West Indian manatees (Trichechus manatus) are separated into two allopatric subspecies: the Florida manatee (T. m. latirostris) and the Antillean manatee (T. m. manatus). In the winter of 2020–2021, an adult manatee was sighted off the coast of Cancun, Quintana Roo, Mexico, in areas where Antillean manatees are not typically seen. The individual had distinct watercraft scars on its body, which were matched using photo-identification to a known male Florida manatee (PE424) that had been repeatedly photographed in Florida since 1998. This is the first record of a Florida manatee visiting the Mexican Caribbean. Previous reports of individuals from this subspecies in Cuba, combined with genetic evidence, suggest some level of connectivity among geographically separated manatee populations.
We present the first evidence of along-distance movement by amanatee from Florida to the Yucatan Peninsula (Quintana Roo, Mexican Caribbean).
This case, previous reports of Florida manatees in Cuba, and genetic evidence, suggest acertain degree of genetic mixture among the two subspecies.
Vernal pools of the northeastern United States provide important breeding habitat for amphibians but may be sensitive to droughts and climate change. These seasonal wetlands typically fill by early spring and dry by mid-to-late summer. Because climate change may produce earlier and stronger growing-season evapotranspiration combined with increasing droughts and shifts in precipitation timing, management concerns include the possibility that some pools will increasingly become dry earlier in the year, potentially interfering with amphibian life-cycle completion. In this context, a subset of pools that continue to provide wetland habitat later into the year under relatively dry conditions might function as ecohydrologic refugia, potentially supporting species persistence even as summer conditions become warmer and droughts more frequent. We used approximately 3,000 field observations of inundation from 449 pools to train machine-learning models that predict the likelihood of pool inundation based on pool size, day of the year, climate conditions, short-term weather patterns, and soil, geologic, and landcover attributes. Models were then used to generate predictions of pool wetness across five seasonal time points, three short-term weather scenarios, and four sets of downscaled climate projections. Model outputs are available through a website allowing users to choose the inundation thresholds, time points, weather scenarios, and future climate projections most relevant to their management needs. Together with long-term monitoring of individual pools at the site scale, this regional-scale study can support amphibian conservation by helping to identify which pools may be most likely to function as ecohydrologic refugia from droughts and climate change.
The 2019
Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.
Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (
Subsidence and accelerated sea level rise impact nesting area availability and flood probabilities of breeding islands for colonial nesting waterbirds. In 2017 and 2018, we monitored 855 nests of four species of colonial nesting waterbirds on Rabbit Island, LA, to determine factors affecting nest and chick success. Based on logistic exposure models of nests, tricolored herons had the greatest likelihood of survival to hatch (mean (95% confidence interval)) (77% (65.9–83.1%)), followed by brown pelicans (70% (59.9–98.5%)), roseate spoonbills (70% (38.9–83.8%)), and Forster’s terns (12% (10.7–12.2%)). Likelihood of survival to fledge was highest for tricolored herons (32% (12.8–40.7%)), followed by brown pelicans (28% (19.5–28.6%)), roseate spoonbills (47% (43.7–53.3%)), and Forster’s terns (0% (0.005–0.01%)). Nesting strategy and nest timing impacted survival rate; however, the effect depended on timing of inundation events as the timing of inundation events varied across years. Flooding was the primary cause of nest failure for most species. In 2003–2012, rapid expansion in brown pelican colony numbers and significant chick production occurred at Rabbit Island, but hydrologic records indicate no island inundation occurred during the breeding season from the beginning of the hydrologic record (2006) through 2011. Thus, our results contrast with those of previous studies conducted under different hydrologic conditions and demonstrate the challenges of short-term studies informing coastal restoration in a system that is influenced by multi-year to multi-decadal climatic cycles.
Earthquake hazards in the U.S. Pacific Northwest (PNW) are increased by the presence of deep sedimentary basins that amplify and prolong ground shaking. To better understand basin and site effects on ground motions, we compile a database of recordings from crustal and intraslab earthquakes. We process 8028 records with magnitudes from 3.5 to 6.8 and hypocentral depths up to 62 km to compute Fourier amplitude spectra of ground acceleration for frequencies of 0–20 Hz. We compute residuals relative to the Bayless and Abrahamson (2019; hereafter, BA18) ground‐motion model and perform a series of linear, crossed, mixed‐effects regressions. In addition to estimating the bias, event, and site terms, we incorporate groupings for broad regionalized site response in three different regions (Seattle basin, Puget Lowland, non‐Puget Lowland), for effects from seismotectonic regime (crustal and intraslab sources), and for interactions between the regions and seismotectonic regimes. We find that the scaling of site response with respect to VS30 (time‐averaged shear‐wave velocity from the surface to a depth of 30 m) and to basin depth indicators Z1.0 and Z2.5 (depths to the 1.0 and 2.5 km/s shear‐wave velocity horizons) is generally consistent with BA18; however, the region terms display strong spatial amplification patterns. For frequencies less than 5 Hz, the Seattle basin amplifies ground motions up to a factor of four, relative to the non‐Puget Lowland, with a maximum amplification around near 0.5 Hz. Sites in the Puget Lowland amplify low frequencies up to a factor of 2.5. At higher frequencies (f>5 Hz), the Puget Lowland and Seattle basin show regional deamplification of ground motions, with the smallest average amplification factor of 0.65 occurring at 10.0 Hz. Although we observe slight differences in the seismotectonic regime terms, we find that the region terms are significantly more important for modeling earthquake hazard in the PNW.
Regional scale forest distribution models are important tools for biogeography and understanding the structure of forest communities in space. These models take climate and geographic variables as input and are therefore helpful for long-term decision support and climate adaptation planning. Generally, local processes of tree germination and seedling survival are resolved probabilistically with explanatory variables such as elevation, latitude, exposure, soil type, moisture availability, climate and weather inputs and `trained’ using landscape and regional presence-absence data and machine learning techniques. How seeds are distributed in these models, that is, determining the dispersal kernel, is far more problematic. The challenge is that variables conditioning vertebrate seed dispersal (motility and probability of utilization or caching in response to cover type) are not represented in large scale distribution models, and in fact vary on scales (10-100 meters) that are much smaller than the smallest pixel size for the distribution model (1-10 kilometers). We present a homogenized seed digestion kernel (HSDK) which incorporates this scale separation. Homogenization naturally links highly variable small-scale processes (like seed foraging and caching by birds and rodents) with large scale effects (like dispersal of seeds over tens of kilometers). We develop a homogenization strategy to predict seed dispersal on landscape scales, analytically linking small-scale variables (landscape fraction cover by tree type, gut residence times and cover type utilization by frugivorous birds) with large scale behaviors. Closed form approximations are developed in two dimensions for two limiting cases of seed handling behavior, and the approach is illustrated using landscape data and piñon-pine dispersal in a 630,000 square kilometer region in the southwestern US.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.amc.2021.126591","usgsCitation":"Neupane, R.C., Powell, J., and Edwards, T., 2022, Connecting regional-scale tree distribution models with seed dispersal kernels: Applied Mathematics and Computation, v. 412, 126591, 17 p., https://doi.org/10.1016/j.amc.2021.126591.","productDescription":"126591, 17 p.","ipdsId":"IP-124972","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.amc.2021.126591","text":"Publisher Index Page"},{"id":396921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Neupane, Ram C.","contributorId":288149,"corporation":false,"usgs":false,"family":"Neupane","given":"Ram","email":"","middleInitial":"C.","affiliations":[{"id":61709,"text":"ta&m","active":true,"usgs":false}],"preferred":false,"id":837519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, James A.","contributorId":288150,"corporation":false,"usgs":false,"family":"Powell","given":"James A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":837520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":837518,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224338,"text":"70224338 - 2022 - Solutions in microbiome engineering: Prioritizing barriers to organism establishment","interactions":[],"lastModifiedDate":"2022-01-25T16:50:53.459975","indexId":"70224338","displayToPublicDate":"2021-08-21T07:11:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9357,"text":"The ISME Journal: Multidisciplinary Journal of Microbial Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Solutions in microbiome engineering: Prioritizing barriers to organism establishment","docAbstract":"Microbiome engineering is increasingly being employed as a solution to challenges in health, agriculture, and climate. Often manipulation involves inoculation of new microbes designed to improve function into a preexisting microbial community. Despite, increased efforts in microbiome engineering inoculants frequently fail to establish and/or confer long-lasting modifications on ecosystem function. We posit that one underlying cause of these shortfalls is the failure to consider barriers to organism establishment. This is a key challenge and focus of macroecology research, specifically invasion biology and restoration ecology. We adopt a framework from invasion biology that summarizes establishment barriers in three categories: (1) propagule pressure, (2) environmental filtering, and (3) biotic interactions factors. We suggest that biotic interactions is the most neglected factor in microbiome engineering research, and we recommend a number of actions to accelerate engineering solutions.
Two related concepts in restoration ecology include the relative interchangeability of biotic and abiotic restoration treatments for initiating recovery and bet hedging using multiple restoration approaches to increase the likelihood of favorable restoration outcomes. We used these concepts as a framework to implement a factorial experiment including biotic (outplanting greenhouse-grown individuals of three perennial species) and abiotic treatments (constructing microtopography or vertical mulch consisting of upright, dead plant material). These treatments were designed to stimulate native plant recruitment and reverse soil degradation at four disturbed sites in the Sonoran Desert, U.S.A. The first growing season after the restoration treatments was the driest of the last 47 years, and 100% of outplants died. While the biotic treatment failed, the vertical mulch abiotic treatment increased native shrub seedling cover at the driest site and reversed soil loss across sites by increasing soil accumulation by 6× to 2 cm/year. Results revealed that (1) inexpensive, minimal-input abiotic treatments outperformed resource-intensive biotic treatments; (2) the restoration effort withstood the total failure of a major component (outplanting) to nevertheless achieve key restoration benefits within 2–3 growing seasons; and (3) incorporating multiple treatment types served as a bet-hedging approach to buffer against treatment failures. Integrating minimal-input abiotic treatments in restoration warrants consideration given their low cost and bet-hedging potential.
Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.
We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability
Lakes process both terrestrial and aquatic organic matter, and the relative contribution from each source is often measured via ecosystem metabolism and terrestrial resource use in the food web (i.e., consumer allochthony). Yet, ecosystem metabolism and consumer allochthony are rarely considered together, despite possible interactions and potential for them to respond to the same lake characteristics. In this study, we compiled global datasets of lake gross primary production (GPP), ecosystem respiration (ER), and zooplankton allochthony to compare the strength and shape of relationships with physicochemical characteristics across a broad set of lakes. GPP was positively related to total phosphorus (TP) in lakes with intermediate TP concentrations (11–75 μg L−1) and was highest in lakes with intermediate dissolved organic carbon (DOC) concentrations. While ER and GPP were strongly positively correlated, decoupling occurred at high DOC concentrations. Lastly, allochthony had a unimodal relationship with TP and related variably to DOC. By integrating metabolism and allochthony, we identified similar change points in GPP and zooplankton allochthony at intermediate DOC (4.5–10 mg L−1) and TP (8–20 μg L−1) concentrations, indicating that allochthony and GPP may be coupled and inversely related. The ratio of DOC:nutrients also helped to identify conditions where lake organic matter processing responded more to autochthonous or allochthonous organic matter sources. As lakes globally face eutrophication and browning, predicting how lake organic matter processing will respond requires an updated paradigm that incorporates nonlinear dynamics and interactions.
The Prairie Pothole Region (PPR) of North America has experienced extreme changes in wetland habitat due to proliferation of invasive plants. Typha × glauca is a highly competitive hybrid between native T. latifolia and non-native T. angustifolia, and it is likely the predominant taxon in PPR wetlands. Genetics-based studies are limited, and distributions are poorly known for the first-generation (F1) hybrid and advanced-generation hybrids from F1 mating. Information pertaining to the distribution of T. × glauca could benefit efforts to understand the mechanisms of its spread and to develop management strategies to limit hybrid expansion and preserve progenitors. We used microsatellite markers of field-collected tissue samples from 131 wetlands spread over approximately 350,000 km2 in the PPR to assess the distribution of hybrid T. × glauca relative to its parental species and to examine the prevalence of F1 hybrids and advanced-generation hybrids. Typha × glauca was found in over 80% of wetlands throughout the PPR, compared to 26 and 18% of wetlands with T. latifolia and T. angustifolia, respectively. Advanced-generation hybrids were more common than F1 hybrids, suggesting that hybridization is not a recent phenomenon. Hybrids were significantly taller than T. latifolia, indicating heterosis. Only 7% of sampled individual genets were pure T. latifolia. These results suggest that T. × glauca is pervasive throughout the PPR and may spread independently of both parents. In addition, limited prevalence of native T. latifolia indicates the need for active management to preserve the species.
Imidacloprid is among the most used pesticides worldwide and there are toxicity concerns for nontarget organisms. Accurate and sensitive methods are necessary to quantitate imidacloprid concentrations in biological matrices to better understand their fate and effects. Here we evaluated an enzyme-linked immunosorbent assay (ELISA) kit for the analysis of imidacloprid in biological samples. Following the dosing of Japanese quail (Coturnix japonica) with imidacloprid-treated wheat seeds, plasma, liver, and fecal matter samples were analyzed by ELISA and compared to previous analyses that employed liquid chromatography-tandem mass spectrometry (LC-MS/MS). Imidacloprid metabolites—5-OH-imidacloprid, imidacloprid-olefin, imidacloprid-urea, desnitro-imidacloprid, and 6-chloronicotinic acid—were tested for their cross-reactivity to antibodies within the commercial imidacloprid ELISA kit. The two major metabolites, 5-OH-imidacloprid and imidacloprid-olefin, showed cross-reactivities of 0.93–26 %. ELISA and LC-MS/MS results were positively correlated but there was poor agreement in concentrations: plasma and fecal matter imidacloprid concentrations were higher by ELISA, whereas liver imidacloprid concentrations were higher by LC-MS/MS. Matrix interferences observed in analyses were minimized by the application of matrix-matched calibration curves. ELISA provided an effective screening tool for imidacloprid in these biological matrices, but the presence of cross-reactants confounded results. Confirmation of ELISA results by more selective techniques (e.g., LC-MS/MS) is suggested for complex samples.
Indoor air pollution is associated with adverse health effects; however, few studies exist studying indoor air pollution on the Navajo Nation in the southwest U.S., a community with high rates of respiratory disease.
Indoor PM2.5 concentration was evaluated in 26 homes on the Navajo Nation using real-time PM2.5 monitors. Household risk factors and daily activities were evaluated with three metrics of indoor PM2.5: time-weighted average (TWA), 90th percentile of concentration, and daily minutes exceeding 100 μg/m3. A questionnaire and recall sheet were used to record baseline household characteristics and daily activities.
The median TWA, 90th percentile, and daily minutes exceeding 100 μg/m3 were 7.9 μg/m3, 14.0 μg/m3, and 17 min, respectively. TWAs tended to be higher in autumn and in houses that used fuel the previous day. Other characteristics associated with elevated PM exposure in all metrics included overcrowded houses, nonmobile houses, and houses with current smokers, pets, and longer cooking time.
Some residents of the Navajo Nation have higher risk of exposure to indoor air pollution by Environmental Protection Agency (EPA) standards. Efforts to identify the causes and associations with adverse health effects are needed to ensure that exposure to risks and possible health impacts are mitigated.
Effects of climate change-driven disturbance on lake ecosystems can be subtle; indirect effects include increased nutrient loading that could impact ecosystem function. We designed a low-level fertilization experiment to mimic persistent, climate change-driven disturbances (deeper thaw, greater weathering, or thermokarst failure) delivering nutrients to arctic lakes. We measured responses of pelagic trophic levels over 12 yr in a fertilized deep lake with fish and a shallow fishless lake, compared to paired reference lakes, and monitored recovery for 6 yr. Relative to prefertilization in the deep lake, we observed a maximum pelagic response in chl a (+201%), dissolved oxygen (DO, −43%), and zooplankton biomass (+88%) during the fertilization period (2001–2012). Other responses to fertilization, such as water transparency and fish relative abundance, were delayed, but both ultimately declined. Phyto- and zooplankton biomass and community composition shifted with fertilization. The effects of fertilization were less pronounced in the paired shallow lakes, because of a natural thermokarst failure likely impacting the reference lake. In the deep lake there was (a) moderate resistance to change in ecosystem functions at all trophic levels, (b) eventual responses were often nonlinear, and (c) postfertilization recovery (return) times were most rapid at the base of the food web (2–4 yr) while higher trophic levels failed to recover after 6 yr. The timing and magnitude of responses to fertilization in these arctic lakes were similar to responses in other lakes, suggesting indirect effects of climate change that modify nutrient inputs may affect many lakes in the future.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11893","usgsCitation":"Budy, P., Pennock, C., Giblin, A.E., Luecke, C., White, D.L., and Kling, G., 2022, Understanding the effects of climate change via disturbance on pristine arctic lakes — Multitrophic level response and recovery to a 12-yr, low-level fertilization experiment: Limnology and Oceanography, v. 67, no. S1, p. S224-S241, https://doi.org/10.1002/lno.11893.","productDescription":"18 p.","startPage":"S224","endPage":"S241","ipdsId":"IP-129828","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11893","text":"Publisher Index Page"},{"id":397154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Toolik Field Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.8642578125,\n 68.24089575900885\n ],\n [\n -148.73291015625,\n 68.24089575900885\n ],\n [\n -148.73291015625,\n 68.87143872335129\n ],\n [\n -150.8642578125,\n 68.87143872335129\n ],\n [\n -150.8642578125,\n 68.24089575900885\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"S1","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":838020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giblin, Anne E.","contributorId":103966,"corporation":false,"usgs":true,"family":"Giblin","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":838021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luecke, Chris","contributorId":239659,"corporation":false,"usgs":false,"family":"Luecke","given":"Chris","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":838022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, D. L.","contributorId":288498,"corporation":false,"usgs":false,"family":"White","given":"D.","email":"","middleInitial":"L.","affiliations":[{"id":61777,"text":"wh","active":true,"usgs":false}],"preferred":false,"id":838023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kling, George","contributorId":120446,"corporation":false,"usgs":true,"family":"Kling","given":"George","email":"","affiliations":[],"preferred":false,"id":838024,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226472,"text":"70226472 - 2022 - Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada","interactions":[],"lastModifiedDate":"2022-05-13T14:33:49.961069","indexId":"70226472","displayToPublicDate":"2021-08-02T07:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada","docAbstract":"Tectonic interpretation of the central Sierra Nevada—whether the crest of the Sierra Nevada (California, USA) was uplifted in the late Cenozoic or whether the range has undergone continuous down-wearing since the Late Cretaceous—is controversial, since there is no obvious tectonic explanation for renewed uplift. The strongest direct evidence for late Cenozoic uplift of the central Sierra Nevada comes from study of the Trachyandesite of Kennedy Table, which followed the course of the Miocene San Joaquin River but has a steeper gradient than the modern river. Early workers attributed this steeper gradient to tilting of the Sierra Nevada block since the late Miocene, resulting in 2 km of range-crest uplift. However, this interpretation has been contested on grounds that the Miocene river gradient had to be assumed and that the Sierran Batholith could have warped during tilting, thus failing to uplift the range crest. The objective of this study was to obtain quantitative data that test these criticisms.
The Trachyandesite of Kennedy Table is a chain of 33 remnants of a single lava flow as thick as 65 m, preserved for 21 km from Squaw Leap to Little Dry Creek, close to the modern San Joaquin River in the foothills of the Sierra Nevada. Several remnants lie on fluvial gravel of the late Miocene San Joaquin River. Early workers speculated that the lava concealed its own (unrecognized) vent, but in 2011, we identified the vent on the Middle Fork of the San Joaquin River, 13.5 km south of Deadman Pass and 70 km northeast of Kennedy Table. The vent complex intrudes Cretaceous granite, has 285 m relief, and is an intricately jointed intrusion that grades up into a glassy lava flow. Composition (58% SiO2) and 40Ar/39Ar age (9.3 Ma) are identical at the vent and downstream. Basal elevations of remnants were recorded, and the present-day basal gradients of several were adjusted for apparent dip and projected along a vertical plane at 220° (the estimated tilt azimuth). The basal gradients are far steeper than that of the modern river, but they differ slightly from reach to reach and are thus inconsistent measures of the post-Miocene tilt. Likewise, relief eroded atop most remnants renders modeling of upper surfaces suspect. At Little Dry Creek, however, a chain of nine remnants rests on fluvial floodplain sand and gravel; this chain trends 230°, and its smooth basal contact now dips 1.36° (adjusted at 220°). Projection of this dip 89 km from the 207 m base of the most distal remnant at Little Dry Creek to the vent intrusion falls far below the 2760 m intrusion-to-lava-flow transition near the Sierran crest, showing that the Sierran block has not undergone pronounced convex warping. Using elevation data on paleoriver meanders preserved by the lava flow, we show that the paleogradient has a cosine dependence on meander-section azimuth, indicating tilting. Subtraction of 1.07° of dip restores the data to an azimuth-independent configuration, indicating total tilting since 9.3 Ma of 1.07° and an original large-scale gradient of 0.46°, similar to the published value of 0.33° at Squaw Leap, but larger than the previously obtained value of 0.057° at Little Dry Creek. Subtraction of those Miocene estimates from the observable 1.643° tilt along the section from Little Dry Creek to the vent yields vent uplift of 2464 m (for 0.057°), 1835 m (for 0.46°), and 2040 m (for 0.33°). Confirmation of earlier assumptions regarding Miocene river gradient and block rigidity greatly strengthens the case for ∼2 km of late Cenozoic uplift of the central Sierra Nevada crest.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36125.1","usgsCitation":"Hildreth, E., Fierstein, J., Phillips, F., and Calvert, A.T., 2022, Trachyandesite of Kennedy Table, its vent complex, and post−9.3 Ma uplift of the central Sierra Nevada: GSA Bulletin, v. 134, no. 5-6, p. 1143-1159, https://doi.org/10.1130/B36125.1.","productDescription":"17 p.","startPage":"1143","endPage":"1159","ipdsId":"IP-130343","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449767,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36125.1","text":"Publisher Index Page"},{"id":391916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 37\n ],\n [\n -119,\n 37\n ],\n [\n -119,\n 37.75\n ],\n [\n -120,\n 37.75\n ],\n [\n -120,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2021-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Edward 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":146999,"corporation":false,"usgs":true,"family":"Hildreth","given":"Edward","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Fred M.","contributorId":269402,"corporation":false,"usgs":false,"family":"Phillips","given":"Fred M.","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":827034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240891,"text":"70240891 - 2022 - Potential role for microbial ureolysis in the rapid formation of carbonate tufa mounds","interactions":[],"lastModifiedDate":"2023-02-28T12:41:34.192522","indexId":"70240891","displayToPublicDate":"2021-08-02T06:38:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1751,"text":"Geobiology","active":true,"publicationSubtype":{"id":10}},"title":"Potential role for microbial ureolysis in the rapid formation of carbonate tufa mounds","docAbstract":"Modern carbonate tufa towers in the alkaline (~pH 9.5) Big Soda Lake (BSL), Nevada, exhibit rapid precipitation rates (exceeding 3 cm/year) and host diverse microbial communities. Geochemical indicators reveal that carbonate precipitation is, in part, promoted by the mixing of calcium-rich groundwater and carbonate-rich lake water, such that a microbial role for carbonate precipitation is unknown. Here, we characterize the BSL microbial communities and evaluate their potential effects on carbonate precipitation that may influence fast carbonate precipitation rates of the active tufa mounds of BSL. Small subunit rRNA gene surveys indicate a diverse microbial community living endolithically, in interior voids, and on tufa surfaces. Metagenomic DNA sequencing shows that genes associated with metabolisms that are capable of increasing carbonate saturation (e.g., photosynthesis, ureolysis, and bicarbonate transport) are abundant. Enzyme activity assays revealed that urease and carbonic anhydrase, two microbial enzymes that promote carbonate precipitation, are active in situ in BSL tufa biofilms, and urease also increased calcium carbonate precipitation rates in laboratory incubation analyses. We propose that, although BSL tufas form partially as a result of water mixing, tufa-inhabiting microbiota promote rapid carbonate authigenesis via ureolysis, and potentially via bicarbonate dehydration and CO2 outgassing by carbonic anhydrase. Microbially induced calcium carbonate precipitation in BSL tufas may generate signatures preserved in the carbonate microfabric, such as stromatolitic layers, which could serve as models for developing potential biosignatures on Earth and elsewhere.
Predation on anadromous salmon can have important consequences for both predators and prey. Salmon provide large seasonal pulses of energy and nutrients via carcasses, eggs and juveniles to many freshwater consumers, and conversely, predation can represent a significant source of mortality for juvenile salmon. Recent declines of Chinook salmon (Oncorhynchus tshawytscha) populations in Alaska have raised concern that predation might inhibit their recovery. Here, we quantify patterns of predation by freshwater fishes on juvenile salmon across seasons, habitats, predator sizes and streamflow levels in the Arctic-Yukon-Kuskokwim region of Alaska. We analysed piscivore stomach contents and identified prey using DNA sequence “barcoding.” In coastal rivers, juvenile pink (O. gorbuscha) and chum (O. keta) salmon contributed heavily to Arctic grayling (Thymallus arcticus) and Dolly Varden char (Salvelinus malma) diets, coho salmon (O. kisutch) prey were rare, and Chinook salmon were not detected. In interior rivers, Arctic grayling, burbot (Lota lota) and northern pike (Esox lucius) consumed small numbers of Chinook salmon. Predation on Chinook salmon was documented disproportionately in sloughs during a summer of exceptionally high streamflow. Dietary and distributional patterns suggested northern pike and burbot may exclude salmon from sloughs in low-gradient river reaches that would otherwise provide suitable rearing habitat. The data also provided tentative support for the hypothesis that high streamflow induces juvenile Chinook salmon to move from mainstem habitats into sloughs, where they face an increased risk of mortality. Incorporating predation risk into climate adaptation, fisheries management and habitat restoration decisions may help to facilitate Chinook salmon recovery.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12626","usgsCitation":"Erik R. Schoen, Kristen W. Sellmer, Wipfli, M.S., López, J., Meyer, B.E., and Ivanoff, R., 2022, Piscine predation on juvenile salmon in sub-arctic Alaskan rivers: Associations with season, habitat, predator size and streamflow: Ecology of Freshwater Fish, v. 31, no. 2, p. 243-259, https://doi.org/10.1111/eff.12626.","productDescription":"17 p.","startPage":"243","endPage":"259","ipdsId":"IP-127178","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485711,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic-Yukon-Kuskokwim region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -141.10147646297003,\n 68.3449468703235\n ],\n [\n -156.9154253909846,\n 67.08522178303117\n ],\n [\n -160.57755346633166,\n 65.7946938791593\n ],\n [\n -167.68091025059113,\n 65.37438160750091\n ],\n [\n -166.02578339933964,\n 64.5871850291825\n ],\n [\n -161.57951338791028,\n 63.97208503621405\n ],\n [\n -164.3166616652914,\n 63.224393208662505\n ],\n [\n -166.79494731479465,\n 61.465571001059644\n ],\n [\n -163.41623031807688,\n 58.92141056825929\n ],\n [\n -152.74292030658648,\n 61.19555667367189\n ],\n [\n -147.87124146516078,\n 63.43635278597176\n ],\n [\n -144.46134619105635,\n 63.1032486591549\n ],\n [\n -141.13828573559508,\n 62.46536178017422\n ],\n [\n -141.10147646297003,\n 68.3449468703235\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Erik R. Schoen","contributorId":354925,"corporation":false,"usgs":false,"family":"Erik R. Schoen","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":936654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kristen W. Sellmer","contributorId":354927,"corporation":false,"usgs":false,"family":"Kristen W. Sellmer","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":936655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"López, Juan A.","contributorId":354929,"corporation":false,"usgs":false,"family":"López","given":"Juan A.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":936656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Benjamin E.","contributorId":200050,"corporation":false,"usgs":false,"family":"Meyer","given":"Benjamin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":936658,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ivanoff, Renae","contributorId":264889,"corporation":false,"usgs":false,"family":"Ivanoff","given":"Renae","affiliations":[{"id":54574,"text":"norton sound","active":true,"usgs":false}],"preferred":false,"id":936657,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222547,"text":"70222547 - 2022 - Modeling morphodynamics of coastal response to extreme events: What shape are we in?","interactions":[],"lastModifiedDate":"2022-01-25T16:45:04.659973","indexId":"70222547","displayToPublicDate":"2021-07-27T07:03:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":811,"text":"Annual Review of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling morphodynamics of coastal response to extreme events: What shape are we in?","docAbstract":"This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash, collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-marine-032221-090215","usgsCitation":"Sherwood, C.R., van Dongeren, A., Doyle, J., Hegermiller, C., Hsu, T.J., Kalra, T., Olabarrieta, M., Penko, A., Rafati, Y., Roelvink, D., van der Lugt, M., Veeramony, J., and Warner, J.C., 2022, Modeling morphodynamics of coastal response to extreme events: What shape are we in?: Annual Review of Marine Science, v. 14, p. 457-492, https://doi.org/10.1146/annurev-marine-032221-090215.","productDescription":"36 p.","startPage":"457","endPage":"492","ipdsId":"IP-126726","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449771,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/29021","text":"External Repository"},{"id":387676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":820521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doyle, James","contributorId":261741,"corporation":false,"usgs":false,"family":"Doyle","given":"James","affiliations":[{"id":52981,"text":"U.S. Naval Research Laboratory, Monterey, C","active":true,"usgs":false}],"preferred":false,"id":820522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christie 0000-0002-6383-7508 chegermiller@usgs.gov","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":149010,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","email":"chegermiller@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsu, T. J.","contributorId":261742,"corporation":false,"usgs":false,"family":"Hsu","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":52981,"text":"U.S. Naval Research Laboratory, Monterey, C","active":true,"usgs":false}],"preferred":false,"id":820524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":820544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":820526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Penko, Allison","contributorId":191932,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","affiliations":[],"preferred":false,"id":820527,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rafati, Yashar","contributorId":223049,"corporation":false,"usgs":false,"family":"Rafati","given":"Yashar","email":"","affiliations":[],"preferred":false,"id":820528,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roelvink, Dano","contributorId":139950,"corporation":false,"usgs":false,"family":"Roelvink","given":"Dano","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":820529,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van der Lugt, Marlies","contributorId":221148,"corporation":false,"usgs":false,"family":"van der Lugt","given":"Marlies","email":"","affiliations":[{"id":40335,"text":"Detlares","active":true,"usgs":false}],"preferred":false,"id":820530,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Veeramony, Jay","contributorId":261743,"corporation":false,"usgs":false,"family":"Veeramony","given":"Jay","email":"","affiliations":[{"id":52984,"text":"U.S. Naval Research Laboratory, Stennis Space Center, MS","active":true,"usgs":false}],"preferred":false,"id":820531,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820532,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ]}