggerelloides advenus in marine sediment toxicity testing: Water, v. 13, no. 6, 775, 33 p., https://doi.org/10.3390/w13060775.","productDescription":"775, 33 p.","ipdsId":"IP-117658","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453114,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13060775","text":"Publisher Index Page"},{"id":385443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.58343505859374,\n 34.14590795200977\n ],\n [\n -118.85009765625,\n 33.708347493688414\n ],\n [\n -118.23486328125,\n 33.458942753687644\n ],\n [\n -117.77618408203124,\n 33.56199537293026\n ],\n [\n -118.28979492187499,\n 33.916013113401696\n ],\n [\n -118.98468017578125,\n 34.15045403191448\n ],\n [\n -119.34997558593749,\n 34.35023911062779\n ],\n [\n -119.58343505859374,\n 34.14590795200977\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":815133,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70219433,"text":"70219433 - 2021 - Eastward expansion of Round Goby in New York: Assessment of detection methods and current range","interactions":[],"lastModifiedDate":"2021-04-06T12:01:57.537653","indexId":"70219433","displayToPublicDate":"2021-03-12T06:55:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Eastward expansion of Round Goby in New York: Assessment of detection methods and current range","docAbstract":"The Round Goby Neogobius melanostomus has spread rapidly around the Great Lakes region since its introduction to North America in 1990. In 2014, a specimen was captured in the New York State Canal System west of Utica, prompting concerns that Round Goby would soon reach the ecologically and economically valuable watersheds of Lake Champlain and the Hudson River estuary. The establishment of Round Goby populations elsewhere has been linked to a number of negative ecological consequences, yet methods for monitoring the invasion front of this species remain limited. The objectives of this study were to assess the current distribution of Round Goby in central New York and to determine the most effective methods for monitoring the invasion front. This was achieved by concurrently using benthic trawling, seining, minnow traps, and environmental DNA (eDNA) twice annually from 2016 to 2019 at 12 sites on the canal system between Oneida Lake and the Hudson River. Of the three traditional gear types, benthic trawling was the most effective method and captured Round Goby as far east as Utica by 2019. This finding suggests only minimal eastward expansion of Round Goby occurred between 2014 and 2019. Round Goby DNA was detected in water samples during all surveys in which individuals were captured with trawling, and the estimated concentration of DNA explained 69% of the variability in trawl catch. At multiple study sites, Round Goby DNA was identified during consecutive surveys before Round Goby were first captured with trawling. This suggests that in lotic waters, eDNA has the potential to forecast or serve as a sentinel for the expansion of Round Goby to new locations. Our results demonstrate the importance of using eDNA in a repeated sampling framework and supplementing eDNA sampling with some level of effort with traditional sampling methods.
We use over 100 in situ and remotely sensed temperature datasets to investigate thermal variability within and across the intertidal nearshore, coastal and offshore waters of the northern Gulf of Alaska. For the years 1970 through 2019 we document a warming trend of 0.24±0.10 °C per decade for the coastal northern shelf (0-250 m depth average) and a Gulf-wide sea surface temperature (SST) trend of 0.25±0.11 °C per decade. The Gulf-wide SST trend in the last halfcentury is more than twice that of the 0.11±0.003 °C warming rate computed for 1900-2019. Decorrelation length scales vary regionally and correlation of synoptic scale fluctuations (less than one month) between two stations rapidly degrades with increasing station distance, accounting for less than 10% of the covariance for separations exceeding 100 km. In contrast, stations separated by as much as 500 km retain 50% of their covariance in common for seasonal and sub-seasonal fluctuations. While satellite-based measures often capture most of the daily SST anomaly in coastal and offshore waters, a significant portion of the variance (30-40%) can remain unresolved, even exceeding 75% in the nearshore realm. Similarly, the North Pacific and Gulf of Alaska leading modes of SST variability leave large fractions (25-50%) of the subseasonal thermal variance unresolved. These evaluations show the importance of in situ temperature records for studies that seek to understand mechanistic responses of marine organisms to habitat variability at biologically important time and space scales. We find that near-bottom temperature anomalies on the outer shelf vary inversely with surface temperatures and with near-bottom salinity, suggesting that thermal anomalies are also linked with nutrient flux anomalies. A case study of the recent Pacific marine heatwave and transition out of preceding cool years shows that the northern Gulf of Alaska surface temperatures (0-50 m) were elevated from 2014 to 2019 relative to the long-term record. Coastal temperatures warmed contemporaneously with offshore waters through the 2013 calendar year. In contrast, deep inner shelf waters (200-250 m) exhibited delayed warming relative to the surface and relative to deep waters offshore at the same depth. While offshore surface waters cooled from early 2014 into 1-2 Science Synthesis Final Report Gulf Watch Alaska, 2021 early 2016, the shelf continued to warm over this time as the effects of local air-sea and advective heat fluxes continued to permeate across the northern Gulf. These results highlight the importance of different heating mechanisms for surface and near-bottom waters across the northern Gulf of Alaska.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The Pacific marine heatwave: Monotoring during a major perturbation in the Gulf of Alaska","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council","usgsCitation":"Danielson, S.L., Hennon, T.D., Monson, D., Suryan, R.M., Campbell, R.W., Baird, S.J., Holderied, K., and Weingartner, T., 2021, A study of marine temperature variations in the northern Gulf of Alaska across years of marine heatwaves and cold spells: Gulf Watch Alaska Long-Term Monitoring Program Synthesis Report, 56 p.","productDescription":"56 p.","startPage":"1-1","endPage":"1-56","ipdsId":"IP-119985","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":400044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400013,"type":{"id":15,"text":"Index Page"},"url":"https://gulfwatchalaska.org/resources/reports/science-synthesis-reports/"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.95703125,\n 54.87660665410869\n ],\n [\n -134.208984375,\n 58.401711667608\n ],\n [\n -140.712890625,\n 60.50052541051131\n ],\n [\n -147.568359375,\n 62.186013857194226\n ],\n [\n -153.017578125,\n 61.3546135846894\n ],\n [\n -161.89453125,\n 55.57834467218206\n ],\n [\n -164.443359375,\n 54.316523240258256\n ],\n [\n -162.24609375,\n 52.74959372674114\n ],\n [\n -143.7890625,\n 51.01375465718821\n ],\n [\n -132.626953125,\n 52.908902047770255\n ],\n [\n -130.95703125,\n 54.87660665410869\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Danielson, Seth L.","contributorId":256682,"corporation":false,"usgs":false,"family":"Danielson","given":"Seth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":842031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hennon, Tyler D.","contributorId":291317,"corporation":false,"usgs":false,"family":"Hennon","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":842032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":842033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suryan, Rob M.","contributorId":291318,"corporation":false,"usgs":false,"family":"Suryan","given":"Rob","email":"","middleInitial":"M.","affiliations":[{"id":62685,"text":"Alaska Fisheries Science Center, NOAA","active":true,"usgs":false}],"preferred":false,"id":842034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Rob W.","contributorId":251805,"corporation":false,"usgs":false,"family":"Campbell","given":"Rob","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":842035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baird, Steven J.","contributorId":12375,"corporation":false,"usgs":false,"family":"Baird","given":"Steven","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":842036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holderied, Kristine","contributorId":291319,"corporation":false,"usgs":false,"family":"Holderied","given":"Kristine","affiliations":[{"id":62686,"text":"Kasitsna Bay Laboratory, NOAA","active":true,"usgs":false}],"preferred":false,"id":842037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weingartner, Thomas","contributorId":291321,"corporation":false,"usgs":false,"family":"Weingartner","given":"Thomas","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":842038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70225526,"text":"70225526 - 2021 - Pore water exchange-driven inorganic carbon export from intertidal salt marshes","interactions":[],"lastModifiedDate":"2021-10-20T13:06:17.578828","indexId":"70225526","displayToPublicDate":"2021-03-11T08:02:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Pore water exchange-driven inorganic carbon export from intertidal salt marshes","docAbstract":"Respiration in intertidal salt marshes generates dissolved inorganic carbon (DIC) that is exported to the coastal ocean by tidal exchange with the marsh platform. Understanding the link between physical drivers of water exchange and chemical flux is a key to constraining coastal wetland contributions to regional carbon budgets. The spatial and temporal (seasonal, annual) variability of marsh pore water exchange and DIC export was assessed from a microtidal salt marsh (Sage Lot Pond, Massachusetts). Spatial variability was constrained from 224Ra : 228Th disequilibria across two hydrologic units within the marsh sediments. Disequilibrium between the more soluble 224Ra and its sediment-bound parent 228Th reveals significant pore water exchange in the upper 5 cm of the marsh surface (0–36 L m−2 d−1) that is most intense in low marsh elevation zones, driven by tidal overtopping. Surficial sediment DIC transport ranges from 0.0 to 0.7 g C m−2 d−1. The sub-surface sediment horizon intersected by mean low tide was disproportionately impacted by tidal pumping (20–80 L m−2 d−1) and supplied a seasonal DIC flux of 1.7–5.4 g C m−2 d−1. Export exceeded 10 g C m−2 d−1 for another marsh unit, demonstrating that fluxes can vary substantially across salt marshes under similar conditions within the same estuary. Seasonal and annual variability in marsh pore water exchange, constrained from tidal time-series of radium isotopes, was driven in part by variability in mean sea level. Rising sea levels will further inundate high marsh elevation zones, which may lead to greater DIC export.
In coarse resolution hydrological modeling we face the problem of subgrid variability, the effects of which are difficult to express and are often hidden in the parameterization and calibration. We present a numerical experiment with the physically based hydrological model ParFlow‐CLM with which we quantify the effect of subgrid heterogeneities in headwater catchments within the cell size typically used for regional hydrological applications. We simulate homogeneous domains and domains with subgrid heterogeneities in topography or soil thickness for two climates and soil types. The presence of side slope is the main error source, leading to large underestimation of runoff, and marginally also of evapotranspiration. The spatial distribution of soil saturation in the presence of subgrid variability in topography also leads to underestimation of landslide risk. Soil thickness is the second influential subgrid property, affecting soil moisture distribution and surface runoff formation. Results are consistent for the climates and the soil types considered. The topographic wetness index approach is tested as a way to downscale soil moisture simulations within the domain. Although this method is successful in reproducing some spatial variability and patterns, it fails when the coarse grid mean soil saturation is inaccurate or subgrid topography does not represent subsurface flow paths accurately. We conclude that ignoring subgrid variability in topography and soil thickness in coarse‐scale hydrological models may lead locally to underestimation of runoff and slope instability. Users of such models should be aware of these biases and consider ways to include subgrid effects in coarse‐scale hydrological predictions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027326","usgsCitation":"Leonarduzzi, E., Maxwell, R.M., Mirus, B.B., and Molnar, P., 2021, Numerical analysis of the effect of subgrid variability in a physically based hydrological model on runoff, soil moisture, and slope stability: Water Resources Research, v. 57, no. 4, e2020WR027326, 16 p., https://doi.org/10.1029/2020WR027326.","productDescription":"e2020WR027326, 16 p.","ipdsId":"IP-124808","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":453131,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020wr027326","text":"External Repository"},{"id":384495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Leonarduzzi, E. 0000-0002-6811-9118","orcid":"https://orcid.org/0000-0002-6811-9118","contributorId":255523,"corporation":false,"usgs":false,"family":"Leonarduzzi","given":"E.","email":"","affiliations":[{"id":51571,"text":"Institute of Environmental Engineering, ETH Zurich, Switzerland; Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":812489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maxwell, R. M.","contributorId":255524,"corporation":false,"usgs":false,"family":"Maxwell","given":"R.","email":"","middleInitial":"M.","affiliations":[{"id":51573,"text":"Integrated Groundwater Modeling Center and Department of Geology and Geological Engineering, Colorado School of Mines, Golden, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":812490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":812491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molnar, P. 0000-0001-6437-4931","orcid":"https://orcid.org/0000-0001-6437-4931","contributorId":255525,"corporation":false,"usgs":false,"family":"Molnar","given":"P.","email":"","affiliations":[{"id":51575,"text":"Institute of Environmental Engineering, ETH Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":812492,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218822,"text":"70218822 - 2021 - Population density and stream-habitat relations of the Yellowcheek Darter (Nothonotus moorei) among the headwaters of the Little Red River in Arkansas","interactions":[],"lastModifiedDate":"2021-03-16T11:45:53.545635","indexId":"70218822","displayToPublicDate":"2021-03-11T06:37:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Population density and stream-habitat relations of the Yellowcheek Darter (Nothonotus moorei) among the headwaters of the Little Red River in Arkansas","docAbstract":"Nothonotus moorei (Yellowcheek Darter [YCD]) is an endangered species endemic to the headwaters of the Little Red River in north-central Arkansas. Population decline, habitat loss and fragmentation, and threats from land use and seasonal drought necessitate monitoring of population density and distribution to determine ecological and habitat associations. We evaluated YCD density and associated stream-habitat variables from 9 sites in the South Fork, Archey Fork, Middle Fork, and Beech Fork of the Little Red River from March to April 2018. Yellowcheek Darters were present at all 9 sites and 19 of 23 riffles sampled. Densities were generally comparable or higher than reported in previous studies, and we collected YCD at some sites at which they were considered previously extirpated, suggesting a rather stable population and evidence of recolonization of some sites since they were last surveyed. Yellowcheek Darter density was significantly negatively related to substrate embeddedness, and the consistent relation to embeddedness in this study and other studies suggest that this species is vulnerable to sedimentation.
","language":"English","publisher":"BioOne","doi":"10.1656/058.020.0124","usgsCitation":"Driver, L., and Justus, B., 2021, Population density and stream-habitat relations of the Yellowcheek Darter (Nothonotus moorei) among the headwaters of the Little Red River in Arkansas: Southeastern Naturalist, v. 20, no. 1, p. 227-244, https://doi.org/10.1656/058.020.0124.","productDescription":"18 p.","startPage":"227","endPage":"244","ipdsId":"IP-095659","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":384400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Little Red River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.65869140625,\n 35.37113502280101\n ],\n [\n -91.56005859375,\n 35.37113502280101\n ],\n [\n -91.56005859375,\n 35.96022296929667\n ],\n [\n -92.65869140625,\n 35.96022296929667\n ],\n [\n -92.65869140625,\n 35.37113502280101\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Driver, Lucas 0000-0003-2549-1849","orcid":"https://orcid.org/0000-0003-2549-1849","contributorId":219176,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Justus, Billy 0000-0002-3458-9656 bjustus@usgs.gov","orcid":"https://orcid.org/0000-0002-3458-9656","contributorId":202148,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812291,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218752,"text":"ofr20211026 - 2021 - Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","interactions":[],"lastModifiedDate":"2021-04-07T01:36:23.477755","indexId":"ofr20211026","displayToPublicDate":"2021-03-10T15:49:09","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1026","displayTitle":"Expected Warning Times from the ShakeAlert® Earthquake Early Warning System for Earthquakes in the Pacific Northwest","title":"Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest","docAbstract":"The ShakeAlert® earthquake early warning system has been live since October 2019 for the testing of public alerting to mobile devices in California and will soon begin testing this modality in Oregon and Washington. The Pacific Northwest presents new challenges and opportunities for ShakeAlert owing to the different types of earthquakes that occur in the Cascadia subduction zone. Many locations in the Pacific Northwest are expected to experience shaking from shallow crustal earthquakes (similar to those in California), earthquakes that occur deep within the subducted slab, and large megathrust earthquakes that occur primarily offshore. The different geometries and maximum magnitudes associated with these types of earthquakes lead to a range of warning times that are possible between when the initial ShakeAlert Message is issued and when a user experiences strong shaking. After an earthquake begins, the strategy of the ShakeAlert system for public alerting is to warn people who are located close enough to the fault that the system estimates they will experience at least weak to moderate shaking. By alerting the public at these low levels of expected shaking, it is possible to provide sufficient warning times for some users to take protective actions before strong shaking begins. In this study, we present an analysis of past ShakeAlert Messages as well as simulations of historical earthquakes and potential future Cascadia earthquakes to quantify the range of warning times that users who experience strong or worse shaking are likely to receive. Additional applications for ShakeAlert involve initiation of automatic protective actions prior to the onset of shaking, such as slowing trains, shutting water supplies, and opening firehouse doors, which are beyond the scope of this paper. Users in the Pacific Northwest should expect that the majority of alerts they receive will be from shallow crustal and intraslab earthquakes. In these cases, users will only have a few seconds of warning before strong shaking begins. This remains true even during infrequent, offshore great (magnitude ≥8) megathrust earthquakes, where warning times will generally range from seconds to tens of seconds, depending on the user’s location and the intensity of predicted shaking that a user chooses to be alerted for, with the longest warning times of 50–80 seconds possible only for users located at considerable distance from the epicenter. ShakeAlert thus requires short, readily understood alerts stating that earthquake shaking is imminent and suggesting protective actions users should take. Extensive education and outreach efforts that emphasize the need to take actions quickly will be required for ShakeAlert to successfully reduce injuries and losses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211026","usgsCitation":"McGuire, J.J., Smith, D.E., Frankel, A.D., Wirth, E.A., McBride, S.K., and de Groot, R.M., 2021, Expected warning times from the ShakeAlert earthquake early warning system for earthquakes in the Pacific Northwest (ver. 1.1, March 24, 2021): U.S. Geological Survey Open-File Report 2021–1026, 37 p., https://doi.org/10.3133/ofr20211026.","productDescription":"v, 37 p.","onlineOnly":"Y","ipdsId":"IP-125131","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384638,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1026/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":384281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1026/ofr20211026_v1.1.pdf","text":"Report","size":"12 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\"}}]}","edition":"Version 1.0: Marhc 10, 2021; Version 1.1: March 24, 2021","contact":"Earthquake Science Center—Menlo Park, Calif. Office
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
The St. Clair-Detroit River System contains a world-class Great Lakes muskellunge (Esox masquinongy) fishery that has avoided the declines observed in many Great Lakes muskellunge populations. Muskellunge are an upper trophic level predator, and therefore a naturally low-density species. Limited fishery-independent data exist on which to base management decisions. To remedy this, we initiated an acoustic telemetry study in May of 2016, in collaboration with the Great Lakes Acoustic Telemetry Observation System. Our objective was to describe patterns of movement of muskellunge in this large and open system to better understand their spatial ecology. We acoustically tagged 133 muskellunge in the Detroit River and Lake St. Clair, and movements of 58 fish that passed our data quality control screens were analyzed. We utilized mixed modelling to assess the effects of sex, length, release location, and season on daily movement rates. We found that movement rates only differed among seasons, with highest movement rates occurring in the fall and lowest movement rates in the winter. Muskellunge tagged at different locations exhibited distinct residency patterns, and fish frequently crossed jurisdictional and waterbody boundaries. Ultimately our study highlights the scope and patterns of muskellunge movement in a large, unimpounded system and demonstrates that management of these fish would benefit from consideration of their full distribution covering multiple management jurisdictions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2020.12.006","usgsCitation":"Hessenauer, J., Harris, C., Marklevitz, S., Faust, M.D., Thorn, M.W., Utrup, B., and Hondorp, D.W., 2021, Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management: Journal of Great Lakes Research, v. 47, no. 2, p. 475-485, https://doi.org/10.1016/j.jglr.2020.12.006.","productDescription":"11 p.","startPage":"475","endPage":"485","ipdsId":"IP-121684","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":385423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Clair – Detroit River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.16650390625,\n 42.039094188385945\n ],\n [\n -82.99072265625,\n 42.285437007491545\n ],\n [\n -82.37548828125,\n 42.28746890196628\n ],\n [\n -82.42218017578125,\n 42.5733097370664\n ],\n [\n -82.38372802734375,\n 43.022721607058344\n ],\n [\n -82.496337890625,\n 43.022721607058344\n ],\n [\n -82.63641357421875,\n 42.7349091465156\n ],\n [\n -82.95501708984375,\n 42.64608143458068\n ],\n [\n -83.045654296875,\n 42.49235259142821\n ],\n [\n -83.232421875,\n 42.28340504748081\n ],\n [\n -83.22418212890625,\n 42.071723466810774\n ],\n [\n -83.16650390625,\n 42.039094188385945\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hessenauer, Jan-Michael","contributorId":257795,"corporation":false,"usgs":false,"family":"Hessenauer","given":"Jan-Michael","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Cleyo","contributorId":257796,"corporation":false,"usgs":false,"family":"Harris","given":"Cleyo","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marklevitz, Stephen","contributorId":257797,"corporation":false,"usgs":false,"family":"Marklevitz","given":"Stephen","email":"","affiliations":[{"id":52125,"text":"Ontario Ministry of Natural Resources & Forestry","active":true,"usgs":false}],"preferred":false,"id":815042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faust, Matthew D.","contributorId":257798,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorn, Michael W.","contributorId":257799,"corporation":false,"usgs":false,"family":"Thorn","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":52125,"text":"Ontario Ministry of Natural Resources & Forestry","active":true,"usgs":false}],"preferred":false,"id":815044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Utrup, Brad","contributorId":257800,"corporation":false,"usgs":false,"family":"Utrup","given":"Brad","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815045,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815046,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219076,"text":"70219076 - 2021 - Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams","interactions":[],"lastModifiedDate":"2021-05-27T13:21:52.551307","indexId":"70219076","displayToPublicDate":"2021-03-10T10:18:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams","docAbstract":"Improved analytical methods can quantify hundreds of pesticide transformation products (TPs), but understanding of TP occurrence and potential toxicity in aquatic ecosystems remains limited. We quantified 108 parent pesticides and 116 TPs in more than 3 700 samples from 442 small streams in mostly urban basins across five major regions of the United States. TPs were detected nearly as frequently as parents (90 and 95% of streams, respectively); 102 TPs were detected at least once and 28 were detected in >20% samples in at least one region—TPs of 9 herbicides, 2 fungicides (chlorothalonil and thiophanate-methyl), and 1 insecticide (fipronil) were the most frequently detected. TPs occurred commonly during baseflow conditions, indicating chronic environmental TP exposures to aquatic organisms and the likely importance of groundwater as a TP source. Hazard quotients based on acute aquatic-life benchmarks for invertebrates and nonvascular plants and vertebrate-centric molecular endpoints (sublethal effects) quantify the range of the potential contribution of TPs to environmental risk and highlight several TP exposure–response data gaps. A precautionary approach using equimolar substitution of parent benchmarks or endpoints for missing TP benchmarks indicates that potential aquatic effects of pesticide TPs could be underestimated by an order of magnitude or more.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06625","usgsCitation":"Mahler, B., Nowell, L.H., Sandstrom, M.W., Bradley, P., Romanok, K., Konrad, C., and Van Metre, P., 2021, Inclusion of pesticide transformation products is key to estimating pesticide exposures and effects in small U.S. streams: Environmental Science and Technology, v. 55, no. 8, p. 4740-4752, https://doi.org/10.1021/acs.est.0c06625.","productDescription":"13 p.","startPage":"4740","endPage":"4752","ipdsId":"IP-122426","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science 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M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Konrad, Christopher 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":220231,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812677,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Metre, Peter 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":255624,"corporation":false,"usgs":false,"family":"Van Metre","given":"Peter","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":812678,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219129,"text":"70219129 - 2021 - Partitioning and transformation of organic and inorganic phosphorus among dissolved, colloidal and particulate phases in a hypereutrophic freshwater estuary","interactions":[],"lastModifiedDate":"2021-03-25T13:25:59.68269","indexId":"70219129","displayToPublicDate":"2021-03-10T08:24:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Partitioning and transformation of organic and inorganic phosphorus among dissolved, colloidal and particulate phases in a hypereutrophic freshwater estuary","docAbstract":"Phosphorus (P) loadings to the Great Lakes have been regulated for decades, but re-eutrophication and seasonal hypoxia have recently been increasingly reported. It is of paramount importance to better understand the fate, transformation, and biogeochemical cycling processes of different P species across the river-lake interface. We report here results on chemical speciation of P in the seasonally hypoxic Fox River-Green Bay system and variations in sources and partitioning of P species along the aquatic continuum. During midsummer when productivity is generally high, phosphate and dissolved organic P (DOP) were the major species in river water while particulate-organic-P predominated in open bay waters, showing a dynamic change in the chemical speciation of P along the river-bay transect with active transformations between inorganic and organic P and between colloidal and particulate phases. Colloidal organic P (COP, >1 kDa) comprised 33‒65% of the bulk DOP, while colloidal inorganic P was generally insignificant and undetectable especially in open bay water. Sources of COP changed from mainly allochthonous in the Fox River, having mostly smaller sized colloids (1–3 kDa) and a lower organic carbon to phosphorus (C/P) ratio, to predominantly autochthonous in open bay waters with larger sized colloids (>10 kDa) and a higher organic C/P ratio. The observed high apparent distribution coefficients (Kd) of P between dissolved and particulate phases and high-abundant autochthonous colloidal and particulate organic P in the hypereutrophic environment suggest that, in addition to phosphate, colloidal/particulate organic P may play a critical role in the biogeochemical cycling of P and the development of seasonal hypoxia.
Hawai'i's endangered waterbirds have experienced epizootics caused by ingestion of prey that accumulated a botulinum neurotoxin produced by the anaerobic bacterium Clostridium botulinum (avian botulism; Type C). Waterbird carcasses, necrophagous flies, and their larvae initiate and spread avian botulism, a food-borne paralytic disease lethal to waterbirds. Each new carcass has potential to develop toxin-accumulating necrophagous vectors amplifying outbreaks and killing hundreds of endangered waterbirds. Early carcass removal is an effective mitigation strategy for preventing avian intoxication, toxin concentration in necrophagous and secondary food webs, and reducing the magnitude of epizootics. However, rapid detection of carcasses can be problematic and labor intensive. Therefore, we tested a new method using scent detection canines for avian botulism surveillance on Kaua'i Island. During operational surveillance and a randomized double-blind field trial, trained detector canines with experienced field handlers improved carcass detection probability, especially in dense vegetation. Detector canines could be combined with conventional surveillance to optimize search strategies for carcass removal and are a useful tool to reduce risks of the initiation and propagation of avian botulism.
","language":"English","publisher":"Wiley","doi":"10.1111/csp2.397","usgsCitation":"Reynolds, M.H., Johnson, K.N., Schvaneveldt, E., Dewy, D.L., Uyehara, K.J., and Hess, S.C., 2021, Efficacy of detection canines for avian botulism surveillance and mitigation: Conservation Science and Practice, v. 3, no. 6, e397, 18 p., https://doi.org/10.1111/csp2.397.","productDescription":"e397, 18 p.","ipdsId":"IP-114784","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":488913,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.397","text":"Publisher Index Page"},{"id":436467,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C4N47X","text":"USGS data release","linkHelpText":"Kaua'i Avian Botulism Surveillance Using Detector Canines 2017-2018"},{"id":386983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"3","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Reynolds, Michelle H 0000-0001-7253-8158","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":245720,"corporation":false,"usgs":false,"family":"Reynolds","given":"Michelle","email":"","middleInitial":"H","affiliations":[{"id":49297,"text":"USGS PIERC (formerly)","active":true,"usgs":false}],"preferred":false,"id":818711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kyoko N","contributorId":260779,"corporation":false,"usgs":false,"family":"Johnson","given":"Kyoko","email":"","middleInitial":"N","affiliations":[{"id":52675,"text":"Country Canines, LLC","active":true,"usgs":false}],"preferred":false,"id":818716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schvaneveldt, Eleni","contributorId":260778,"corporation":false,"usgs":false,"family":"Schvaneveldt","given":"Eleni","email":"","affiliations":[{"id":39456,"text":"USGS-PIERC (formerly)","active":true,"usgs":false}],"preferred":false,"id":818715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewy, Dan L","contributorId":260777,"corporation":false,"usgs":false,"family":"Dewy","given":"Dan","email":"","middleInitial":"L","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":818714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Uyehara, Kim J","contributorId":260776,"corporation":false,"usgs":false,"family":"Uyehara","given":"Kim","email":"","middleInitial":"J","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":818712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hess, Steven C.","contributorId":176679,"corporation":false,"usgs":false,"family":"Hess","given":"Steven","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":818713,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220157,"text":"70220157 - 2021 - Probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass","interactions":[],"lastModifiedDate":"2021-04-22T14:31:36.304212","indexId":"70220157","displayToPublicDate":"2021-03-09T09:29:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":861,"text":"Aquatic Botany","active":true,"publicationSubtype":{"id":10}},"title":"Probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass","docAbstract":"Levels of submersed aquatic vegetation (SAV) are commonly assessed using a modified garden rake. However, the utility of the rake sampling method relative to methods that are typically viewed as more definitive (and expensive) such as snorkeling and coring remains a matter of debate. This study explores whether probabilities of species detections for four SAV species varied among sampling units in a rake-biomass study and, if so, whether such variation reflected variation in species abundance. Variation in detection probabilities, when unaddressed, may yield biased estimators of percent frequency of occurrence (“occupancy”) and of occurrence-habitat associations. Biomass-driven variation in detection probabilities is important because such variation may not be explainable using covariates typically measured when sampling using the rake method. This study found substantial among-unit variation in detection probabilities, with majorities of that variation on the logit or modeling scale being associated with biomass but not with the non-biomass covariates substrate type, water depth and day of study. The study closes by exploring sampling protocols and modeling methods that may yield improved SAV occupancy estimates.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquabot.2021.103375","usgsCitation":"Gray, B.R., 2021, Probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass: Aquatic Botany, v. 171, 103375, 7 p., https://doi.org/10.1016/j.aquabot.2021.103375.","productDescription":"103375, 7 p.","ipdsId":"IP-123221","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436468,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZM11FY","text":"USGS data release","linkHelpText":"SAS Code: Estimating probabilities of detecting submersed aquatic vegetation species using a rake method may vary with biomass."},{"id":385277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":814599,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237781,"text":"70237781 - 2021 - Development and validation of a spatially-explicit agent-based model for space utilization by African savanna elephants (Loxodonta africana) based on determinants of movement","interactions":[],"lastModifiedDate":"2022-10-24T14:38:38.267353","indexId":"70237781","displayToPublicDate":"2021-03-09T09:28:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development and validation of a spatially-explicit agent-based model for space utilization by African savanna elephants (Loxodonta africana) based on determinants of movement","title":"Development and validation of a spatially-explicit agent-based model for space utilization by African savanna elephants (Loxodonta africana) based on determinants of movement","docAbstract":"African elephants (Loxodonta africana) are well-studied and inhabit diverse landscapes that are being transformed by both humans and natural forces. Most tools currently in use are limited in their ability to predict how elephants will respond to novel changes in the environment. Individual-, or agent-based modeling (ABM), may extend current methods in addressing and predicting spatial responses to environmental conditions over time. We developed a spatially explicit agent-based model to simulate elephant space use and validated the model with movement data from elephants in Kruger National Park (KNP) and Chobe National Park (CNP). We simulated movement at an hourly scale, as this scale can reflect switches in elephant behavior due to changes in internal states and short-term responses to the local availability and distribution of critical resources, including forage, water, and shade. Known internal drivers of elephant movement, including perceived temperature and the time since an individual last visited a water source, were linked to the external environment through behavior-based movement rules. Simulations were run on model landscapes representing the wet season and the hot, dry season for both parks. The model outputs, including home range size, daily displacement distance, net displacement distance, and maximum distance traveled from a permanent water source, were evaluated through qualitative and quantitative comparisons to actual elephant movement data from both KNP and CNP. The ABM was successful in reproducing the differences in daily displacements between seasons in each park, and in distances traveled from a permanent water source between parks and seasons. Other movement characteristics, including differences in home range sizes and net daily displacements, were partially reproduced. Out of the all the statistical comparisons made between the empirical and simulated movement patterns, the majority were classified as discrepancies of medium or small effect size. We have shown that a resource-driven model with relatively simple decision rules generates trajectories with movement characteristics that are mostly comparable to those calculated from empirical data. Simulating hourly movement (as our model does) may be useful in predicting how finer-scale patterns of space use, such as those created by foraging movements, are influenced by finer spatio-temporal changes in the environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109499","usgsCitation":"Diaz, S.G., DeAngelis, D.L., Gaines, M.S., Purdon, A., Mole, M.A., and van Aarde, R.J., 2021, Development and validation of a spatially-explicit agent-based model for space utilization by African savanna elephants (Loxodonta africana) based on determinants of movement: Ecological Modelling, v. 447, 109499, 27 p., https://doi.org/10.1016/j.ecolmodel.2021.109499.","productDescription":"109499, 27 p.","ipdsId":"IP-124073","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":408643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Botswana, Mozambique, South Africa","otherGeospatial":"Chobe National Park, Kruger National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 25.26908811865576,\n -17.811236528794907\n ],\n [\n 23.696375701212872,\n -17.811236528794907\n ],\n [\n 23.696375701212872,\n -19.291477668581805\n ],\n [\n 25.26908811865576,\n -19.291477668581805\n ],\n [\n 25.26908811865576,\n -17.811236528794907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 30.337765815705552,\n -22.153479707969097\n ],\n [\n 30.337765815705552,\n -25.725433227433996\n ],\n [\n 33.00624860561675,\n -25.725433227433996\n ],\n [\n 33.00624860561675,\n -22.153479707969097\n ],\n [\n 30.337765815705552,\n -22.153479707969097\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"447","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Diaz, Stephanie G.","contributorId":212228,"corporation":false,"usgs":false,"family":"Diaz","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":855617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":855618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaines, Michael S.","contributorId":298435,"corporation":false,"usgs":false,"family":"Gaines","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":855619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purdon, Andrew","contributorId":298436,"corporation":false,"usgs":false,"family":"Purdon","given":"Andrew","email":"","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":855620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mole, Michael A.","contributorId":298438,"corporation":false,"usgs":false,"family":"Mole","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":855621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Aarde, Rudi J.","contributorId":298440,"corporation":false,"usgs":false,"family":"van Aarde","given":"Rudi","email":"","middleInitial":"J.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":855622,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219424,"text":"70219424 - 2021 - UAV-based estimate of snow cover dynamics: Optimizing semi-arid forest structure for snow persistence","interactions":[],"lastModifiedDate":"2021-04-05T13:40:13.157647","indexId":"70219424","displayToPublicDate":"2021-03-09T08:18:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"UAV-based estimate of snow cover dynamics: Optimizing semi-arid forest structure for snow persistence","docAbstract":"Seasonal snow cover in the dry forests of the American West provides essential water resources to both human and natural systems. The structure of trees and their arrangement across the landscape are important drivers of snow cover distribution across these forests, varying widely in both space and time. We used unmanned aerial vehicle (UAV) multispectral imagery and Structure-from-Motion (SfM) models to quantify rapidly melting snow cover dynamics and examine the effects of forest structure shading on persistent snow cover in a recently thinned ponderosa pine forest. Using repeat UAV multispectral imagery (n = 11 dates) across the 76 ha forest, we first developed a rapid and effective method for identifying persistent snow cover with 90.2% overall accuracy. The SfM model correctly identified 98% (n = 1280) of the trees, when compared with terrestrial laser scanner validation data. Using the SfM-derived forest structure variables, we then found that canopy shading associated with the vertical and horizontal metrics was a significant driver of persistent snow cover patches (R2 = 0.70). The results indicate that UAV image-derived forest structure metrics can be used to accurately predict snow patch size and persistence. Our results provide insight into the importance of forest structure, specifically canopy shading, in the amount and distribution of persistent seasonal snow cover in a typical dry forest environment. An operational understanding of forest structure effects on snow cover will help drive forest management that can target snow cover dynamics in addition to forest health.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13051036","usgsCitation":"Belmonte, A., Sankey, T.T., Biedermann, J., Bradford, J., Goetz, S.J., and Kolb, T., 2021, UAV-based estimate of snow cover dynamics: Optimizing semi-arid forest structure for snow persistence: Remote Sensing, v. 13, no. 5, 1036, 20 p., https://doi.org/10.3390/rs13051036.","productDescription":"1036, 20 p.","ipdsId":"IP-126824","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":453149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13051036","text":"Publisher Index Page"},{"id":384871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.78863525390625,\n 34.5235300339023\n ],\n [\n -111.23382568359374,\n 34.5235300339023\n ],\n [\n -111.23382568359374,\n 35.15135442846945\n ],\n [\n -111.78863525390625,\n 35.15135442846945\n ],\n [\n -111.78863525390625,\n 34.5235300339023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Belmonte, Adam","contributorId":222546,"corporation":false,"usgs":false,"family":"Belmonte","given":"Adam","email":"","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":813495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":813496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biedermann, Joel","contributorId":256936,"corporation":false,"usgs":false,"family":"Biedermann","given":"Joel","email":"","affiliations":[{"id":51904,"text":"USDA Agricultural Research Service Southwest Watershed Research Center, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":813497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, Scott J 0000-0002-6326-4308","orcid":"https://orcid.org/0000-0002-6326-4308","contributorId":210734,"corporation":false,"usgs":false,"family":"Goetz","given":"Scott","email":"","middleInitial":"J","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":813499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolb, Thomas","contributorId":174381,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","affiliations":[],"preferred":false,"id":813500,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219558,"text":"70219558 - 2021 - Fish habitat use and food web structure following pond and plug restoration of a Montane Meadow in the Sierra Nevada, California","interactions":[],"lastModifiedDate":"2021-04-13T12:43:12.368334","indexId":"70219558","displayToPublicDate":"2021-03-09T07:34:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8119,"text":"Northwest Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Fish habitat use and food web structure following pond and plug restoration of a Montane Meadow in the Sierra Nevada, California","docAbstract":"Montane meadows are areas of high biodiversity and provide many important ecosystem services; however, degradation of 40–60% of these habitats in the Sierra Nevada region of California has left many of these areas impaired. The “pond-and-plug” meadow-restoration technique is 1 type of treatment implemented to restore montane meadows. The objectives of this technique are to re-water the meadow and promote downstream flow by increasing the water-table elevation and providing additional water storage that will promote the growth of mesic and hydric vegetation that maintains and stabilizes stream channels. However, aquatic habitat and the composition and functioning of aquatic communities in these systems post-treatment are poorly documented or understood. We evaluated: (1) fish habitat, community composition, and relative abundance among recently created ponds spanning the range of pond habitats; (2) seasonal movement and survival of fish within and among ponds; and (3) food web structure in ponds. We documented over-summer and winter survival in the fish community and short-distance movement by 1 species occupying the ponds. Mark-recapture data suggest that all fish species present are capable of surviving both summer and winter conditions when pond conditions could be most limiting. Food web structure among intensively sampled ponds was similar, with overlapping isotopic niche width for dominant taxa. However, basal resource diversity (BRD) varied among ponds, with those having higher macrophyte cover also showing greater BRD. Our findings suggest that pond-and-plug techniques can provide habitat for native fishes that are able to tolerate departures from the species thermal and dissolved oxygen optima. Future meadow treatments could benefit from short-term restoration techniques such as pond-and-plug to allow for longer-term processes to influence meadow condition over time.
We present a comprehensive critical review of well-established satellite remote sensing water indices and offer a novel, robust Augmented Normalized Difference Water Index (ANDWI). ANDWI employs an expanded set of spectral bands, RGB, NIR, and SWIR1-2, to maximize the contrast between water and non-water pixels. Further, we implement a dynamic thresholding method, the Otsu algorithm, to enhance ANDWI's performance. Applied to a variety of environmental conditions, ANDWI with Otsu-thresholding offered the highest overall accuracy (accuracy = 0.98, F1 = 0.98, and Kappa = 0.96) compared to other indices (NDWI, MNDWI, AWEI, WI). We also propose a novel cloud filtering algorithm that substantially increases the number of useable images compared to the conventional cloud-free composites (124% increased observations in the studied area) and resolves inappropriate masking of water bodies and hot sands as clouds by conventional methods. Finally, we develop a Google Earth Engine App to readily delineate 16-day surface water bodies across the globe.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105030","usgsCitation":"Rad, A.M., Kreitler, J.R., and Sadegh, M., 2021, Augmented normalized difference water index for improved monitoring of surface water: Environmental Modeling and Software, v. 140, 105030, 15 p., https://doi.org/10.1016/j.envsoft.2021.105030.","productDescription":"105030, 15 p.","ipdsId":"IP-121583","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":453156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105030","text":"Publisher Index Page"},{"id":385213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rad, Arash Modaresi","contributorId":257536,"corporation":false,"usgs":false,"family":"Rad","given":"Arash","email":"","middleInitial":"Modaresi","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":814522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadegh, Mojitaba","contributorId":257538,"corporation":false,"usgs":false,"family":"Sadegh","given":"Mojitaba","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":814523,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255557,"text":"70255557 - 2021 - Global Changes in 20-year, 50-year and 100-year River Floods","interactions":[],"lastModifiedDate":"2024-06-24T11:35:50.509067","indexId":"70255557","displayToPublicDate":"2021-03-09T06:30:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Global Changes in 20-year, 50-year and 100-year River Floods","docAbstract":"Concepts like the 100-year flood event can be misleading if they are not updated to reflect significant changes over time. Here, we model observed annual maximum daily streamflow using a nonstationary approach to provide the first global picture of changes in: (a) the magnitudes of the 20-, 50-, and 100-year floods (i.e., flows of a given exceedance probability in each year); (b) the return periods of the 20-, 50-, and 100-year floods, as assessed in 1970 (i.e., flows of a fixed magnitude); and (c) corresponding flood probabilities. Empirically, we find the 20-/50-year floods have mostly increased in temperate climate zones, but decreased in arid, tropical, polar, and cold zones. In contrast, 100-year floods have mostly decreased in arid/temperate zones and exhibit mixed trends in cold zones, but results are influenced by the small number of stations with long records, and highlight the need for continued updating of hazard assessments.
Multiple studies have reported widespread browning of Northern Hemisphere lakes. Most examples are from boreal lakes that have experienced limited human influence, and browning has alternatively been attributed to changes in atmospheric deposition, climate, and land use. To determine the extent and possible causes of browning across a more geographically diverse region, we examined watercolor and dissolved organic carbon (DOC) time series in hundreds of northeastern U.S. lakes. The majority of lakes have increased in both DOC and color, but there were neither coherent spatial patterns in trends nor relationships with previously reported drivers. Color trends were more variable than DOC trends, and DOC and color trends were not strongly correlated, indicating a cause other than or in addition to increased loading of terrestrial carbon. Browning may be pronounced in regions where climate and atmospheric deposition are dominant drivers but muted in more human-dominated landscapes with a limited extent of organic soils where other disturbances predominate.
Regional flood frequency analysis (RFFA) methods are essential tools to assess flood hazard and plan interventions for its mitigation. They are used to estimate flood quantiles when the at‐site record of streamflow data is not available or limited. One commonly used RFFA method is the index flood method (IFM), which assumes that peak floods satisfy the simple scaling hypothesis.
In this work we present an integrated approach to assess the spatial scaling behavior of floods in the United Kingdom (UK) for 540 catchments, where the IFM is currently used operationally. This assessment employs product moments, probability weighted moments, and quantile analysis, and is applied to two different types of “hydrologically homogeneous” UK regions: geographical regions as defined in the Flood Studies Report (NERC, 1975) and pooling‐groups as defined in the updated Flood Estimation Handbook (FEH; Institute of Hydrology, 1999). To understand which variables play a significant role in the flood‐peak generating mechanism, the assessment approach considers scaling not only of drainage area alone but also of other hydro‐geomorphological variables. Results provided by the different methodologies consistently showed that only part (ranging from 30% to 70%) of the peak flow variability is explained by drainage area alone; this fraction increases (up to 80%–95%) when multiple regression is used. Supported by the peak flow spatial scaling assessment, we compared the proposed approach for peak flow quantile estimation with the current FEH method in ungauged catchments. The quantile regression method based on the pooling‐group outperforms the current FEH‐ungauged method, providing a 14% relative improvement in root mean square error over the entire country.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028076","usgsCitation":"Formetta, G., Over, T.M., and Stewart, E., 2021, Assessment of peak flow scaling and Its effect on flood quantile estimation in the United Kingdom: Water Resources Research, v. 57, no. 4, e2020WR028076, 21 p., https://doi.org/10.1029/2020WR028076.","productDescription":"e2020WR028076, 21 p.","ipdsId":"IP-119682","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":453168,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://nora.nerc.ac.uk/id/eprint/529960/1/N529960PP.pdf","text":"External Repository"},{"id":384966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Kingdom","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -5.712890625,\n 49.61070993807422\n ],\n [\n -2.28515625,\n 50.064191736659104\n ],\n [\n 1.669921875,\n 50.84757295365389\n ],\n [\n 2.3291015625,\n 52.32191088594773\n ],\n [\n 0.9228515625,\n 54.826007999094955\n ],\n [\n -0.2197265625,\n 55.85064987433714\n ],\n [\n -0.791015625,\n 57.231502991478926\n ],\n [\n -1.142578125,\n 57.938183012205315\n ],\n [\n -2.548828125,\n 58.63121664342478\n ],\n [\n -4.130859375,\n 59.153403092050375\n ],\n [\n -6.767578125,\n 58.97266715450153\n ],\n [\n -8.1298828125,\n 56.24334992410525\n ],\n [\n -7.9541015625,\n 54.521081495443596\n ],\n [\n -7.0751953125,\n 54.059387886623576\n ],\n [\n -5.888671875,\n 53.409531853086435\n ],\n [\n -5.6689453125,\n 51.56341232867588\n ],\n [\n -6.1083984375,\n 50.233151832472245\n ],\n [\n -6.064453125,\n 49.55372551347579\n ],\n [\n -5.712890625,\n 49.61070993807422\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Formetta, Giuseppe 0000-0002-0252-1462","orcid":"https://orcid.org/0000-0002-0252-1462","contributorId":210296,"corporation":false,"usgs":false,"family":"Formetta","given":"Giuseppe","email":"","affiliations":[{"id":38100,"text":"Department of Civil and Environmental Engineering, Colorado School of Mines, Golden, CO","active":true,"usgs":false}],"preferred":false,"id":813730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Elizabeth","contributorId":257050,"corporation":false,"usgs":false,"family":"Stewart","given":"Elizabeth","email":"","affiliations":[{"id":51971,"text":"UK Centre for Ecology & Hydrology","active":true,"usgs":false}],"preferred":false,"id":813732,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}