Amphibian conservation has progressed from the identification of declines to mitigation, but efforts are hampered by the lack of nuanced information about the effects of environmental characteristics and stressors on mechanistic processes of population regulation. Challenges include a paucity of long-term data and scant information about the relative roles of extrinsic (e.g., weather) and intrinsic (e.g., density dependence) factors. We used a Bayesian formulation of an open population capture-recapture model and >30 years of data to examine intrinsic and extrinsic factors regulating two adult boreal chorus frogs (Pseudacris maculata) populations. We modelled population growth rate and apparent survival directly, assessed their temporal variability, and derived estimates of recruitment. Populations were relatively stable (geometric mean population growth rate >1) and regulated by negative density dependence (i.e., higher population sizes reduced population growth rate). In the smaller population, density dependence also acted on adult survival. In the larger population, higher population growth was associated with warmer autumns. Survival estimates ranged from 0.30–0.87, per-capita recruitment was <1 in most years, and mean seniority probability was >0.50, suggesting adult survival is more important to population growth than recruitment. Our analysis indicates density dependence is a primary driver of population dynamics for P. maculata adults.
","language":"English","publisher":"MDPI","doi":"10.3390/d12120478","usgsCitation":"Kissel, A.M., Tenan, S., and Muths, E.L., 2020, Density dependence and adult survival drive the dynamics in two high elevation amphibian populations: Diversity, v. 12, no. 12, 478, 15 p., https://doi.org/10.3390/d12120478.","productDescription":"478, 15 p.","ipdsId":"IP-122660","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454660,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d12120478","text":"Publisher Index Page"},{"id":436698,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9229ZLM","text":"USGS data release","linkHelpText":"Chorus frog density and population growth, Cameron Pass, Colorado, 1986-2020"},{"id":391386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lily Pond, Matthews Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.86,\n 40.6\n ],\n [\n -105.82,\n 40.6\n ],\n [\n -105.82,\n 40.56\n ],\n [\n -105.86,\n 40.56\n ],\n [\n -105.86,\n 40.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda M.","contributorId":211917,"corporation":false,"usgs":false,"family":"Kissel","given":"Amanda","email":"","middleInitial":"M.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":826397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tenan, Simone","contributorId":177519,"corporation":false,"usgs":false,"family":"Tenan","given":"Simone","email":"","affiliations":[],"preferred":false,"id":826398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826396,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228740,"text":"70228740 - 2020 - Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","interactions":[],"lastModifiedDate":"2022-02-17T15:10:38.050995","indexId":"70228740","displayToPublicDate":"2020-12-15T09:05:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Use of remote sensing tools to predict focal areas for sea turtle conservation in the Southwestern Atlantic","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Soil and water conservation: A celebration of 75 years","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Soil and Water Conservation Society","usgsCitation":"Mushet, D.M., and Aram Calhoun, 2020, Wetland conservation in the United States: A swinging pendulum, chap. 14 of Soil and water conservation: A celebration of 75 years, p. 162-171.","productDescription":"10 p.","startPage":"162","endPage":"171","ipdsId":"IP-115447","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":381440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381426,"type":{"id":15,"text":"Index Page"},"url":"https://www.swcs.org/resources/publications/soil-and-water-conservation-a-celebration-of-75-years"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":807027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aram Calhoun","contributorId":245784,"corporation":false,"usgs":false,"family":"Aram Calhoun","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":807028,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216899,"text":"ofr20201140 - 2020 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","interactions":[],"lastModifiedDate":"2020-12-15T19:44:17.549778","indexId":"ofr20201140","displayToPublicDate":"2020-12-15T08:17:17","publicationYear":"2020","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":"2020-1140","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2019","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the fourth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. The report contains information pertinent to data collection during the 2019 water year, from October 2018 to September 2019. No changes to the previously installed data collection network were made during this period.
Discharge and salinity varied widely during the data collection period, which included above-average rainfall for all counties in the study area over the 3-month period from November to January, below-average annual rainfall for all counties, and effects from Hurricane Dorian in September 2019. Total annual rainfall for all counties ranked third among the annual totals computed for the 4 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Ortega River, Julington Creek, Pottsburg Creek, Broward River, Cedar River, Clapboard Creek, and Dunn Creek. The annual mean discharge for each of the main-stem sites was lower for the 2019 water year than for the 2018 water year. Since the beginning of the study in 2016, the St. Johns River at Astor station computed its lowest annual mean discharge, the Jacksonville station recorded its second lowest, and the Buffalo Bluff station recorded its second highest in 2019.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2018 water year, annual mean salinity at all monitoring locations was higher for the 2019 water year except at the main-stem site below Shands Bridge and at the tributary sites of Durbin Creek and Julington Creek, which remained the same. The 2019 annual mean salinity at Dunn Creek was the highest on record for that site, and Clapboard Creek and Trout River were the second highest on record for those sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201140","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2020, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2019: U.S. Geological Survey Open-File Report 2020–1140, 48 p., https://doi.org/10.3133/ofr20201140.","productDescription":"ix, 48 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-118214","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":381275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1140/coverthb.jpg"},{"id":381276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1140/ofr20201140.pdf","text":"Report","size":"7.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1140"}],"country":"United States","state":"Florida","otherGeospatial":"St John's River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93878173828125,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 29.1161749329972\n ],\n [\n -81.4691162109375,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 30.545704405480997\n ],\n [\n -81.93878173828125,\n 29.1161749329972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Biological conservation is a fundamental purpose of the National Park system, and Catoctin Mountain Park (CATO) supports high-quality habitat for native fishes in the headwaters of the Chesapeake Bay watershed in eastern North America. However, native Blue Ridge sculpin (Cottus caeruleomentum) have been extirpated in Big Hunting Creek above Cunningham Falls in CATO. Prior research indicates that infection by the fungal-like protist Dermocystidium is a likely cause for the extirpation, but elevated stream temperatures also have been observed in the study area, and it remains unknown whether thermal stress may exacerbate infections or otherwise limit habitat suitability for fishes in CATO.
The purpose of this study was to quantify spatial variation in summer stream temperatures and to evaluate the effects of temperature on sculpin growth rates and susceptibility to Dermocystidium infection. We used observational and experimental methods to address these objectives. First, we deployed stream temperature gages at 10 sites throughout the study area to assess hourly and daily temperatures during the summer of 2019. Second, we conducted an in situ fish enclosure experiment at five of the temperature sites to assess fish growth and susceptibility to Dermocystidium infection over a 45-day exposure period. For this experiment we collected sculpin from a stream in CATO that supports a robust population of Blue Ridge sculpin (Owens Creek) and held them in quarantine for 50 days in the Experimental Stream Laboratory at the U.S. Geological Survey (USGS) Leetown Science Center. Pre-exposure histopathology confirmed the absence of Dermocystidium infection prior to the introduction of fish into experimental enclosures.
We found that stream temperatures were warmer where sculpin have been extirpated than elsewhere in CATO where sculpin persist. However, the fish enclosure experiment revealed a positive effect of temperature on fish growth, suggesting that increased food availability and foraging rates compensated for increased metabolic demands in the warmest sites. Moreover, fish held in enclosures did not develop Dermocystidium infection. Our results therefore suggest that current environmental conditions in upper Big Hunting Creek may be suitable for Blue Ridge sculpin reintroduction, and this could ultimately lead to sportfishing opportunities by increasing the forage base for native brook trout (Salvelinus fontinalis).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201137","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Hitt, N.P., Kessler, K.G., Kelly, Z.A., Rogers, K.M., Macmillan, H.E., and Walsh, H.L., 2020, Assessing native fish restoration potential in Catoctin Mountain Park: U.S. Geological Survey Open-File Report 2020–1137, 17 p., https://doi.org/10.3133/ofr20201137.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122955","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381222,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P950A13P","text":"USGS data release","linkHelpText":"Stream temperature and sculpin growth data collected from Catoctin Mountain Park in 2019"},{"id":381221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1137/ofr20201137.pdf","text":"Report","size":"4.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1137"},{"id":381220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1137/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Catoctin Mountain Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51781463623047,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.60621720230201\n ],\n [\n -77.38151550292969,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.70137566512028\n ],\n [\n -77.51781463623047,\n 39.60621720230201\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
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Monitoring demographic response over time is valuable for understanding population dynamics of endangered species. We quantified the variation in survival patterns for three small isolated island populations of endangered waterfowl in the Hawaiian Archipelago. Laysan Teal Anas laysanensis were individually marked and the fate of 1,150 individuals were followed from different cohorts among the two reintroduced (Kure and Midway Atolls) and the single relict (Laysan Island) populations for time series of 4, 10 and 15 years respectively. We applied a non-parametric Kaplan-Meier estimator to describe variation between the populations in survival for different cohorts. For Laysan Island and Midway Atoll, we used log-rank tests to determine the effects of cohort, island and sex on survival. Birds in the Laysan Island population had significantly higher survival than those in the Midway population, and males had higher survival than females in both populations. The proportion of females surviving at Midway Atoll was 40% lower than for females on Laysan Island at year 5. The oldest bird observed from Laysan Island was at least 15.5 years old and had been ringed as an adult. The Kure Atoll founder cohort (n = 28) had 100% survival 18 months post-release, but this dropped by 39% during the first avian botulism type C outbreak. Ten of twenty-eight founders and a population of 60–70 birds persisted on Kure Atoll in 2020. We summarised mortality records to generate hypotheses to explain the cause-specific mechanisms driving the observed survival differences. Mortality data showed that the survival differences between islands in Laysan Teal survival was driven by chronic epizootics of avian botulism type C at Midway and Kure Atoll.
Previous work has proposed transfer of kinetic heat energy from low-energy broad ion beam (BIB) milling causes thermal alteration of sedimentary organic matter, resulting in increases of organic matter reflectance. Whereas, other studies have suggested the organic matter reflectance increase from BIB milling is due to decreased surface roughness. To test if reflectance increases to sedimentary organic matter (vitrinite) caused by BIB milling were related to molecular aromatization and condensation, Raman and Fourier transform infrared (FTIR) spectroscopies were used to evaluate potential compositional changes in the same vitrinite locations pre- and post-BIB milling. The same locations also were examined by atomic force microscopy (AFM) to determine topographic changes caused by BIB milling (as quantified by the areal root-mean-square roughness parameter Sq). Samples consisted of four medium volatile bituminous coals. A non-aggressive BIB milling approach was used with conditions of 5 min, 4 keV, 15°incline, 360° rotation at 25 rpm and 100% focus (1.5 kV discharge; ∼100 μA). This gentle BIB milling caused vitrinite reflectance (VRo) increases of 12 to 36% of the original values determined optically before milling (average 26% increase). When molecular proxies from FTIR (A- and C-factor, branching ratio) were plotted against each other for the same vitrinite locations pre- and post-milling, mean data points for each sample generally lie within error of a 1:1 line. Likewise, mean Raman thermal proxy [full-width half maximum of G-band (G-FWHM), Raman band separation (RBS) and D1/G band intensity ratio] values were similar for pre- and post-milled locations, also plotting within error of a 1:1 line. AFM confirms the majority (24 of 36) of pre- and post-ion milled surface pairs were smoother (lower Sq values) after BIB milling. These results are interpreted to indicate VRo increase induced by the gentle BIB milling conditions used in this study is an effect of decreased diffuse reflectance due to flatter surfaces, causing more photons to reflect directly back to the detector. Little evidence was observed for molecular aromatization and condensation of vitrinite molecules following BIB milling (with the conditions used). The presence of milling-induced artifacts, including differential milling effects dependent on location and the development of self-organized patterned structures, indicate much work remains in standardization of BIB milling before its promulgation as a routine sample preparation technique for organic petrography. These results provide better understanding of anthropogenic-induced changes to geological samples caused by the now widespread adoption of BIB milling as a disruptive innovation in sample preparation.
Predictions of river channel adjustment to changes in streamflow regime based on relations between mean channel characteristics and mean flood magnitude can be useful to evaluate average channel response. However, because these relations assume equilibrium sediment transport, their applicability to cases where streamflow and sediment transport are decoupled may be limited. These general relations also lack the specificity that is required to connect specific characteristics of the streamflow and sediment regime with the dynamics of channel morphological change that create channel complexity, which is often of ecological interest. We integrate historical records of channel change, observations of scour and fill during a snowmelt flood, measurements of sediment transport, and predictions from a two-dimensional streamflow model to describe how annual peak flow magnitude and peak-flow duration interact with the upstream sediment supply to control channel form for a 15-km study reach on the regulated Green River in Canyonlands National Park, Utah. Two major decadal-scale episodes of channel narrowing have occurred within the study area. For each of these episodes, the reduction in average channel width was consistent with the change predicted by hydraulic geometry relations as a function of average flood magnitude. However, channel narrowing occurred during periods of exceptionally low annual floods. The most recent episode of channel narrowing occurred between 1988 and 2009, during low-flow cycles when the 5-yr mean peak flow was less than 60% of the long-term (1959–2016) mean peak flow. These findings, together with findings from previous studies, demonstrate that decreases in peak-flow magnitude caused by streamflow regulation, climate change, or a combination of those factors have driven episodes of channel narrowing on the Green River. Observations of streamflow, sediment-transport, and morphologic change coupled with predictions from a two-dimensional streamflow model indicate that peak flow magnitudes of at least 75% of the long-term mean peak flow are required to transport bed-material sand in suspension in all regions of the multi-thread channel and that the ~2-month duration of the snowmelt flood played an important role in creating conditions necessary to maintain channel conveyance. These results indicate that detailed characterizations of channel response such as these are needed to predict how river channels will respond to changes in streamflow regime that affect annual peak flow magnitude and duration.
In 1869, John Wesley Powell completed the first well-recorded scientific river journey to explore an extensive region of the Colorado River Basin. Powell later helped to establish the U.S. Geological Survey (USGS) and served as its second director (1881–94), cementing his position in the folklore of the Survey. In 2019, the USGS marked the 150th anniversary of Powell’s first expedition with a broad-scale educational campaign as an opportunity to highlight current USGS science in the region through the lens of an exciting river expedition, with the goal of inspiring the next generation of USGS scientists. The project included a partnership with the Sesquicentennial Colorado River Exploring Expedition (SCREE), which traveled the length of the original route for ~1,000 river miles from Green River, Wyoming, to Lake Mead, Nevada, including the Grand Canyon. Small, interdisciplinary groups of USGS employees joined each segment of the journey, gathered data to be used for educational purposes, participated in community outreach events, and upon return shared their experiences with their local communities. This report documents a photographic journey of the expedition, personal vignettes from the USGS participants, Science Stories to explain the scope of the experiments, and Then and Now articles (which were published online during the expedition), to explore some of the changes that have occurred since the first expedition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1475","usgsCitation":"Scott, A., and Snow, E., 2020, The 150th anniversary of the 1869 Powell expedition—USGS participation in the Sesquicentennial Colorado River Exploring Expedition and reflections from the ~1,000-mile journey down the Green and Colorado Rivers (ver. 1.1, December 14, 2020): U.S. Geological Survey Circular 1475, 88 p., https://doi.org/10.3133/cir1475.","productDescription":"Report: vii, 88 p.; Version History","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-119749","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":381274,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1475/versionHist.txt","size":"1.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":381014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1475/cir1475.pdf","text":"Report","size":"24.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1475"},{"id":380830,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1475/coverthb3.jpg"}],"country":"United States","state":"Arizona, Colorado, Utah, Wyoming","otherGeospatial":"Colorado River, Grand Canyon, Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.4073486328125,\n 41.6154423246811\n ],\n [\n -109.7479248046875,\n 41.32732632036622\n ],\n [\n -109.7039794921875,\n 40.88444793903562\n ],\n [\n -109.2095947265625,\n 40.84706035607122\n ],\n [\n -109.017333984375,\n 40.751418432997454\n ],\n [\n -109.09423828125,\n 40.55972134684838\n ],\n [\n -109.4677734375,\n 40.455307212131494\n ],\n [\n -109.8358154296875,\n 40.052847601823984\n ],\n [\n -110.1324462890625,\n 39.57182223734374\n ],\n [\n -110.2423095703125,\n 38.93377552819722\n ],\n [\n -110.093994140625,\n 38.49229419236133\n ],\n [\n -109.984130859375,\n 38.199338565983844\n ],\n [\n -110.1708984375,\n 38.03078569382294\n ],\n [\n -110.5828857421875,\n 37.79676317682161\n ],\n [\n -110.75866699218749,\n 37.57505900514996\n ],\n [\n -110.94543457031249,\n 37.38761749978395\n ],\n [\n -111.03881835937499,\n 37.204081555898526\n ],\n [\n -111.3848876953125,\n 37.18220222107978\n ],\n [\n -111.6375732421875,\n 37.077093191754436\n ],\n [\n -112.049560546875,\n 36.22211876039103\n ],\n [\n -112.4945068359375,\n 36.4566360115962\n ],\n [\n -113.302001953125,\n 36.25756282630298\n ],\n [\n -113.4613037109375,\n 36.01800375871416\n ],\n [\n -113.477783203125,\n 35.82672127366604\n ],\n [\n -113.97766113281249,\n 36.23984280222428\n ],\n [\n -114.0216064453125,\n 36.115690180653395\n ],\n [\n -113.917236328125,\n 35.875698032496665\n ],\n [\n -113.345947265625,\n 35.65729624809628\n ],\n [\n -113.203125,\n 36.02688935430189\n ],\n [\n -112.510986328125,\n 36.3106987841827\n ],\n [\n -112.0770263671875,\n 35.9157474194997\n ],\n [\n -111.741943359375,\n 36.06686213257888\n ],\n [\n -111.72546386718749,\n 36.48755716938576\n ],\n [\n -111.3629150390625,\n 36.932330061503144\n ],\n [\n -110.7861328125,\n 37.08585785263673\n ],\n [\n -110.40710449218749,\n 37.54893261064111\n ],\n [\n -109.8028564453125,\n 38.16047628099622\n ],\n [\n -109.0887451171875,\n 38.94232097947902\n ],\n [\n -109.22607421875,\n 39.0831721934762\n ],\n [\n -109.9346923828125,\n 38.47509432050245\n ],\n [\n -109.984130859375,\n 39.06184913429154\n ],\n [\n -109.599609375,\n 40.04864272291728\n ],\n [\n -108.8525390625,\n 40.40513069752789\n ],\n [\n -108.69873046875,\n 40.78885994449482\n ],\n [\n -109.0008544921875,\n 40.97160353279909\n ],\n [\n -109.3963623046875,\n 41.04621681452063\n ],\n [\n -109.3359375,\n 41.41801503608024\n ],\n [\n -109.2974853515625,\n 41.611335399441735\n ],\n [\n -109.4073486328125,\n 41.6154423246811\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 3, 2020; Version 1.1: December 14, 2020","contact":"https://www.usgs.gov
https://www.usgs.gov/powell150
The U.S. Geological Survey (USGS) Precipitation Chemistry Quality Assurance project (PCQA) operated five distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program’s (NADP) National Trends Network and Mercury Deposition Network during 2017–18. The National Trends Network programs included (1) a field audit program to evaluate sample contamination and stability, (2) an interlaboratory comparison program to evaluate analytical laboratory performance, and (3) a colocated sampler program to evaluate variability attributed to automated precipitation samplers. The Mercury Deposition Network programs include the (4) system blank program and (5) an interlaboratory comparison program. The results indicate consistently low levels of sample contamination, generally strong analytical laboratory performance, and low overall variability in concentration data imparted by field equipment. The NADP operations moved from its 40-year home at the Illinois State Water Survey to the Wisconsin State Laboratory of Hygiene in June 2018. The PCQA programs were modified and (or) temporarily curtailed during the transition in 2018. Bias and variability of sample analysis results were evaluated for the two Central Analytical Laboratories, and ongoing monitoring will be helpful to differentiate true environmental signals from the effects of changing laboratory conditions and performance. Results of quality assurance sample analyses are provided to document that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends for chemical constituents in wet deposition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205084","usgsCitation":"Wetherbee, G.A., and Martin, R., 2020, External quality assurance project report for the National Atmospheric Deposition Program’s National Trends Network and Mercury Deposition Network, 2017–18: U.S. Geological Survey Scientific Investigations Report 2020–5084, 31 p., https://doi.org/10.3133/sir20205084.","productDescription":"Report: vii, 31 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-110354","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":381227,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94RC4GD","text":"USGS data release","linkHelpText":"Data for the U.S. Geological Survey Precipitation Chemistry Quality Assurance Project for the National Atmospheric Deposition Program, 1978–2017"},{"id":381224,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5084/coverthb.jpg"},{"id":381225,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5084/sir20205084.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5084"},{"id":381226,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZKXD8N","text":"USGS data release","linkHelpText":"U.S. Geological Survey Precipitation Chemistry Quality Assurance Project Data 2017 – 2018"}],"contact":"Director, Observing Systems Division
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Buildings 2101, 2204 HIF
Hydrologic Instrumentation Facility
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The Alaska Volcano Observatory responded to eruptions, significant and minor volcanic unrest, and seismic events at 16 volcanic centers in Alaska during 2017. The most notable volcanic activity consisted of a major eruption at Bogoslof Island, continuing intermittent dome growth and ash eruptions from Mount Cleveland, the end of the Pavlof Volcano eruption, volcanic unrest at Shishaldin Volcano, and significant earthquake activity at Tanaga and Great Sitkin Islands. This report also documents reports of degassing at Redoubt Volcano, Makushin Volcano, Mount Gareloi, and Kiska Volcano, anomalous seismicity at Mount Spurr, Augustine Volcano, Akutan Peak, and Makushin Volcano, landslides at Iliamna Volcano, resuspended ash from the 1912 Novarupta-Katmai eruption, and continuing inflation at Okmok Caldera.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205102","collaboration":"Prepared in cooperation with the Alaska Volcano Observatory, a cooperative program of the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Dixon, J.P., Cameron, C.E., Iezzi, A.M., Power, J.A., Wallace, K., and Waythomas, C.F., 2020, 2017 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2020–5102, 61 p., https://doi.org/10.3133/sir20205102.","productDescription":"vii, 61 p.","numberOfPages":"61","onlineOnly":"Y","ipdsId":"IP-109226","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5102/sir20205102.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5102/covrthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -139.130859375,\n 60.50052541051131\n ],\n [\n -140.80078125,\n 60.326947742998414\n ],\n [\n -140.888671875,\n 69.62651016802958\n ],\n [\n -143.7890625,\n 70.19999407534661\n ],\n [\n -152.490234375,\n 70.95969716686398\n ],\n [\n -156.26953125,\n 71.44117085172385\n ],\n [\n -158.37890625,\n 71.21607526596131\n ],\n [\n -161.982421875,\n 70.31873847853124\n ],\n [\n -167.080078125,\n 68.6885206018014\n ],\n [\n -167.783203125,\n 65.54936668811527\n ],\n [\n -165.9375,\n 61.18562468142281\n ],\n [\n -167.6953125,\n 60.19615576604439\n ],\n [\n -166.376953125,\n 59.17592824927136\n ],\n [\n -159.345703125,\n 57.98480801923985\n ],\n [\n -158.466796875,\n 57.657157596582984\n ],\n [\n -164.267578125,\n 55.429013452407396\n ],\n [\n -167.6953125,\n 54.213861000644926\n ],\n [\n -169.45312499999997,\n 52.696361078274485\n ],\n [\n -166.2890625,\n 53.225768435790194\n ],\n [\n -159.78515624999997,\n 55.62799595426723\n ],\n [\n -156.26953125,\n 56.897003921272606\n ],\n [\n -155.302734375,\n 56.84897198026975\n ],\n [\n -154.68749999999997,\n 55.97379820507658\n ],\n [\n -152.578125,\n 57.088515327886505\n ],\n [\n -151.962890625,\n 57.89149735271034\n ],\n [\n -150.99609375,\n 59.0405546167585\n ],\n [\n -148.18359375,\n 60.1524422143808\n ],\n [\n -144.404296875,\n 60.06484046010452\n ],\n [\n -138.69140625,\n 58.309488840677645\n ],\n [\n -134.38476562499997,\n 54.87660665410869\n ],\n [\n -131.044921875,\n 51.72702815704774\n ],\n [\n -131.220703125,\n 53.38332836757156\n ],\n [\n -130.60546875,\n 55.02802211299252\n ],\n [\n -130.341796875,\n 56.022948079627454\n ],\n [\n -132.451171875,\n 57.42129439209407\n ],\n [\n -134.912109375,\n 59.355596110016315\n ],\n [\n -135.35156249999997,\n 59.88893689676585\n ],\n [\n -136.31835937499997,\n 59.130863097255904\n ],\n [\n -139.130859375,\n 60.50052541051131\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
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The Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, and seismic events at 15 volcanic centers in Alaska during 2016. The most notable volcanic activity consisted of eruptions at Pavlof and Bogoslof volcanoes. Both eruptions produced significant ash clouds that affected regional air travel. Mount Cleveland continued a pattern of dome growth followed by explosion, producing very short-lived ash clouds. An eruptive period at Shishaldin Volcano ended in 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205125","collaboration":"Prepared in cooperation with the Alaska Volcano Observatory, a cooperative program of the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Cameron, C.E., Dixon, J.P., Waythomas, C.F., Iezzi, A.M., Wallace, K.L., McGimsey, R.G., and Bull, K.F., 2020, 2016 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2020–5125, 63 p., https://doi.org/10.3133/sir20205125.","productDescription":"vii, 63 p.","numberOfPages":"63","onlineOnly":"Y","ipdsId":"IP-113325","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":381256,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5125/coverthb.jpg"},{"id":381257,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5125/sir20205125.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -139.130859375,\n 60.50052541051131\n ],\n [\n -140.80078125,\n 60.326947742998414\n ],\n [\n -140.888671875,\n 69.62651016802958\n ],\n [\n -143.7890625,\n 70.19999407534661\n ],\n [\n -152.490234375,\n 70.95969716686398\n ],\n [\n -156.26953125,\n 71.44117085172385\n ],\n [\n -158.37890625,\n 71.21607526596131\n ],\n [\n -161.982421875,\n 70.31873847853124\n ],\n [\n -167.080078125,\n 68.6885206018014\n ],\n [\n -167.783203125,\n 65.54936668811527\n ],\n [\n -165.9375,\n 61.18562468142281\n ],\n [\n -167.6953125,\n 60.19615576604439\n ],\n [\n -166.376953125,\n 59.17592824927136\n ],\n [\n -159.345703125,\n 57.98480801923985\n ],\n [\n -158.466796875,\n 57.657157596582984\n ],\n [\n -164.267578125,\n 55.429013452407396\n ],\n [\n -167.6953125,\n 54.213861000644926\n ],\n [\n -169.45312499999997,\n 52.696361078274485\n ],\n [\n -166.2890625,\n 53.225768435790194\n ],\n [\n -159.78515624999997,\n 55.62799595426723\n ],\n [\n -156.26953125,\n 56.897003921272606\n ],\n [\n -155.302734375,\n 56.84897198026975\n ],\n [\n -154.68749999999997,\n 55.97379820507658\n ],\n [\n -152.578125,\n 57.088515327886505\n ],\n [\n -151.962890625,\n 57.89149735271034\n ],\n [\n -150.99609375,\n 59.0405546167585\n ],\n [\n -148.18359375,\n 60.1524422143808\n ],\n [\n -144.404296875,\n 60.06484046010452\n ],\n [\n -138.69140625,\n 58.309488840677645\n ],\n [\n -134.38476562499997,\n 54.87660665410869\n ],\n [\n -131.044921875,\n 51.72702815704774\n ],\n [\n -131.220703125,\n 53.38332836757156\n ],\n [\n -130.60546875,\n 55.02802211299252\n ],\n [\n -130.341796875,\n 56.022948079627454\n ],\n [\n -132.451171875,\n 57.42129439209407\n ],\n [\n -134.912109375,\n 59.355596110016315\n ],\n [\n -135.35156249999997,\n 59.88893689676585\n ],\n [\n -136.31835937499997,\n 59.130863097255904\n ],\n [\n -139.130859375,\n 60.50052541051131\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
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Resources for addressing stream fish conservation issues are often limited and the stressors impacting fish continue to increase, so decision makers often rely on tools to prioritize locations for conservation actions. Because conservation networks already exist in many areas, incorporating these into the planning process can increase the ability of decision makers to carry out management actions. In this study we aim to identify priority areas within established networks to provide an approach which allows managers to focus efforts on the most valuable areas they control, while identifying areas outside of the network, which support species with minimal representation within the network, for acquisition or conservation partnerships. The goal of this approach is to prioritize sites to achieve high levels of species representation while also developing workable solutions. We applied a methodology incorporating established networks into a systematic conservation planning process for fish in temperate wadeable streams located in Missouri, USA. We compared how well species were represented in our approach with two commonly used alternatives: A blank slate approach which used the same systematic conservation planning technique but did not incorporate established networks, and a habitat integrity approach based solely on anthropogenic threat data. Relative to the blank slate approach, our approach required 210% more segments for representation of all species, and contained an average of 0.5 additional occurrences for the least well-represented species. Although the blank slate solution was more efficient in achieving species representation, 77% of segments in this solution were not already protected. This would likely pose a challenge for implementing conservation actions. Relative to habitat integrity-based priorities, our approach required only 38% of the number of stream segments to achieve representation of all species and contained an average of 5 additional occurrences of the least represented species, representing a substantial gain in representation. Incorporating established networks may allow managers to focus resources on areas with the greatest conservation value within established networks and to identify the most valuable areas complementary to the established networks, resulting in priorities which may be more actionable and effective than those developed by alternative approaches.
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B.","contributorId":272501,"corporation":false,"usgs":false,"family":"Whittier","given":"J.","email":"","middleInitial":"B.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":831995,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227125,"text":"70227125 - 2020 - Forest management and bats","interactions":[],"lastModifiedDate":"2022-01-03T15:48:10.840428","indexId":"70227125","displayToPublicDate":"2020-12-13T11:10:08","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Forest management and bats","docAbstract":"Because more than half of the forest land in the United States is privately owned, forest landowners play an important role in the stewardship of our wildlife resources. This publication will introduce you to a group of wildlife that is particularly important to forest ecosystems, but also one of the most misunderstood: bats. We will demonstrate how active forest management can improve forest health and productivity while maintaining and enhancing habitat for these fascinating and beneficial mammals.
","language":"English","publisher":"U.S. Department of Agriculture, Forest Service","usgsCitation":"Taylor, D.A., Perry, R.W., Miller, D.A., and Ford, W., 2020, Forest management and bats, 23 p.","productDescription":"23 p.","numberOfPages":"26","ipdsId":"IP-117926","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":393656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":393640,"type":{"id":15,"text":"Index Page"},"url":"https://www.srs.fs.usda.gov/pubs/61910"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Daniel A. R.","contributorId":270678,"corporation":false,"usgs":false,"family":"Taylor","given":"Daniel","email":"","middleInitial":"A. R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":829734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Roger W.","contributorId":201436,"corporation":false,"usgs":false,"family":"Perry","given":"Roger","email":"","middleInitial":"W.","affiliations":[{"id":25513,"text":"USDA Forest Service Southern Research Station","active":true,"usgs":false}],"preferred":false,"id":829735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Darren A.","contributorId":203650,"corporation":false,"usgs":false,"family":"Miller","given":"Darren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":829736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":829733,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262421,"text":"70262421 - 2020 - The ghosts of propagation past: Haplotype information clarifies the relative influence of stocking history and phylogeographic processes on contemporary population structure of walleye (Sander vitreus)","interactions":[],"lastModifiedDate":"2025-01-23T14:32:14.022314","indexId":"70262421","displayToPublicDate":"2020-12-13T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The ghosts of propagation past: Haplotype information clarifies the relative influence of stocking history and phylogeographic processes on contemporary population structure of walleye (Sander vitreus)","title":"The ghosts of propagation past: Haplotype information clarifies the relative influence of stocking history and phylogeographic processes on contemporary population structure of walleye (Sander vitreus)","docAbstract":"Stocking of fish is an important tool for maintaining fisheries but can also significantly alter population genetic structure and erode the portfolio of within-species diversity that is important for promoting resilience and adaptability. Walleye (Sander vitreus) are a highly valued sportfish in the midwestern United States, a region characterized by postglacial recolonization from multiple lineages and an extensive history of stocking. We leveraged genomic data and recently developed analytical approaches to explore the population structure of walleye from two midwestern states, Minnesota and Wisconsin. We genotyped 954 walleye from 23 populations at ~20,000 loci using genotyping by sequencing and tested for patterns of population structure with single-SNP and microhaplotype data. Populations from Minnesota and Wisconsin were highly differentiated from each other, with additional substructure found in each state. Population structure did not consistently adhere to drainage boundaries, as cases of high intra-drainage and low inter-drainage differentiation were observed. Low genetic structure was observed between populations from the upper Wisconsin and upper Chippewa river watersheds, which are found as few as 50 km apart and were likely homogenized through historical stocking. Nevertheless, we were able to differentiate these populations using microhaplotype-based co-ancestry analysis, providing increased resolution over previous microsatellite studies and our other single SNP-based analyses. Although our results illustrate that walleye population structure has been influenced by past stocking practices, native ancestry still exists in most populations and walleye populations may be able to purge non-native alleles and haplotypes in the absence of stocking. Our study is one of the first to use genomic tools to investigate the influence of stocking on population structure in a nonsalmonid fish and outlines a workflow leveraging recently developed analytical methods to improve resolution of complex population structure that will be highly applicable in many species and systems.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13186","usgsCitation":"Bootsma, M., Miller, L., Sass, G., Euclide, P., and Larson, W., 2020, The ghosts of propagation past: Haplotype information clarifies the relative influence of stocking history and phylogeographic processes on contemporary population structure of walleye (Sander vitreus): Evolutionary Applications, v. 14, no. 4, p. 1124-1144, https://doi.org/10.1111/eva.13186.","productDescription":"21 p.","startPage":"1124","endPage":"1144","ipdsId":"IP-119896","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481105,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13186","text":"Publisher Index Page"},{"id":480943,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, 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\"}}]}","volume":"14","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Bootsma, Matthew L.","contributorId":349232,"corporation":false,"usgs":false,"family":"Bootsma","given":"Matthew L.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Loren","contributorId":349233,"corporation":false,"usgs":false,"family":"Miller","given":"Loren","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":924158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sass, Greg G.","contributorId":349235,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":924160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euclide, Peter T.","contributorId":349234,"corporation":false,"usgs":false,"family":"Euclide","given":"Peter T.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924159,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Wesley 0000-0003-4473-3401 wlarson@usgs.gov","orcid":"https://orcid.org/0000-0003-4473-3401","contributorId":199509,"corporation":false,"usgs":true,"family":"Larson","given":"Wesley","email":"wlarson@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924156,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216881,"text":"cir1472 - 2020 - Research priorities for migratory birds under climate change—A qualitative value of information assessment","interactions":[],"lastModifiedDate":"2024-03-04T19:15:34.789216","indexId":"cir1472","displayToPublicDate":"2020-12-11T14:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1472","displayTitle":"Research Priorities for Migratory Birds Under Climate Change—A Qualitative Value of Information Assessment","title":"Research priorities for migratory birds under climate change—A qualitative value of information assessment","docAbstract":"The mission of the U.S. Geological Survey National Climate Adaptation Science Center is to provide actionable, management-relevant research on climate change effects on ecosystems and wildlife to U.S. Department of the Interior bureaus. Providing this kind of useful scientific information requires understanding how natural-resource managers make decisions and identifying research priorities that support those decision-making processes. Migratory bird management and conservation of migratory bird habitat are central components of the U.S. Department of the Interior’s mission. In particular, the U.S. Fish and Wildlife Service has an intensive, complex decision-making process for identifying high-priority parcels of land that will contribute to migratory bird conservation through permanent acquisition or easement. Climate change introduces several uncertainties into this decision-making process, and additional climate change research should help to support more informed decision making regarding habitat acquisition.
Not all climate change related uncertainties, however, will have a meaningful effect on acquisition decisions; therefore, understanding which uncertainties have the most potential to alter decision making is crucial. This document summarizes a multiyear effort to clarify the major sources of climate change uncertainty that affect migratory bird management and to articulate related research priorities. We worked with U.S. Fish and Wildlife Service staff to assess the primary ways in which climate change is likely to affect migratory birds and their habitats; to clarify uncertainties surrounding these effects; and to assess how uncertainties may affect habitat acquisition decisions. Using a modified structured decision-making approach, we assessed a set of hypotheses about how climate change will affect migratory birds and their habitats. Then, we used a qualitative value of information assessment to rank the most important topics for future research. The ranking process was built on an assessment of three primary characteristics: the magnitude of uncertainty, the topic’s relevance to habitat acquisition decision making, and the feasibility of reducing the uncertainty. Based on the results of this process, high-priority topics for future research include the following:
In addition to describing high-priority research needs, this document provides a summary of the methodology used to identify, assess, and rank uncertainties. This method was developed for a climate change related topic where a full quantitative value of information approach may not be feasible. The results and methodology described here may be useful for U.S. Geological Survey and other science-funding agencies interested in improving the applicability of their research to natural-resource management decision making.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1472","usgsCitation":"Rubenstein, M.A., Rushing, C.S., Lyons, J.E., and Runge, M.C., 2020, Research priorities for migratory birds under climate change—A qualitative value of information assessment: U.S. Geological Survey Circular 1472, 18 p., https://doi.org/10.3133/cir1472.","productDescription":"vi, 18 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118784","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":381217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1472/coverthb.jpg"},{"id":381218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1472/cir1472.pdf","text":"Report","size":"1.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1472"}],"contact":"National Climate Adaptation Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 516
Reston, VA 20192
Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
A new sequence stratigraphic framework for Turonian to Santonian (94-84 Ma) sediments is established using data from the USGS Kure Beach and Elizabethtown cores collected from the Atlantic Coastal Plain of North Carolina (NC). These sediments represent some of the oldest marine units deposited on the southeastern Atlantic Coastal Plain and record the early development of a clastic wedge atop crystalline basement. Sediments were deposited as transitional marginal-marine to marine units in a complex interplay of fluvial, estuarine, and shelf environments. Repetitive lithologies and minimal biostratigraphic control requires an integrated analysis of grain-size data, geophysical logs, biostratigraphy, and 87Sr/86Sr isotopic data to identify systems tracts and establish a sequence stratigraphic framework. From this integrated approach, three Turonian to Santonian sequences in the Elizabethtown core and six in the Kure Beach core are identified. The new sequences from oldest to youngest are Clubhouse II, Fort Fisher I, Fort Fisher II, Collins Creek I, Collins Creek II, Pleasant Creek I, and Pleasant Creek II. Sequences from North Carolina document significant shifts of global and regional sea-level during greenhouse conditions in the early Late Cretaceous. Maximum sea-level rise occurred globally during the early Turonian and is documented from the marine sediments of the Clubhouse II sequence. This sequence is unconformably overlain by terrestrial sediments deposited during a major fall in sea level and maximum progradation of the shoreline, as evidenced by the Fort Fisher I sequence. Global sea-level rise in the Coniacian resulted in the deposition of the Fort Fisher II sequence, which is present only in the Kure Beach core. Local marine circulation and erosion on the shelf is suggested by the absence of the Collins Creek I sequence at Kure Beach; this sequence is present only in the up-dip Elizabethtown core. Activation of a possible buried fault structure along the Cape Fear arch resulted in the formation of a regional depocenter during the late Coniacian to early Santonian and is reflected in the unusual thickness of the Collins Creek II and Pleasant Creek I sequences. The return to a more global sea-level influence occurred in the late Santonian with the deposition of the Pleasant Creek II sequence. A comparison of temporal distribution of sequences in the Elizabethtown and Kure Beach cores to corresponding sequences in New Jersey indicates significant differences in erosional and tectonic processes in the Cape Fear region during the Turonian and Santonian.
","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.17.4.293-314","usgsCitation":"Aleman Gonzalez, W., Self-Trail, J., Harris, W., Moore, J.P., and Farrell, K., 2020, Depositional sequence stratigraphy of Turonian to Santonian sediments, Cape Fear arch, North Carolina Coastal Plain, USA: Stratigraphy, v. 17, no. 4, p. 293-314, https://doi.org/10.29041/strat.17.4.293-314.","productDescription":"22 p.","startPage":"293","endPage":"314","ipdsId":"IP-117982","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":382554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.8111572265625,\n 36.52288052805137\n ],\n [\n -77.069091796875,\n 36.527294814546245\n ],\n [\n -78.8104248046875,\n 34.10725639663118\n ],\n [\n -78.5302734375,\n 33.8339199536547\n ],\n [\n -77.969970703125,\n 33.925129700072\n ],\n [\n -77.135009765625,\n 34.619647359797185\n ],\n [\n -76.475830078125,\n 34.710009159224946\n ],\n [\n -75.4705810546875,\n 35.26804693351555\n ],\n [\n -75.4156494140625,\n 35.7286770448517\n ],\n [\n -75.8111572265625,\n 36.52288052805137\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Aleman Gonzalez, Wilma 0000-0003-3156-0126","orcid":"https://orcid.org/0000-0003-3156-0126","contributorId":223454,"corporation":false,"usgs":true,"family":"Aleman Gonzalez","given":"Wilma","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":806906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":806907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harris, W. Burleigh","contributorId":192889,"corporation":false,"usgs":false,"family":"Harris","given":"W. Burleigh","affiliations":[],"preferred":false,"id":806908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Jessica P.","contributorId":245725,"corporation":false,"usgs":false,"family":"Moore","given":"Jessica","email":"","middleInitial":"P.","affiliations":[{"id":49298,"text":"WVGS","active":true,"usgs":false}],"preferred":false,"id":806909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Farrell, Kathleen","contributorId":245726,"corporation":false,"usgs":false,"family":"Farrell","given":"Kathleen","affiliations":[{"id":40717,"text":"NCGS","active":true,"usgs":false}],"preferred":false,"id":806910,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215678,"text":"fs20203045 - 2020 - Assessment of undiscovered oil and gas resources in the Upper Cretaceous Austin Chalk and Tokio and Eutaw Formations, U.S. Gulf Coast, 2019","interactions":[],"lastModifiedDate":"2020-12-11T20:34:51.971986","indexId":"fs20203045","displayToPublicDate":"2020-12-11T10:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3045","displayTitle":"Assessment of Undiscovered Oil and Gas Resources in the Upper Cretaceous Austin Chalk and Tokio and Eutaw Formations, U.S. Gulf Coast, 2019","title":"Assessment of undiscovered oil and gas resources in the Upper Cretaceous Austin Chalk and Tokio and Eutaw Formations, U.S. Gulf Coast, 2019","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 6.9 billion barrels of oil and 41.5 trillion cubic feet of natural gas in conventional and continuous accumulations in the Upper Cretaceous Austin Chalk and Tokio and Eutaw Formations onshore and in State waters of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203045","usgsCitation":"Pitman, J.K., Paxton, S.T., Kinney, S.A., Whidden, K.J., Haines, S.S., Varela, B.A., Mercier, T.J., Woodall, C.A., Schenk, C.J., Leathers-Miller, H.M., Pearson, O.N., Burke, L.A., Le, P.A., Birdwell, J.E., Gianoutsos, N.J., French, K.L., Drake, R.M., II, Finn, T.M., Ellis, G.S., Gaswirth, S.B., Marra, K.R., Tennyson, M.E., and Shorten, C.M., 2020, Assessment of undiscovered oil and gas resources in the Upper Cretaceous Austin Chalk and Tokio and Eutaw Formations, U.S. Gulf Coast, 2019 (ver 1.1., December 2020): U.S. Geological Survey Fact Sheet 2020–3045, 4 p., https://doi.org/10.3133/fs20203045.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"N","ipdsId":"IP-114091","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":381196,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2020/3045/verHist.txt","text":"Version History","size":"4.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2020-3045 version History"},{"id":379804,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F5O4TX","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Gulf Coast Mesozoic Province, Upper Cretaceous Austin Chalk Group and Tokio and Eutaw Formations Assessment Units and Input Data Forms"},{"id":379802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3045/coverthb2.jpg"},{"id":379803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3045/fs20203045.pdf","text":"Report","size":"2.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3045"}],"country":"United States","state":"Alabama, Arkansas, Louisiana, Mississippi, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.919921875,\n 27.293689224852407\n ],\n [\n -85.166015625,\n 27.293689224852407\n ],\n [\n -85.166015625,\n 35.17380831799959\n ],\n [\n -102.919921875,\n 35.17380831799959\n ],\n [\n -102.919921875,\n 27.293689224852407\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 29, 2020; Version 1.1: December 11, 2020","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Genetically-based seed transfer zones are described herein for two priority restoration species on and adjacent to the Colorado Plateau (Massatti 2020). Species include Cleome lutea Hook. (Capparaceae; commonly called yellow spiderflower or yellow beeplant; synonym Peritoma lutea (Hook.) Raf.) and Machaeranthera canescens (Pursh) A. Gray (Asteraceae; commonly called hoary tansyaster; synonym Dieteria canescens (Pursh) Nutt.). The seed transfer zones depict both evolutionary lineages and inferences of adaptation as discerned from molecular investigations. These shapefile data may support successful restoration outcomes if, for example, seed transfer follows seed transfer zones depicted herein and/or composite seed strategies for native plant materials development utilize seed transfer zones when determining which seed accessions may be combined. The ultimate goal of these seed transfer zones is to protect species’ natural patterns of genetic variation – genetic diversity is increasingly recognized a unit of conservation concern (Hoban et al. 2013) – and to understand species' adaptations to regional environmental gradients. Development of these seed transfer zones was funded by CPNPP, which was established, in part, to evaluate and develop native plant materials for important grass and forb species adapted to the unique ecological conditions of the Colorado Plateau (Wood et al. 2015). Each species’ shapefile data available in Massatti (2020) are described in turn.
","language":"English","publisher":"Bureau of Land Management","collaboration":"Bureau of Land Management","usgsCitation":"Massatti, R., 2020, Genetically-informed seed transfer zones for Cleome lutea and Machaeranthera canescens across the Colorado Plateau and adjacent regions, 9 p.","productDescription":"9 p.","ipdsId":"IP-124660","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":381254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381240,"type":{"id":15,"text":"Index Page"},"url":"https://www.blm.gov/sites/blm.gov/files/docs/2020-12/genetic_STZs_CPNPP_2020.pdf"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 36.59788913307022\n ],\n [\n -108.5009765625,\n 36.59788913307022\n ],\n [\n -108.5009765625,\n 39.87601941962116\n ],\n [\n -112.32421875,\n 39.87601941962116\n ],\n [\n -112.32421875,\n 36.59788913307022\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806745,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216895,"text":"70216895 - 2020 - Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences","interactions":[],"lastModifiedDate":"2022-08-16T17:31:25.733964","indexId":"70216895","displayToPublicDate":"2020-12-11T08:17:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences","docAbstract":"Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs.
Dynamic triggering of earthquakes has been reported at various fault systems. The triggered earthquakes are thought to be caused either directly by dynamic stress changes due to the passing seismic waves, or indirectly by other nonlinear processes that are initiated by the passing waves. Distinguishing these physical mechanisms is difficult because of the general lack of high‐resolution earthquake catalogs and robust means to quantitatively evaluate triggering responses, particularly, delayed responses. Here we use the high‐resolution Quake Template Matching catalog in Southern California to systematically evaluate teleseismic dynamic triggering patterns in the San Jacinto Fault Zone and the Salton Sea Geothermal Field from 2008 to 2017. We develop a new statistical approach to identify triggered cases, finding that approximately 1 out of every 5 global Mw ≥ 6 earthquakes dynamically trigger microearthquakes in Southern California. The triggering responses include both instantaneous and delayed triggering, showing a highly heterogeneous pattern and indicating possible evolving triggering thresholds. We do not observe a clear peak ground velocity triggering threshold that can differentiate triggering earthquakes from non‐triggering events, but there are subtle differences in the frequency content that may possibly differentiate the earthquakes. In contrast to the depth distribution of background seismicity, the identified triggered earthquakes tend to concentrate at the edges of the seismogenic zones. Although instantaneously triggered earthquakes are likely a result of dynamic Coulomb stress changes, the cases of delayed dynamic triggering are best explained by nonlinear triggering processes, including cyclic material fatigue, accelerated transient creep, and stochastic frictional heterogeneities.
Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this common data structure, using three freshwater mussel species being considered for listing under the US Endangered Species Act. The probability that a population is classified under each risk category was modeled as a function of projected landscape change using ordered probit regression, assuming observed categories reflect a latent, continuous probability of persistence. All three species were more likely than not (mean probability >0.5) to be classified as extirpated or low condition throughout their range based on effects of urban development and hydrologic alteration. Spatial variation in estimates revealed strongholds and high-risk areas relevant to conservation decision making. Projected change in probabilities of each risk category based on multiple land-use and climate models was generally small relative to high baseline risk resulting from past landscape changes. Assessing extinction risk based on probabilities of ordinal condition as a function of landscape patterns may provide a flexible and robust approach for many at-risk taxa by adjusting species' demographic criteria to match relative risk categories, following standardized criteria, or using expert elicitation for data-deficient species. This approach provides decision makers with a useful measure of uncertainty around ordinal classifications and provides a framework for estimating future risk based on projections of anthropogenic stressors.
Salt marsh survival with sea‐level rise (SLR) increasingly relies on soil organic carbon (SOC) accumulation and preservation. Using a novel combination of geochemical approaches, we characterized fine SOC (≤1 mm) supporting marsh elevation maintenance. Overlaying thermal reactivity, source (δ13C), and age (F14C) information demonstrates several processes contributing to soil development: marsh grass production, redeposition of eroded material, and microbial reworking. Redeposition of old carbon, likely from creekbanks, represented ∼9‐17% of shallow SOC (≤26 cm), indicating that this process may become increasingly important with SLR. Soils stored marsh grass‐derived compounds with a range of reactivities that were reworked over centuries‐to‐millennia. Decomposition decreases SOC thermal reactivity throughout the soil column while the decades‐long disturbance of ponding accelerated this shift in surface horizons. Empirically derived estimates of SOC turnover based on geochemical composition spanned a wide range (640–9,951 years) and have the potential to inform future predictions of marsh ecosystem evolution.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL090287","usgsCitation":"Luk, S., Todd-Brown, K., Eagle, M.J., McNichol, A., Sanderman, J., Gosselin, K., and Spivak, A.C., 2020, Soil organic carbon development and turnover in natural and disturbed salt marsh environments: Geophysical Research Letters, v. 48, e2020GL090287, 11 p., https://doi.org/10.1029/2020GL090287.","productDescription":"e2020GL090287, 11 p.","ipdsId":"IP-124399","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454676,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020gl090287","text":"External Repository"},{"id":436699,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HIOWKT","text":"USGS data release","linkHelpText":"Collection, analysis, and age-dating of sediment cores from a salt marsh platform and ponds, Rowley, Massachusetts, 2014-15"},{"id":382124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Plum Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.77667236328125,\n 42.69984747212718\n ],\n [\n -70.7687759399414,\n 42.7028751605754\n ],\n [\n -70.79418182373047,\n 42.75709622397268\n ],\n [\n -70.80448150634766,\n 42.796912183869914\n ],\n [\n -70.8072280883789,\n 42.817566071581616\n ],\n [\n -70.82164764404297,\n 42.81907706089614\n ],\n [\n -70.82405090332031,\n 42.806736234334345\n ],\n [\n -70.82061767578125,\n 42.79892750088133\n ],\n [\n -70.81546783447266,\n 42.79237748061043\n ],\n [\n -70.80894470214844,\n 42.78784244506899\n ],\n [\n -70.81306457519531,\n 42.78255115030856\n ],\n [\n -70.81615447998047,\n 42.768186784785875\n ],\n [\n -70.8120346069336,\n 42.75835661495798\n ],\n [\n -70.80997467041014,\n 42.739700210406156\n ],\n [\n -70.79692840576172,\n 42.71801138812346\n ],\n [\n -70.78285217285156,\n 42.69984747212718\n ],\n [\n -70.77667236328125,\n 42.69984747212718\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2021-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Luk, Sheron","contributorId":247610,"corporation":false,"usgs":false,"family":"Luk","given":"Sheron","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":808031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Todd-Brown, Katherine","contributorId":240705,"corporation":false,"usgs":false,"family":"Todd-Brown","given":"Katherine","affiliations":[{"id":34255,"text":"Wilfred Laurier University","active":true,"usgs":false}],"preferred":false,"id":808032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":808033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNichol, Ann","contributorId":247612,"corporation":false,"usgs":false,"family":"McNichol","given":"Ann","affiliations":[{"id":49591,"text":"Marine Geology and Geophysics Department, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":808034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanderman, Jonathan","contributorId":187477,"corporation":false,"usgs":false,"family":"Sanderman","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":808035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gosselin, Kelsey","contributorId":247614,"corporation":false,"usgs":false,"family":"Gosselin","given":"Kelsey","email":"","affiliations":[{"id":49592,"text":"Marine Chemistry and Geochemistry Department, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":808036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":808037,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216869,"text":"ofr20201117 - 2020 - Environmental data associated with sites infected with white-nose syndrome (WNS) before October 2011 in North America","interactions":[],"lastModifiedDate":"2020-12-14T17:12:04.819056","indexId":"ofr20201117","displayToPublicDate":"2020-12-10T16:30:00","publicationYear":"2020","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":"2020-1117","displayTitle":"Environmental Data Associated With Sites Infected With White-Nose Syndrome (WNS) Before October 2011 in North America","title":"Environmental data associated with sites infected with white-nose syndrome (WNS) before October 2011 in North America","docAbstract":"White-nose syndrome (WNS) is an emerging infectious disease of hibernating bats caused by a fungus previously known as Geomyces destructans and reclassified as Pseudogymnoascus destructans. The disease was first documented in 2006 in New York, has since spread across much of eastern North America, and as of January 2012, had caused the death of at least 5.7 to 6.7 million bats. Previous studies have suggested that environmental conditions play a strong role in WNS mortality. However, to predict where and when the disease will spread to new sites is difficult because detailed site information and associated environmental data are notably sparse. This paper presents a chronology of where and when WNS was detected in North America before October 2011 and indicates who reported the infections. This paper also presents available data on WNS-infected site elevation, geology, sediment chemistry and biota, air temperature, and relative humidity.
By the end of September 2011, at least 241 known WNS-infected sites were in North America and the number of infected sites per winter season had increased each year since 2006. The progressive increase in the number of infected sites per winter season suggests that the number of WNS infections had not peaked as of the 2010–11 winter season. WNS-infected sites include caves and mines, but the sites are not restricted by elevation, lithology, or strata age. Available data on site sediment chemistry are sparse but present a wide range of values, suggesting that caves and mines may contain a great range of microenvironments that are still poorly understood. The distribution of WNS may be restricted by air temperature and relative humidity. Published air temperature values from WNS-infected sites range from −15 to 33 degrees Celsius (but most temperature values are less than 20 degrees Celsius), and relative humidity values range from 50 to 100 percent. The spread of WNS may be restricted by a cave or mine temperature threshold of 20 degrees Celsius (which is likely to be south of most of the continental United States) and by some yet to be determined threshold of low relative humidity. These results indicate that WNS may not spread south into Mexico or to Puerto Rico.
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