Perchlorate (ClO4−) has synthetic and natural sources. Synthetic ClO4− is released to the environment from its use as an oxidant in military and aerospace applications, and from its presence in a variety of common commercial products, such as safety flares, chlorate herbicides, and fireworks. Natural sources of ClO4− in the environment include imported nitrate fertilizers derived from salt deposits in the Atacama Desert of Chile and indigenous natural ClO4− that accumulates in unsaturated soils and groundwaters in other arid and semi-arid environments, largely from atmospheric deposition. The stable isotope ratios of chlorine (37Cl/35Cl) and oxygen (18O/16O, 17O/16O) and the isotopic abundance of radioactive 36Cl in ClO4− can be used to discriminate these different sources. Perchlorate was previously detected at relatively high concentrations (3.8–34.7 μg/L) in groundwater from many wells in the Boardman-Umatilla area near the Columbia River in northeastern Oregon, which is a semi-arid, highly agricultural, heavily irrigated area that includes several past and current military installations. Eight representative groundwater wells were sampled throughout this region and isotopic characteristics of ClO4− collected from each well were measured along with other chemical and isotopic parameters including tritium and other groundwater age indicators. Isotopic data indicate that indigenous natural ClO4− was present in groundwater from all sampled wells and was the predominant source in five of the wells. Synthetic ClO4− was present in the three remaining wells with natural ClO4−, and a minor fraction of Atacama-fertilizer-derived ClO4− was indicated in one of the wells. Data from this study expand the geographic area of the USA in which indigenous natural ClO4− has been detected to include the semi-arid northwest. This study also illustrates the role of irrigation recharge as a mechanism for producing relatively high concentrations of indigenous natural ClO4− in groundwater by flushing accumulated salts from the unsaturated zone.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2022.105232","usgsCitation":"Hatzinger, P.B., Bohlke, J., Jackson, W., Gu, B., Mroczkowski, S.J., and Sturchio, N.C., 2022, Isotopic discrimination of natural and anthropogenic perchlorate sources in groundwater in a semi-arid region of northeastern Oregon (USA): Applied Geochemistry, v. 139, 105232, 11 p., https://doi.org/10.1016/j.apgeochem.2022.105232.","productDescription":"105232, 11 p.","ipdsId":"IP-130304","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":448682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1879959","text":"Publisher Index Page"},{"id":399737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C28","displayTitle":"An Apparent Dip Calculator for Spreadsheets","title":"An apparent dip calculator for spreadsheets","docAbstract":"This report and spreadsheet calculator contain Microsoft Excel-based equations that are useful in structural geology to calculate plunge or apparent dip when measuring lineations on a plane. The spreadsheet allows users to measure the trend or the plunge of a lineation and calculate the corresponding unknown value of trend or plunge. The spreadsheet provides the user with two options:
Option 1: Calculates the plunge of a lineation from the measured strike and dip of a plane and the measured trend of a lineation.
Option 2: Calculates two potential trends of a lineation from the measured strike and dip of a plane and a measured plunge of a lineation. The user can decide which trend is appropriate for their data.
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U.S. Geological Survey
12201 Sunrise Valley Drive, MS 926A
Reston, VA 20192
We conducted a macroscale study of 2210 shallow lakes (mean depth ≤ 3 m or a maximum depth ≤ 5 m) in the Upper Midwestern and Northeastern USA. We asked the following: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4360 non-shallow lakes, and do results differ by hydrologic connectivity class? Spatial patterns and Bayesian hierarchical models indicated that shallow lakes had higher TP and CHLa than non-shallow lakes, connected shallow lakes were more productive than unconnected shallow lakes, and there was regional variation in these patterns. Important predictors of TP and CHLa included lake-specific watershed:lake area ratio, forested land use/cover, and baseflow; unconnected lakes were more difficult to predict than connected lakes; and region-specific predictors were mostly unimportant. Shallow lake TP–CHLa relationships were less steep than for non-shallow lakes and these relationships varied regionally. Our results, combined with the facts that only 23% of lakes in the study extent have depth data and that shallow and unconnected lakes are undersampled, have important implications for estimates of lake contributions to global cycles that are based mainly on large (and deeper) lakes.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-022-04811-1","usgsCitation":"Spence Cheruvelil, K., Webster, K., King, K., Poisson, A., and Wagner, T., 2022, Taking a macroscale perspective to improve understanding of shallow lake total phosphorus and chlorophyll a: Hydrobiologia, v. 849, p. 3663-3677, https://doi.org/10.1007/s10750-022-04811-1.","productDescription":"15 p.","startPage":"3663","endPage":"3677","ipdsId":"IP-130204","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":465993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Illinois, Indiana, Iowa, Maine, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, 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\"}}]}","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Spence Cheruvelil, Kendra","contributorId":348079,"corporation":false,"usgs":false,"family":"Spence Cheruvelil","given":"Kendra","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webster, Katherine","contributorId":348080,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Katelyn","contributorId":348081,"corporation":false,"usgs":false,"family":"King","given":"Katelyn","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poisson, Autumn C.","contributorId":348082,"corporation":false,"usgs":false,"family":"Poisson","given":"Autumn C.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922922,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243724,"text":"70243724 - 2022 - Active forest management accelerates carbon storage in plantation forests in Lishui, southern China","interactions":[],"lastModifiedDate":"2023-05-18T13:48:54.445288","indexId":"70243724","displayToPublicDate":"2022-02-25T08:39:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5054,"text":"Forest Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Active forest management accelerates carbon storage in plantation forests in Lishui, southern China","docAbstract":"China has committed to achieving peak CO2 emissions before 2030 and carbon neutrality before 2060; therefore, accelerated efforts are needed to better understand carbon accounting in industry and energy fields as well as terrestrial ecosystems. The carbon sink capacity of plantation forests contributes to the mitigation of climate change. Plantation forests throughout the world are intensively managed, and there is an urgent need to evaluate the effects of such management on long-term carbon dynamics.
We assessed the carbon cycling patterns of ecosystems characterized by three typical plantation species (Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), oak (Cyclobalanopsis glauca (Thunb.) Oerst.), and pine (Pinus massoniana Lamb.)) in Lishui, southern China, by using an integrated biosphere simulator (IBIS) tuned with localized parameters. Then, we used the state-and-transition simulation model (STSM) to study the effects of active forest management (AFM) on carbon storage by combining forest disturbance history and carbon cycle regimes.
1) The carbon stock of the oak plantation was lower at an early age (<50 years) but higher at an advanced age (>50 years) than that of the Chinese fir and pine plantations. 2) The carbon densities of the pine and Chinese fir plantations peaked at 70 years (223.36 Mg·ha‒1) and 64 years (232.04 Mg·ha‒1), respectively, while the carbon density in the oak plantation continued increasing (>100 years). 3) From 1989 to 2019, the total carbon pools of the three plantation ecosystems followed an upward trend (an annual increase of 0.16–0.22 Tg C), with the largest proportional increase in the aboveground biomass carbon pool. 4) AFM increased the recovery of carbon storage after 1996 and 2009 in the pine and Chinese fir plantations, respectively, but did not result in higher growth in the oak plantation. 5) The proposed harvest planning is reasonable and conducive to maximizing the carbon sequestration capacity of the forest.
This study provides an example of a carbon cycle coupling model that is potentially suitable for simulating China's plantation forest ecosystems and supporting carbon accounting to monitor peak CO2 emissions and reach carbon neutrality.
To investigate the sensitivity of slip inversions to station distribution and choice of empirical Green’s function (EGF), we examine three microearthquakes that occurred within the high‐density LArge‐n Seismic Survey in Oklahoma (LASSO) nodal seismic array. The LASSO array’s dense distribution of 1825 geophones provides an exceptional level of spatial and azimuthal coverage, allowing for more accurate inversions of slip than are possible with typical station distributions. The highly accurate slip inversions, in turn, allow for the exploration of the sensitivity of slip inversions to station distribution and parameter choices. We examine the effects of these choices using three well‐recorded strike‐slip microearthquakes (ML 1.7, 2.3, and 2.7) using an EGF method. From this analysis and the systematic testing of varied network arrangements, we find that station distributions that have uniform coverage of azimuth and distance can retrieve the overall pattern of slip, but the estimated amplitude of slip can vary by 30% for high‐slip regions due to small variations in station location. In addition, we find that the distance range that accurately resolves the overall pattern of slip is the one that contains the takeoff angles of 45°–65°. Concerning azimuthal coverage, a network with >270° performs similarly to having complete coverage. The choice of EGF can shift the location of resolved areas of slip and their amplitude, depending on its similarity in location and radiation pattern to the target earthquake.
Urban development is a well-known stressor for stream ecosystems, presenting a challenge to managers tasked with mitigating its effects. For the past 20 y, streamflow, water quality, geomorphology, and benthic communities were monitored in 5 watersheds in Montgomery County, Maryland, USA. This study presents a synthesis of multiple studies of monitoring efforts in the study area and new analysis of more recent monitoring data to document the primary lessons learned from monitoring. The monitored watersheds include a forested control, an urban control with centralized stormwater management, and 3 suburban treatment watersheds featuring low-impact development and a high density of infiltration-focused stormwater facilities distributed across the watershed. Treatment watersheds were monitored before development, during construction, and after development. Monitoring was initiated to inform adaptive management of stormwater and impervious cover limits within the study area, with a focus on the impacts of distributed stormwater management. Results from our synthesis indicate that distributed stormwater management is advantageous compared with centralized stormwater management in numerous ways. Hydrologic benefits were greater with distributed stormwater infrastructure, demonstrating the ability to mitigate runoff volumes and peak flows and, for small storms, replicate predevelopment conditions. Baseflow temporarily increased during the construction phase in the treatment watersheds. Water-quality benefits were mixed, with declines in baseflow nitrate concentrations but limited changes to nitrate export and increases in specific conductance after development. Substantial topographic changes occurred during construction in the treatment watersheds, including changes within the riparian zone, despite riparian buffer protections. Ecological monitoring indicated that even though index of biotic integrity scores rebounded in some cases, sensitive benthic macroinvertebrate families did not fully recover in the treatment watersheds. Lessons learned from this synthesis highlight the importance of tracking multiple indicators of stream health and considering past land use and that more stormwater facilities distributed across the watershed is beneficial but cannot mitigate the effects of all urban stressors on aquatic ecosystems.
Smear slide petrography has been a standard technique during scientific ocean drilling expeditions to characterize sediment composition and classify sediment types, but presentation of these percent estimates to track downcore trends in sediment composition has become less frequent over the past 2 decades. We compare semi-quantitative smear slide composition estimates to physical property (natural gamma radiation, NGR) and solid-phase geochemical (calcium carbonate, CaCO3 %) measurements from a range of marine depositional environments in the northern Indian Ocean (Bay of Bengal, Andaman Sea, Ninetyeast Ridge) collected during International Ocean Discovery Program (IODP) Expedition 353. We show that presenting smear slide estimates as percentages, rather than abundance categories, reveals similar downcore variation in composition to the more quantitative core analyses. Overall downcore trends in total calcareous components from smear slides (foraminifers + nannofossils + shell fragments + authigenic carbonate) follow similar downcore trends to samples measured by CaCO3 coulometry. Total lithogenic components (clay + mica + quartz + feldspars + lithic grains + vitric grains + glauconite + heavy minerals + iron oxides) and clay from smear slides track reasonably well with NGR measurements. Comparison of site averages of absolute percentages of total calcium carbonate from coulometry and total calcareous components from smear slide observations reveals an overestimation in carbonate percentages in smear slides (likely due in part to underestimation of the clay fraction), especially in sediments rich in smectite clays. Differences in sediment color between sites and settling of clay particles during slide preparation may contribute to this discrepancy. Although smear slide estimates range in accuracy depending on the training of the operator, we suggest that sedimentologists describing cores obtained during scientific drilling can use the percent estimates of sedimentary components in smear slides to identify trends and cyclicity in marine sediment records.
","language":"English","publisher":"Copernicus","doi":"10.5194/sd-30-59-2022","usgsCitation":"Phillips, S.C., and Littler, K., 2022, Comparison of sediment composition by smear slides to quantitative shipboard data: A case study on the utility of smear slide percent estimates, IODP Expedition 353, northern Indian Ocean: Scientific Drilling, v. 30, p. 59-74, https://doi.org/10.5194/sd-30-59-2022.","productDescription":"16 p.","startPage":"59","endPage":"74","ipdsId":"IP-129904","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/sd-30-59-2022","text":"Publisher Index Page"},{"id":396535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Indian Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 65.126953125,\n 0\n ],\n [\n 100.01953125,\n 0\n ],\n [\n 100.01953125,\n 24.126701958681668\n ],\n [\n 65.126953125,\n 24.126701958681668\n ],\n [\n 65.126953125,\n 0\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationDate":"2022-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":836486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Littler, Kate","contributorId":287090,"corporation":false,"usgs":false,"family":"Littler","given":"Kate","email":"","affiliations":[{"id":17840,"text":"University of Exeter","active":true,"usgs":false}],"preferred":false,"id":836487,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229706,"text":"70229706 - 2022 - Nekton community dynamics within active and inactive deltas in a major river estuary: Potential implications for altered hydrology regimes","interactions":[],"lastModifiedDate":"2022-03-17T13:11:00.700596","indexId":"70229706","displayToPublicDate":"2022-02-24T12:00:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"title":"Nekton community dynamics within active and inactive deltas in a major river estuary: Potential implications for altered hydrology regimes","docAbstract":"High fisheries production within estuaries is associated with coastal upwelling, tidal mixing, and land-based runoff facing increasing impacts from climate and human activities. Active river deltas receive large riverine inflows compared to inactive river deltas, providing contrasting estuaries to compare impacts of river inflow on estuarine nekton. We quantified nekton assemblages and stable isotopes (δ13C, δ15N) of commercially important blue crab Callinectes sapidus Rathbun, 1896 within an active and inactive delta in coastal Louisiana to explore the impacts of differing riverine inflow. Crustaceans dominated estuarine assemblages, differing only by season and not delta type, with summer and fall supporting highest densities. Fish density and assemblages differed by the interaction of season and delta due to differences during the 2019 record high spring river inflow. During this period, the active delta supported reduced fish densities and richness compared to the inactive delta. Nekton densities across deltas and seasons reflect a combination of species life history characteristics and habitat conditions. The high spring river discharge in 2019 impacted habitat availability (reduced presence of submerged aquatic vegetation), water conditions (decreased temperature and salinity), and potentially displaced nekton to unsampled habitat areas (i.e. interior marsh surface) within the active delta. While differences in nekton density and assemblages were only evident during the high spring river discharge, δ15N values of blue crabs were approximately 1.5 times higher in the active delta, potentially indicating more terrestrial influence. Understanding how altered inflow impacts environmental variables supporting estuarine nekton production remains critical for supporting management within these hydrologically managed regions.
","language":"English","publisher":"Inter-Research","doi":"10.3354/ab00748","usgsCitation":"Taylor, C.B., Nyman, J.A., and La Peyre, M., 2022, Nekton community dynamics within active and inactive deltas in a major river estuary: Potential implications for altered hydrology regimes: Aquatic Biology, v. 31, p. 1-18, https://doi.org/10.3354/ab00748.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-132543","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":448690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00748","text":"Publisher Index Page"},{"id":397188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta Basin, Terrebonne Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.4337158203125,\n 29.16655229520015\n ],\n [\n -89.2694091796875,\n 29.16655229520015\n ],\n [\n -89.2694091796875,\n 30.088107753367257\n ],\n [\n -91.4337158203125,\n 30.088107753367257\n ],\n [\n -91.4337158203125,\n 29.16655229520015\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Caleb B.","contributorId":288505,"corporation":false,"usgs":false,"family":"Taylor","given":"Caleb","email":"","middleInitial":"B.","affiliations":[{"id":61780,"text":"School of Renewable Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyman, John Andrew","contributorId":288506,"corporation":false,"usgs":false,"family":"Nyman","given":"John","email":"","middleInitial":"Andrew","affiliations":[{"id":61780,"text":"School of Renewable Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228825,"text":"fs20223006 - 2022 - Illinois and Landsat","interactions":[],"lastModifiedDate":"2023-01-21T15:55:11.063065","indexId":"fs20223006","displayToPublicDate":"2022-02-24T10:34:09","publicationYear":"2022","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":"2022-3006","displayTitle":"Illinois and Landsat","title":"Illinois and Landsat","docAbstract":"Illinois is home to more than 12 million residents, including those living in Chicago, the third-largest city in the United States. Yet farmland claims about 75 percent of the largely flat terrain in Illinois. Tallgrass prairie once covered “The Prairie State,” and some remnants remain, but corn and soybeans are a far more common sight now. Adding variety to the landscape, beaches line the State’s Lake Michigan shoreline in the northeast, and more than 80,000 miles of rivers and streams flow along and through the State, including the central cities of Springfield and Peoria. Forests fill several million acres, mostly in the west and the rolling hills of the south.
Urban, agricultural, and forested areas each have environmental characteristics that are noticeable to those who live within them and to those who study the Earth’s surface from space. Landsat satellite data can reveal not only the current condition of these areas, but also when and where they have changed. A better knowledge of Illinois’ past helps its residents better prepare for the future.
Here are just a few examples of how Landsat benefits Illinois.
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Hawksbill sea turtles Eretmochelys imbricata inhabiting the Hawaiian Islands are extremely rare and listed as endangered under the US Endangered Species Act. The paucity of data on basic hawksbill ecology continues to hinder effective management of the species. We analyzed stranding data collected between 1984 and 2018 to gain insights into the distribution, demography, and conservation challenges facing hawksbills in Hawai‘i. In doing so, we present a comprehensive description of the population across developmental stages and rank threats that may be impeding their successful recovery. Over the >30 yr data set, we recorded a total of only 111 juvenile and adult hawksbill stranding events. Interactions with nearshore recreational fishing gear were documented for a large proportion (48.6%) of stranding events in the Hawaiian Islands, identifying this as the primary management challenge for the species. Stranding events were biased towards females (female to male sex ratio of 4.8:1.0), which may be indicative of the population as a whole. Even though the majority of hawksbills nest on the islands of Hawai‘i Moloka‘i, and Maui, the greatest number of juvenile to adult strandings was found to be on the island of Oahu (n = 47). Temporal distribution of the majority of adult hawksbill strandings (72.2%) occurred during a 4 mo period between June and September. We discuss these and other findings that help identify future research and conservation efforts to mitigate anthropogenic threats in Hawai‘i for this enigmatic population.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01167","usgsCitation":"Brunson, S., Gaos, A., Kelly, I., van Houtan, K., Swimmer, Y., Hargrove, S., Balazs, G., Work, T.M., and Jones, T., 2022, Three decades of stranding data reveal insights into endangered hawksbill sea turtles in Hawai‘i: Endangered Species Research, v. 47, p. 109-118, https://doi.org/10.3354/esr01167.","productDescription":"10 p.","startPage":"109","endPage":"118","ipdsId":"IP-134533","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":448691,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01167","text":"Publisher Index Page"},{"id":397393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Groundwater levels were measured mainly from 9:00 a.m. to 12:00 p.m. (times listed in Hawai‘i standard time) and provide a snapshot of groundwater levels during the survey period. Following a reported fuel release that affected groundwater quality in the Red Hill area, several production wells were shut down in the weeks prior to the synoptic survey. These wells include the Red Hill Shaft (shut down on November 28, 2021) and the Hālawa Shaft (shut down on December 3, 2021, except for weekly, short-duration operations for water-quality sampling). Groundwater levels measured in wells during the synoptic survey ranged from 16.34 to 19.77 feet above mean sea level.
The groundwater levels collected during the multiagency synoptic survey contain uncertainty because of several potential sources of error associated with (1) the accuracy of the measuring tapes used, (2) the accuracy of the measuring-point altitude at the top of each well, (3) well plumbness and alignment, (4) human error, and (5) changing conditions during the survey period. Because of these potential sources of error, comparability of groundwater-level measurements may be affected. Some of the sources of uncertainty can be addressed and lead to improved accuracy and comparability of the groundwater levels. For example, uncertainty associated with the measuring-point altitudes can be addressed by resurveying measuring-point altitudes to a common vertical datum using consistent surveying methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221018","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1018, 10 p., https://doi.org/10.3133/ofr20221018.","productDescription":"Report: v, 10 p.; Data Release","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-137125","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":396393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1018/covrthb.jpg"},{"id":396394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1018/ofr20221018.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":401563,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221048","text":"Open-File Report 2022-1048","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, January 18, 2022, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1048, 11 p., https://doi.org/10.3133/ofr20221048.","linkHelpText":"- January 18, 2022, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i"},{"id":396395,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the nation","description":"U.S. Geological Survey, 2022, USGS water data for the nation: U.S. Geological Survey National Water Information database, https://doi.org/10.5066/F7P55KJN"},{"id":501763,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112526.htm","linkFileType":{"id":5,"text":"html"}},{"id":404438,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221069","text":"Open-File Report 2022-1069","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, Groundwater-level monitoring from January 17 to March 3, 2022, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1069, 29 p., https://doi.org/10.3133/ofr20221069.","linkHelpText":"- Groundwater-Level Monitoring from January 17 to March 3, 2022, Hālawa Area, O‘ahu, Hawai‘i"}],"country":"United States","state":"Hawaii","otherGeospatial":"O‘ahu, Hālawa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.95867919921875,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.332873489271286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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A total of 4344 magmatic U-Pb ages in the range 2300 to 800 Ma have been compiled from the Great Proterozoic Accretionary Orogen along the margin of the Columbia / Nuna supercontinent and from the subsequent Grenvillian collisional orogens forming the core of Rodinia. The age data are derived from Laurentia (North America and Greenland, n = 1212), Baltica (NE Europe, n = 1922), Amazonia (central South America, n = 625), Kalahari (southern Africa and Dronning Maud Land in East Antarctica, n = 386), and western Australia (n = 199). Laurentia, Baltica, and Amazonia (and possibly other cratons) most likely formed a ca. 10 000-km-long external active continental margin of Columbia from its assembly at ca. 1800 Ma until its dispersal at ca. 1260 Ma, after which all cratons studied were involved in the Rodinia-forming Grenvillian orogeny. However, the magmatic record is not smooth and even but highly irregular, with marked peaks and troughs, both for individual cratons and the combined data set.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2021.106463","usgsCitation":"Johansson, A., Bingen, B., Huhma, H., Waight, T., Vestergaard, R., Soesoo, A., Skridlaite, G., Krzeminska, E., Shumlyanskyy, L., Holland, M.E., Holm-Denoma, C., Teixeira, W., Faleiros, F., Riberio, B., Jacobs, J., Wang, C., Thomas, R., Macey, P., Kirkland, C., Hartnady, M., Eglington, B., Puetz, S., and Condie, K., 2022, A geochronological review of magmatism along the external margin of Columbia and in the Grenville-age orogens forming the core of Rodinia: Precambrian Research, v. 371, 106463, 43 p., https://doi.org/10.1016/j.precamres.2021.106463.","productDescription":"106463, 43 p.","ipdsId":"IP-128915","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":448693,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2021.106463","text":"Publisher 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Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":886790,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Puetz, Stephen","contributorId":331131,"corporation":false,"usgs":false,"family":"Puetz","given":"Stephen","email":"","affiliations":[{"id":79131,"text":"Progressive Science Institute","active":true,"usgs":false}],"preferred":false,"id":886791,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Condie, Kent","contributorId":331132,"corporation":false,"usgs":false,"family":"Condie","given":"Kent","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":886792,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70229146,"text":"70229146 - 2022 - Pervasive, preferential flow through mega-thick unsaturated zones in the Southern Great Basin","interactions":[],"lastModifiedDate":"2022-08-01T16:53:28.674928","indexId":"70229146","displayToPublicDate":"2022-02-24T06:58:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Pervasive, preferential flow through mega-thick unsaturated zones in the Southern Great Basin","docAbstract":"Recharge from preferential flow through mega-thick (100–1,000 m) unsaturated zones is a pervasive phenomenon, as demonstrated with a case study of volcanic highland recharge areas in the Great Basin province in southern Nevada, USA. Statistically significant rising water-level trends occur for most study-area wells and resulted from a relatively wet period (1969–2005) in south-central Nevada. Wet and dry winters control water-level trends, with water levels rising within a few months to a year following a wet-winter recharge event and declining during sustained dry periods. Even though a megadrought has persisted since 2000, this drought condition did not preclude major recharge events. Modern groundwater reaching the water table is consistent with previous geochemical studies of the study area that indicate mixing of modern and late Pleistocene recharge water. First-order approximations and simple mixing models of modern and late Pleistocene water indicate that 10 to 40 percent of recharge is preferential flow and that modern recharge may play a larger role in the water budget than previously thought.
The Republican River is the primary inflow to Milford Lake and drains areas of Kansas, Nebraska, and Colorado. Milford Lake has been listed as impaired and designated hypereutrophic by the Kansas Department of Health and Environment because of excessive nutrient loading. Milford Lake had confirmed harmful algal blooms every summer from 2011 through 2017 and in 2020 and 2021.
In the lower Republican River drainage basin, the Regional Conservation Partnership Program, administered by the Natural Resources Conservation Service, provides reimbursement to agricultural producers that implement best management practices intended to decrease sediment and nutrient runoff and loading into Milford Lake. Sediment and nutrient loads could potentially be driving factors in the development of harmful algal blooms in the reservoir.
Since July 2018, the U.S. Geological Survey, in cooperation with the Kansas Water Office, has collected continuous and discrete water-quality data at the Republican River at Clay Center, Kansas, streamgage (U.S. Geological Survey station 06856600), which is about 15 river miles upstream from Milford Lake. This report documents site-specific regression models for the computation of continuous concentrations of suspended sediment, total nitrogen, total phosphorus, and total carbon developed using continuous and discrete data collected from July 24, 2018, the date of continuous water-quality monitor installation, through March 31, 2021. The objective of this study is to characterize sediment and nutrient transport in the Milford Lake drainage basin before, during, and after best management practice implementation using the models described in this report.
The explanatory variable turbidity explained a high amount (72–96 percent) of the variance in suspended-sediment, total nitrogen, total phosphorus, and total carbon concentrations. Statistical plots for the four selected models showed the desired normality and homoscedasticity in residuals, and model standard error ratios indicated that recomputing each selected model after removing a randomly selected 10 percent of the data did not substantially change model coefficients.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225016","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Leiker, B.M., 2022, Linear regression model documentation for computing water-quality constituent concentrations using continuous real-time water-quality data for the Republican River, Clay Center, Kansas, July 2018 through March 2021: U.S. Geological Survey Scientific Investigations Report 2022–5016, 13 p., https://doi.org/10.3133/sir20225016.","productDescription":"Report: vi, 13 p.; 4 Appendixes; Dataset","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-133566","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":396379,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"—USGS water data for the Nation"},{"id":396378,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016.XML","linkFileType":{"id":8,"text":"xml"}},{"id":396376,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix4.pdf","text":"Appendix 4","size":"757 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 4","linkHelpText":"—Model Archive Summary for Total Carbon at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396375,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix3.pdf","text":"Appendix 3","size":"681 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 3","linkHelpText":"—Model Archive Summary for Total Phosphorus at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396374,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix2.pdf","text":"Appendix 2","size":"788 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 2","linkHelpText":"—Model Archive Summary for Total Nitrogen at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"},{"id":396377,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5016/images"},{"id":396371,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5016/coverthb.jpg"},{"id":396372,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016.pdf","text":"Report","size":"3.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016"},{"id":396373,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5016/sir20225016_appendix1.pdf","text":"Appendix 1","size":"846 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5016 Appendix 1","linkHelpText":"—Model Archive Summary for Suspended Sediment at U.S. Geological Survey Station 06856600, Republican River at Clay Center, Kansas, during July 2018 through March 2021"}],"country":"United States","state":"Kansas","city":"Clay Center","otherGeospatial":"Republican River drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.8170166015625,\n 39.03838632847035\n ],\n [\n -96.767578125,\n 39.172658670429946\n ],\n [\n -96.866455078125,\n 39.35129035526705\n ],\n [\n -97.01202392578125,\n 39.5146359327835\n ],\n [\n -97.0147705078125,\n 39.65857056750545\n ],\n [\n -96.99829101562499,\n 39.76632525654491\n ],\n [\n -97.14385986328125,\n 39.87601941962116\n ],\n [\n -97.4102783203125,\n 39.8992015115692\n ],\n [\n -97.74810791015625,\n 39.905522539728544\n ],\n [\n -97.92938232421875,\n 39.90762941952987\n ],\n [\n -98.22601318359375,\n 39.78954439311165\n ],\n [\n -98.228759765625,\n 39.65222681530652\n ],\n [\n -97.83050537109375,\n 39.50615988027491\n ],\n [\n -97.51190185546874,\n 39.42346418978382\n ],\n [\n -97.2344970703125,\n 39.3130504637139\n ],\n [\n -96.98181152343749,\n 39.034119526392836\n ],\n [\n -96.84997558593749,\n 39.00211029922515\n ],\n [\n -96.8170166015625,\n 39.03838632847035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
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Lawrence, KS 66049
The Hydrate-01 Stratigraphic Test Well was drilled at the Kuparuk 7-11-12 site on the Alaska North Slope in December 2018. Sonic log data provide compressional (P) and shear (S) slowness from which we determine gas hydrate saturation (Sgh) estimates using effective medium theory. The sonic Sgh estimates compare favorably with Sgh estimated from resistivity and nuclear magnetic resonance (NMR) logs, showing that gas hydrate occupies up to approximately 90% of the pore space in the target reservoir sands. The informally named B1 sand (2294 feet below mean sea level) shows lower VP/VS ratios than the D1 sand (2770 feet below mean sea level), with the lower part of the B1 sand showing lower VP/VS ratios than the upper part of the B1 sand. This corresponds to a stiffer, or more “cemented”, behavior for the lower B1 sand and less cemented behavior for the D1 sand. This trend could be due to differences in the reservoirs themselves or in the gas hydrate morphology or to both factors. We observe that the presence of gas hydrate in the upper B1 sand has greater impact on hydraulic permeability (measurements suggest a greater difference between intrinsic and effective permeability) than in the D1 sand, possibly related to gas hydrate morphology but more likely due simply to higher gas hydrate saturations in the upper B1 sand. Analyses of Sgh relative to porosity, shale fraction, and intrinsic permeability show that reservoir quality (as represented by these three metrics) exerts control on gas hydrate saturation. Grain size and mineralogy data show somewhat smaller grains and better sorting in the D1 reservoir relative to the upper B1 reservoir and smaller grains and greater clay fraction in the lower B1 reservoir relative to the other two reservoir zones. Together, these data suggest that reservoir characteristics play a role in the observed VP/VS patterns, but gas hydrate morphology (possibly varying with saturation) must also be considered.
Per- and polyfluoroalkyl substances (PFAS) are contaminants of concern due to their widespread occurrence in the environment, persistence, and potential to elicit a range of negative health effects. Per- and polyfluoroalkyl substances are regularly detected in surface waters, but their effects on many aquatic organisms are still poorly understood. Species with thyroid-dependent development, like amphibians, can be especially susceptible to PFAS effects on thyroid hormone regulation. We examined sublethal effects of aquatic exposure to four commonly detected PFAS on larval northern leopard frogs (Rana [Lithobates] pipiens), American toads (Anaxyrus americanus), and eastern tiger salamanders (Ambystoma tigrinum). Animals were exposed for 30 days (frogs and salamanders) or until metamorphosis (toads) to 10, 100, or 1000 μg/L of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonate (PFHxS), or 6:2 fluorotelomer sulfonate (6:2 FTS). We determined that chronic exposure to common PFAS can negatively affect amphibian body condition and development at concentrations as low as 10 µg/L. These effects were highly species dependent, with species having prolonged larval development (frogs and salamanders) being more sensitive to PFAS than more rapidly developing species (toads). Our results demonstrate that some species could experience sublethal effects at sites with surface waters highly affected by PFAS. Our results also indicate that evaluating PFAS toxicity using a single species may not be sufficient for accurate amphibian risk assessment. Future studies are needed to determine whether these differences in susceptibility can be predicted from species' life histories and whether more commonly occurring environmental levels of PFAS could affect amphibians.
Scoping reviews, in which the literature on a given topic is systematically collated and summarized, aid literature searches and highlight knowledge gaps on a given topic, thus hastening scientific progress and informing conservation efforts. Because much research and conservation is targeted at the species level, ornithology and bird conservation would benefit from scoping reviews of individual species. We present and apply a framework for scoping reviews for three disparate raptor species: California Condor Gymnogyps californianus, Harpy Eagle Harpia harpyja and Gyrfalcon Falco rusticolus. We consulted expert panels to develop appropriate search strings and lists of essential literature, i.e. ‘benchmark articles’. We searched Web of Science, Scopus and Google Scholar. Searches for California Condor, Harpy Eagle and Gyrfalcon returned 268, 138 and 343 articles, respectively, that discuss, review or collect empirical data for the focal species. Our searches returned all benchmark articles identified by species experts, indicating that the searches captured the most important work on each species. We coded each study according to the topic addressed, country and month in which data were collected. We also coded threats, stresses and conservation actions addressed by studies, following definitions used by the International Union for the Conservation of Nature (IUCN) during Red List assessments. Literature summaries for each species include the number of studies addressing certain topics, monthly timing of research and global maps of research focus. Our coding scheme revealed important knowledge gaps for each species. Effects of conservation actions on wild individuals were less studied for California Condors. Harpy Eagles were less studied outside of Brazil and Panama, and Gyrfalcons were less studied outside of their breeding season. Scoping reviews of the world's bird species would help to identify critical knowledge gaps, thereby aiding the global effort to assuage the sixth mass extinction.
Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush (Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads (n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8508","usgsCitation":"Monroe, A., Nauman, T.W., Aldridge, C.L., O’Donnell, M.S., Duniway, M.C., Cade, B.S., Manier, D., and Anderson, P.J., 2022, Assessing vegetation recovery from energy development using a dynamic reference approach: Ecology and Evolution, v. 12, no. 2, p. 1-22, https://doi.org/10.1002/ece3.8508.","productDescription":"e8508, 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-129277","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448700,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8508","text":"Publisher Index Page"},{"id":435946,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OP5D76","text":"USGS data release","linkHelpText":"Sagebrush recovery analyzed with a dynamic reference approach in southwestern Wyoming, USA 1985-2018"},{"id":396353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.07177734375,\n 43.88205730390537\n ],\n [\n -111.016845703125,\n 41.02135510866602\n ],\n [\n -105.31494140625,\n 41.02135510866602\n ],\n [\n -109.281005859375,\n 43.874138181474734\n ],\n [\n -111.07177734375,\n 43.88205730390537\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Monroe, Adrian P. 0000-0003-0934-8225 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0000-0002-1105-1327","orcid":"https://orcid.org/0000-0002-1105-1327","contributorId":244206,"corporation":false,"usgs":true,"family":"Manier","given":"Daniel","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835676,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835677,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228826,"text":"70228826 - 2022 - Face-off: Novel depredation and nest defense behaviors between an invasive and a native predator in the Greater Everglades Ecosystem, Florida, USA","interactions":[],"lastModifiedDate":"2022-02-23T16:19:06.431573","indexId":"70228826","displayToPublicDate":"2022-02-23T10:11:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Face-off: Novel depredation and nest defense behaviors between an invasive and a native predator in the Greater Everglades Ecosystem, Florida, USA","docAbstract":"We describe several photo-documented novel interactions between intraguild predators in southern Florida—the native bobcat (Lynx rufus) and the invasive Burmese python (Python bivittatus). Over several days we documented a bobcat's depredation of an unguarded python nest and subsequent python nest defense behavior following the return of both animals to the nest. This is the first documentation of any animal in Florida preying on python eggs, and the first evidence or description of such antagonistic interactions at a python nest.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8639","usgsCitation":"Currylow, A.F., McCollister, M.F., Anderson, G.E., Josimovich, J.M., Fitzgerald, A.L., Romagosa, C.M., and Yackel Adams, A.A., 2022, Face-off: Novel depredation and nest defense behaviors between an invasive and a native predator in the Greater Everglades Ecosystem, Florida, USA: Ecology and Evolution, v. 12, no. 2, p. 1-6, https://doi.org/10.1002/ece3.8639.","productDescription":"e8639, 6 p.","startPage":"1","endPage":"6","ipdsId":"IP-134051","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":448702,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8639","text":"External Repository"},{"id":435947,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97ZDQHY","text":"USGS data release","linkHelpText":"Photo-documented sequences from 01 Jun 2021 - 30 Aug 2021 showing novel interactions between intraguild predators in southern Florida, USA, bobcat and Burmese python"},{"id":396350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.6336669921875,\n 24.472150437226865\n ],\n [\n -79.969482421875,\n 24.472150437226865\n ],\n [\n -79.969482421875,\n 27.27416111737468\n ],\n [\n -82.6336669921875,\n 27.27416111737468\n ],\n [\n -82.6336669921875,\n 24.472150437226865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCollister, Matthew F.","contributorId":264909,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew","email":"","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":835652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Josimovich, Jillian Maureen 0000-0002-7523-3496 jjosimovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7523-3496","contributorId":257058,"corporation":false,"usgs":true,"family":"Josimovich","given":"Jillian","email":"jjosimovich@usgs.gov","middleInitial":"Maureen","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Austin Lee 0000-0002-9016-1849","orcid":"https://orcid.org/0000-0002-9016-1849","contributorId":264910,"corporation":false,"usgs":true,"family":"Fitzgerald","given":"Austin","email":"","middleInitial":"Lee","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229800,"text":"70229800 - 2022 - Higher temperature sensitivity of flowering than leaf-out alters the time between phenophases across temperate tree species","interactions":[],"lastModifiedDate":"2022-04-12T14:04:44.422624","indexId":"70229800","displayToPublicDate":"2022-02-23T10:07:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Higher temperature sensitivity of flowering than leaf-out alters the time between phenophases across temperate tree species","docAbstract":"The aims of this study were to evaluate the changes in the length of the time period between leaf-out and flowering across temperate tree species, and associate these changes with potential physiological and environmental drivers to enhance mechanistic insight into these phenomena.
Central Europe.
1980–2016.
Six temperate woody species.
Statistical analyses were carried out based on long-term ground observations of both spring leaf-out and flowering across temperate tree species during 1980–2016, a period characterized by rapid warming.
The temperature sensitivity of flowering (−5.4 ± 0.04 days/℃, mean ± SE) was higher than that of leaf-out (−4.6 ± 0.04 days/℃) across all species, regardless of whether leaf-out occurred before or after flowering. This study postulates a hypothesis attributing the different temperature sensitivities to different thermal sensitivities, thermal requirements, and photoperiodic controls.
The larger temperature sensitivity of flowering than leaf-out resulted in an extended time period between flowering and leaf-out in species that bloom before leafing out, but a shorter time period between these phenophases in species with the opposite strategy. We would like to emphasize the importance of changes in time period between different phenophases, and we recommend conducting experimental research to reveal the underlying mechanisms of plant phenology response to climate change, and to explore its potential ecological implications.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13463","usgsCitation":"Geng, X., Fu, Y., Piao, S., Hao, F., De Boeck, H.J., Zhang, X., Chen, S., Guo, Y., Prevey, J.S., Vitasse, Y., Penuelas, J., Janssens, I.A., and Stenseth, N.C., 2022, Higher temperature sensitivity of flowering than leaf-out alters the time between phenophases across temperate tree species: Global Ecology and Biogeography, v. 31, no. 5, p. 901-911, https://doi.org/10.1111/geb.13463.","productDescription":"11 p.","startPage":"901","endPage":"911","ipdsId":"IP-120459","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":448703,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A30003","text":"External Repository"},{"id":397239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Austria, Croatia, Germany, Montenegro, Slovenia, Switzerland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[16.97967,48.1235],[16.90375,47.71487],[16.34058,47.7129],[16.53427,47.49617],[16.2023,46.85239],[16.3705,46.84133],[16.56481,46.50375],[16.88252,46.38063],[17.63007,45.95177],[18.45606,45.75948],[18.82984,45.90888],[19.07277,45.52151],[19.39048,45.23652],[19.00549,44.86023],[18.55321,45.08159],[17.86178,45.06774],[17.00215,45.23378],[16.53494,45.21161],[16.31816,45.00413],[15.95937,45.23378],[15.75003,44.81871],[16.23966,44.35114],[16.45644,44.04124],[16.91616,43.66772],[17.29737,43.44634],[17.67492,43.02856],[18.56,42.65],[18.70648,43.20011],[19.03165,43.43253],[19.21852,43.52384],[19.48389,43.35229],[19.63,43.21378],[19.95857,43.10604],[20.3398,42.89852],[20.25758,42.81275],[20.0707,42.58863],[19.80161,42.50009],[19.73805,42.68825],[19.30449,42.19574],[19.37177,41.87755],[19.16246,41.95502],[18.88214,42.28151],[18.45002040576871,42.479990627248036],[18.45002,42.47999],[17.50997,42.84999],[16.93001,43.21],[16.01538,43.50722],[15.17445,44.24319],[15.37625,44.31792],[14.92031,44.73848],[14.9016,45.07606],[14.25875,45.23378],[13.95225,44.80212],[13.65698,45.13694],[13.6794,45.48415],[13.71506,45.50032],[13.93763,45.59102],[13.69811,46.01678],[13.80648,46.50931],[12.37649,46.76756],[12.15309,47.11539],[11.16483,46.94158],[11.04856,46.75136],[10.4427,46.89355],[10.36338,46.48357],[9.92284,46.3149],[9.18288,46.44021],[8.96631,46.03693],[8.48995,46.00515],[8.31663,46.16364],[7.75599,45.82449],[7.27385,45.77695],[6.84359,45.99115],[6.5001,46.42967],[6.02261,46.27299],[6.03739,46.72578],[6.76871,47.28771],[6.73657,47.5418],[7.1922,47.44977],[7.46676,47.62058],[7.59368,48.33302],[8.09928,49.01778],[6.65823,49.20196],[6.18632,49.4638],[6.24275,49.90223],[6.04307,50.12805],[6.15666,50.80372],[5.98866,51.85162],[6.5894,51.85203],[6.84287,52.22844],[7.09205,53.14404],[6.90514,53.48216],[7.10042,53.69393],[7.93624,53.7483],[8.12171,53.52779],[8.80073,54.02079],[8.57212,54.39565],[8.52623,54.96274],[9.28205,54.83087],[9.92191,54.9831],[9.93958,54.59664],[10.95011,54.36361],[10.93947,54.00869],[11.95625,54.19649],[12.51844,54.47037],[13.64747,54.07551],[14.11969,53.75703],[14.35332,53.24817],[14.07452,52.98126],[14.4376,52.62485],[14.68503,52.08995],[14.6071,51.74519],[15.017,51.10667],[14.57072,51.00234],[14.30701,51.11727],[14.05623,50.92692],[13.33813,50.73323],[12.96684,50.48408],[12.24011,50.26634],[12.41519,49.96912],[12.52102,49.54742],[13.03133,49.30707],[13.59595,48.87717],[14.3389,48.55531],[14.90145,48.9644],[15.25342,49.03907],[16.02965,48.7339],[16.49928,48.78581],[16.96029,48.59698],[16.87998,48.47001],[16.97967,48.1235]]]},\"properties\":{\"name\":\"Austria\"}}]}","volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Geng, 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