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USGS2021

Fatty acid profiles of feeding and fasting bears: Estimating calibration coefficients, the timeframe of diet estimates, and selective mobilization during hibernation

Accurate information on diet composition is central to understanding and conserving carnivore populations. Quantitative fatty acid signature analysis (QFASA) has emerged as a powerful tool for estimating the diets of predators, but ambiguities remain about the timeframe of QFASA estimates and the need to account for species-specific patterns of metabolism. We conducted a series of feeding experiments with four juvenile male brown bears ( Ursus arctos ) to (1) track the timing of changes in adipose tissue composition and QFASA diet estimates in response to a change in diet and (2) quantify the relationship between consumer and diet FA composition (i.e., determine “calibration coefficients”). Bears were fed three compositionally distinct diets for 90–120 days each. Two marine-based diets were intended to approximate the lipid content and composition of the wild diet of polar bears ( U. maritimus ). Bear adipose tissue composition changed quickly in the direction of the diet and showed evidence of stabilization after 60 days. During hibernation, FA profiles were initially stable but diet estimates after 10 weeks were sensitive to calibration coefficients. Calibration coefficients derived from the marine-based diets were broadly similar to each other and to published values from marine-fed mink ( Mustela vison ), which have been used as a model for free-ranging polar bears. For growing bears on a high-fat diet, the temporal window for QFASA estimates was 30–90 days. Although our results reinforce the importance of accurate calibration, the similarities across taxa and diets suggest it may be feasible to develop a generalized QFASA approach for mammalian carnivores.

Journal of Comparative Physiology B: Biochemical, ↗

USGS2010

Analysis of nonvolcanic tremor on the San Andreas Fault near Parkfield, CA using U.S. Geological Survey Parkfield Seismic Array

Reports by Nadeau and Dolenc (2005) that tremor had been detected near Cholame Valley spawned an effort to use UPSAR (U. S. Geological Survey Parkfield Seismic Array) to study characteristics of tremor. UPSAR was modified to record three channels of velocity at 40–50 sps continuously in January 2005 and ran for about 1 month, during which time we recorded numerous episodes of tremor. One tremor, on 21 January at 0728, was recorded with particularly high signal levels as well as another episode 3 days later. Both events were very emergent, had a frequency content between 2 and 8 Hz, and had numerous high-amplitude, short-duration arrivals within the tremor signal. Here using the first episode as an example, we discuss an analysis procedure, which yields azimuth and apparent velocity of the tremor at UPSAR. We then provide locations for both tremor episodes. The emphasis here is how the tremor episode evolves. Twelve stations were operating at the time of recording. Slowness of arrivals was determined using cross correlation of pairs of stations; the same method used in analyzing the main shock data from 28 September 2004. A feature of this analysis is that 20 s of the time series were used at a time to calculate correlation; the longer windows resulted in more consistent estimates of slowness, but lower peak correlations. These values of correlation (peaks of about 0.25), however, are similar to that obtained for the S wave of a microearthquake. Observed peaks in slowness were traced back to source locations assumed to lie on the San Andreas fault. Our inferred locations for the two tremor events cluster near the locations of previously observed tremor, south of the Cholame Valley. Tremor source depths are in the 14–24 km range, which is below the seismogenic brittle zone, but above the Moho. Estimates of error do not preclude locations below the Moho, however. The tremor signal is very emergent but contains packets that are several times larger than the background tremor signal and lasts about 5 s. These impulsive wavelets are similar to low-frequency earthquakes signals seen in Japan but appear to be broader band rather than just higher in low-frequency energy. They may be more appropriately called high-energy tremor (HET). HET signals at UPSAR correlate well with the record of this event from station GHIB of the HRSN borehole array at Parkfield and HETs typically have a higher cross-correlation coefficient than the rest of the tremor event. The amplitudes of a large HET are consistent with a magnitude of 0.1 when compared with a M2.3 event that had about the same epicenter. Polarizations of the tremor episode at UPSAR are mostly just north of east. Both linearity and azimuth evolve over time suggesting a change in tremor source location over time and linearity is typically higher at the HETs.

California↗

USGS2021

Habitat features predict carrying capacity of a recovering marine carnivore

The recovery of large carnivore species from over‐exploitation can have socioecological effects; thus, reliable estimates of potential abundance and distribution represent a valuable tool for developing management objectives and recovery criteria. For sea otters ( Enhydra lutris ), as with many apex predators, equilibrium abundance is not constant across space but rather varies as a function of local habitat quality and resource dynamics, thereby complicating the extrapolation of carrying capacity ( K ) from one location to another. To overcome this challenge, we developed a state‐space model of density‐dependent population dynamics in southern sea otters ( E. l. nereis ), in which K is estimated as a continuously varying function of a suite of physical, biotic, and oceanographic variables, all described at fine spatial scales. We used a theta‐logistic process model that included environmental stochasticity and allowed for density‐independent mortality associated with shark bites. We used Bayesian methods to fit the model to time series of survey data, augmented by auxiliary data on cause of death in stranded otters. Our model results showed that the expected density at K for a given area can be predicted based on local bathymetry (depth and distance from shore), benthic substrate composition (rocky vs. soft sediments), presence of kelp canopy, net primary productivity, and whether or not the area is inside an estuary. In addition to density‐dependent reductions in growth, increased levels of shark‐bite mortality over the last decade have also acted to limit population expansion. We used the functional relationships between habitat variables and equilibrium density to project estimated values of K for the entire historical range of southern sea otters in California, USA, accounting for spatial variation in habitat quality. Our results suggest that California could eventually support 17,226 otters (95% CrI = 9,739–30,087). We also used the fitted model to compute candidate values of optimal sustainable population abundance (OSP) for all of California and for regions within California. We employed a simulation‐based approach to determine the abundance associated with the maximum net productivity level (MNPL) and propose that the upper quartile of the distribution of MNPL estimates (accounting for parameter uncertainty) represents an appropriate threshold value for OSP. Based on this analysis, we suggest a candidate value for OSP (for all of California) of 10,236, which represents 59.4% of projected K .

California↗

USGS2016

Dynamic reusable workflows for ocean science

Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog search and data access make it now possible to create catalog-driven workflows that automate — end-to-end — data search, analysis and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill-assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enters the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic notebooks across the geoscience domains.

Journal of Marine Science and Engineering↗

USGS2013

An individual-based model for population viability analysis of humpback chub in Grand Canyon

We developed an individual-based population viability analysis model (females only) for evaluating risk to populations from catastrophic events or conservation and research actions. This model tracks attributes (size, weight, viability, etc.) for individual fish through time and then compiles this information to assess the extinction risk of the population across large numbers of simulation trials. Using a case history for the Little Colorado River population of Humpback Chub Gila cypha in Grand Canyon, Arizona, we assessed extinction risk and resiliency to a catastrophic event for this population and then assessed a series of conservation actions related to removing specific numbers of Humpback Chub at different sizes for conservation purposes, such as translocating individuals to establish other spawning populations or hatchery refuge development. Our results suggested that the Little Colorado River population is generally resilient to a single catastrophic event and also to removals of larvae and juveniles for conservation purposes, including translocations to establish new populations. Our results also suggested that translocation success is dependent on similar survival rates in receiving and donor streams and low emigration rates from recipient streams. In addition, translocating either large numbers of larvae or small numbers of large juveniles has generally an equal likelihood of successful population establishment at similar extinction risk levels to the Little Colorado River donor population. Our model created a transparent platform to consider extinction risk to populations from catastrophe or conservation actions and should prove useful to managers assessing these risks for endangered species such as Humpback Chub.

Arizona↗

USGS1995

Finite-fault analysis of the 1979 March 14 Petatlan, Mexico, earthquake using teleseismic P waveforms

Vertical, teleseismic P waves recorded for the 1979 March 14 Petatlan, Mexico, earthquake were used to derive the distribution of coseismic slip using a linear finite-fault inversion scheme that solves for the amount of slip in each of a series of consecutive time windows. Data recorded by six stations of the Global Digital Seismograph Network were inverted in addition to digitized analogue long-period recordings available from nine Worldwide Standardized Seismograph Network stations. The digital data include four broad-band and short-period velocity waveforms reconstructed from the short- and long-period components. The time-window approach allows for a variable rise time on the fault and accounts for the source multiplicity evident in the recorded P waveforms. Synthetic tests conducted using the inversion method on the limited data set, however, reveal that the data are insufficient to identify the exact dislocation duration on the fault. The method is thus implemented by prescribing the fault rise time using five consecutive 1 s time windows. The coseismic slip inferred from the P waves shows a small 70 cm peak near the earthquake hypocentre and a large zone of dislocation (1.2 m maximum) further south-east. The slip pattern covers depths from 3 to 25 km and is located south-east of other recent large interplate ruptures on the Michoacan segment of the Mexican subduction zone. This result indicates that the 1979 Petatlan earthquake broke an independent, adjacent portion of the Cocos-North America plate boundary. The seismic moment of 1.5 × 10 27 dyn cm inferred from the P waves is approximately one-half the long-period moment estimated by other investigators from the observed surface waves. Although the discrepancy is within the uncertainty of the seismic-moment estimates, it may suggest the presence of a component of slow interplate motion that did not radiate significant P -wave energy.

Geophysical Journal International↗

USGS2007

Swarms of repeating long-period earthquakes at Shishaldin Volcano, Alaska, 2001-2004

During 2001–2004, a series of four periods of elevated long-period seismic activity, each lasting about 1–2 months, occurred at Shishaldin Volcano, Aleutian Islands, Alaska. The time periods are termed swarms of repeating events , reflecting an abundance of earthquakes with highly similar waveforms that indicate stable, non-destructive sources. These swarms are characterized by increased earthquake amplitudes, although the seismicity rate of one event every 0.5–5 min has remained more or less constant since Shishaldin last erupted in 1999. A method based on waveform cross-correlation is used to identify highly repetitive events, suggestive of spatially distinct source locations. The waveform analysis shows that several different families of similar events co-exist during a given swarm day, but generally only one large family dominates. A network of hydrothermal fractures may explain the events that do not belong to a dominant repeating event group, i.e. multiple sources at different locations exist next to a dominant source. The dominant waveforms exhibit systematic changes throughout each swarm, but some of these waveforms do reappear over the course of 4 years indicating repeatedly activated source locations. The choked flow model provides a plausible trigger mechanism for the repeating events observed at Shishaldin, explaining the gradual changes in waveforms over time by changes in pressure gradient across a constriction within the uppermost part of the conduit. The sustained generation of Shishaldin's long-period events may be attributed to complex dynamics of a multi-fractured hydrothermal system: the pressure gradient within the main conduit may be regulated by temporarily sealing and reopening of parallel flow pathways, by the amount of debris within the main conduit and/or by changing gas influx into the hydrothermal system. The observations suggest that Shishaldin's swarms of repeating events represent time periods during which a dominant source is activated.

Alaska↗

USGS2010

Subevents of long-period seismicity: implications for hydrothermal dynamics during the 2004-2008 eruption of Mount St. Helens

One of the most striking aspects of seismicity during the 2004–2008 eruption of Mount St. Helens (MSH) was the precise regularity in occurrence of repetitive long-period (LP) or “drumbeat” events over sustained time periods. However, this precise regularity was not always observed, and at times the temporal occurrence of LP events became more random. In addition, accompanying the dominant LP class of events during the 2004–2008 MSH eruption, there was a near-continuous, randomly occurring series of smaller seismic events. These subevents are not always simply small-amplitude versions of the dominant LP class of events but appear instead to result from a separate random process only loosely coupled to the main LP source mechanism. We present an analysis of the interevent time and amplitude distributions of the subevents, using waveform cross correlation to separate LP events from the subevents. We also discuss seismic tremor that accompanied the 8 March 2005 phreatic explosion event at MSH. This tremor consists of a rapid succession of LPs and subevents triggered during the explosion, in addition to broadband noise from the sustained degassing. Immediately afterward, seismicity returned to the pre-explosion occurrence pattern. This triggering in relation to the rapid ejection of steam from the system, and subsequent return to pre-explosion seismicity, suggests that both seismic event types originated in a region of the subsurface hydrothermal system that was (1) in contact with the reservoir feeding the 8 March 2005 phreatic explosion but (2) not destroyed or drained by the explosion event. Finally, we discuss possible thermodynamic conditions in a pressurized hydrothermal crack that could give rise to seismicity. Pressure drop estimates for typical LP events are not generally large enough to perturb pure water in a shallow hydrothermal crack into an unstable state. However, dissolved volatiles such as CO 2 may lead to a more unstable system, increasing the seismogenic potential of a hydrothermal crack subject to rapid heat flux. The interaction of hydrothermal and magmatic systems beneath MSH in 2004–2008 thus appears able to explain a wide range of observed phenomena, including subevents, LP events, larger (M d > 2) events, and phreatic explosions.

Washington↗

USGS2007

Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia

Aim We aimed to estimate the present extent of tsunami-affected mangrove forests and determine the rates and causes of deforestation from 1975 to 2005. Location Our study region covers the tsunami-affected coastal areas of Indonesia, Malaysia, Thailand, Burma (Myanmar), Bangladesh, India and Sri Lanka in Asia. Methods We interpreted time-series Landsat data using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of plus-or-minus half a pixel, an accuracy necessary for change analysis. Each image was normalized for solar irradiance by converting digital number values to the top-of-the atmosphere reflectance. Ground truth data and existing maps and data bases were used to select training samples and also for iterative labelling. We used a post-classification change detection approach. Results were validated with the help of local experts and/or high-resolution commercial satellite data. Results The region lost 12% of its mangrove forests from 1975 to 2005, to a present extent of c . 1,670,000 ha. Rates and causes of deforestation varied both spatially and temporally. Annual deforestation was highest in Burma ( c . 1%) and lowest in Sri Lanka (0.1%). In contrast, mangrove forests in India and Bangladesh remained unchanged or gained a small percentage. Net deforestation peaked at 137,000 ha during 1990–2000, increasing from 97,000 ha during 1975–90, and declining to 14,000 ha during 2000–05. The major causes of deforestation were agricultural expansion (81%), aquaculture (12%) and urban development (2%). Main conclusions We assessed and monitored mangrove forests in the tsunami-affected region of Asia using the historical archive of Landsat data. We also measured the rates of change and determined possible causes. The results of our study can be used to better understand the role of mangrove forests in saving lives and property from natural disasters such as the Indian Ocean tsunami, and to identify possible areas for conservation, restoration and rehabilitation.

Journal of Biogeography↗

USGS2018

Landsat time series analysis of fractional plant cover changes on abandoned energy development sites

Oil and natural gas development in the western United States has increased substantially in recent decades as technological advances like horizontal drilling and hydraulic fracturing have made extraction more commercially viable. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive. Understanding the rates, controls, and degree of recovery of these reclaimed well sites to a state similar to pre-development conditions is critical for energy development and land management decision processes. Here we use a multi-decadal time series of satellite imagery (Landsat 5, 1984–2011) to assess vegetation regrowth on 365 abandoned well pads located across the Colorado Plateau in Utah, Colorado, and New Mexico. We developed high-frequency time series of the Soil-Adjusted Total Vegetation Index (SATVI) for each well pad using the Google Earth Engine cloud computing platform. BFAST time-series models were used to fit temporal trends, identifying when vegetation was cleared from the site and the magnitudes and rates of vegetation change after abandonment. The time series metrics are used to calculate the relative fractional vegetation cover (RFVC) of each pad, a measure of post-abandonment vegetation cover relative to pre-drilling condition. Mean and median RFVC were 36% (s.d. 33%) and 26%, respectively, five years after abandonment, with one third of well pads having RFVC greater than 50%. Statistical analyses suggest that much of the high vegetation cover is associated with weedy invasive annual species such as cheatgrass (Bromus tectorum) and Russian thistle (Salsola spp.). Climate conditions and the year of abandonment also play a role, with increased cover in later years associated with a wetter period. Non-linear change at many pads suggests longer recovery times than would be estimated by linear extrapolation. New techniques implemented here address a complex response of cover change to soils, management, and climate over time, and can be extended to the operational monitoring of energy development across large areas.

International Journal of Applied Earth Observation↗

USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗

USGS2023

Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery

Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality as a function of climate variability or conservation management. We trained a UNet machine-learning model, a convolutional neural network designed to highlight objects of interest within an image, to delineate tile-drain networks in panchromatic satellite imagery without additional data on soils, topography, or historical tile-drain extent. This was done by training the model to match the accuracy of human experts manually tracing the surface representation of tile drains in satellite imagery. Our approach began with a library of images that were used to train and quantify the accuracy of the model, with model performance tested on imagery from two areas that were not used to train the model. Satellite imagery included acquisition dates from 2008 to 2020. Training imagery was from agricultural areas within the US Great Lakes basin. Validation imagery was from the upper Maumee River, tributary to western Lake Erie, and an Indiana, Ohio-River headwater tributary. Our analysis of the satellite imagery paired with meteorological and soil data found that during spring, a combination of relatively high solar radiation, intermediate soil-water content and bare fields enabled the best model performance. Each area of interest was heavily tile-drained, where better understanding the movement of water, nutrients, and sediment from fields to downstream water bodies is key to managing harmful algal blooms and hypoxia. The trained UNet model successfully identified tile drains visible in the validation imagery with an accuracy of 93%–96% and balanced accuracy of 52%–54%, similar to performance for training data (95% and 63%, respectively). Model performance will benefit from ongoing contributions to the training library.

Indiana, Michigan, Ohio, Wisconsin↗

USGS2017

Riverine discharges to Chesapeake Bay: Analysis of long-term (1927–2014) records and implications for future flows in the Chesapeake Bay basin

The Chesapeake Bay (CB) basin is under a total maximum daily load (TMDL) mandate to reduce nitrogen, phosphorus, and sediment loads to the bay. Identifying shifts in the hydro-climatic regime may help explain observed trends in water quality. To identify potential shifts, hydrologic data (1927–2014) for 27 watersheds in the CB basin were analyzed to determine the relationships among long-term precipitation and stream discharge trends. The amount, frequency, and intensity of precipitation increased from 1910 to 1996 in the eastern U.S., with the observed increases greater in the northeastern U.S. than the southeastern U.S. The CB watershed spans the north-to-south gradient in precipitation increases, and hydrologic differences have been observed in watersheds north relative to watersheds south of the Pennsylvania—Maryland (PA-MD) border. Time series of monthly mean precipitation data specific to each of 27 watersheds were derived from the Precipitation-elevation Regression on Independent Slopes Model (PRISM) dataset, and monthly mean stream-discharge data were obtained from U.S. Geological Survey streamgage records. All annual precipitation trend slopes in the 18 watersheds north of the PA-MD border were greater than or equal to those of the nine south of that border. The magnitude of the trend slopes for 1927–2014 in both precipitation and discharge decreased in a north-to-south pattern. Distributions of the monthly precipitation and discharge datasets were assembled into percentiles for each year for each watershed. Multivariate correlation of precipitation and discharge within percentiles among the groups of northern and southern watersheds indicated only weak associations. Regional-scale average behaviors of trends in the distribution of precipitation and discharge annual percentiles differed between the northern and southern watersheds. In general, the linkage between precipitation and discharge was weak, with the linkage weaker in the northern watersheds compared to those in the south. On the basis of simple linear regression, 26 of the 27 watersheds are projected to have higher annual mean discharge in 2025, the target date for implementation of the TMDL for the CB basin.

Chesapeake Bay Basin↗

USGS1967

The ternary system K2SO4 MgSO4 CaSO4

Melting and subsolidus relations in the system K 2 SO 4 MgSO 4 CaSO 4 were studied using heating-cooling curves, differential thermal analysis, optics, X-ray diffraction at room and high temperatures and by quenching techniques. Previous investigators were unable to study the binary MgSO 4 CaSO 4 system and the adjacent area in the ternary system because of the decomposition of MgSO 4 and CaSO 4 at high temperatures. This problem was partly overcome by a novel sealed-tube quenching method, by hydrothermal synthesis, and by long-time heating in the solidus. As a result of this study, we found: (1) a new compound, CaSO 4 ·3MgSO 4 (m.p. 1201°C) with a field extending into the ternary system; (2) a high temperature form of MgSO 4 with a sluggishly reversible inversion. An X-ray diffraction pattern for this polymorphic form is given; (3) the inversion of β-CaSO 4 (anhydrite) to α-CaSO 4 at 1195°C, in agreement with grahmann ; (1) (4) the melting point of MgSO 4 is 1136°C and that of CaSO 4 is 1462°C (using sealed tube methods to prevent decomposition of the sulphates); (5) calcium langbeinite (K 2 SO 4 ·2CaSO 4 ) is the only compound in the K 2 SO 4 CaSO 4 binary system. This resolved discrepancies in the results of previous investigators; (6) a continuous solid solution series between congruently melting K 2 SOP 4 ·2MgSO 4 (langbeinite) and incongruently melting K 2 SO 4 ·2CaSO 4 (calcium langbeinite); (7) the liquidus in the ternary system consists of primary phase fields of K 2 SO 4 , MgSO 4 , CaSO 4 , langbeinite-calcium langbeinite solid solution, and CaSO 4 ·3MgSO 4 . The CaSO 4 field extends over a large portion of the system. Previously reported fields for the compounds (K 2 SO 4 ·MgSO 4 ·nCaSO 4 ), K 2 SO 4 ·3CaSO 4 and K 2 SO 4 ·CaSO 4 were not found; (8) a minimum in the ternary system at: 740°C, 25% MgSO 4 , 6% CaSO 4 , 69% K 2 SO 4 ; and ternary eutectics at 882°C, 49% MgSO 4 , 19% CaSO 4 , 32% K 2 SO 4 ; and 880°, 67·5% MgSO 4 , 5% CaSO 4 , 27·5% K 2 SO 4 .

Journal of Inorganic and Nuclear Chemistry↗

USGS1995

Graphical and PC-software analysis of volcano eruption precursors according to the Materials Failure Forecast Method (FFM)

The Materials Failure Forecasting Method for volcanic eruptions (FFM) analyses the rate of precursory phenomena. Time of eruption onset is derived from the time of “failure” implied by accelerating rate of deformation. The approach attempts to fit data, Ω, to the differential relationship Ω Ω ¨ = A Ω ˙ "> ¨ = AΩ˙ , where the dot superscript represents the time derivative, and the data Ω may be any of several parameters describing the accelerating deformation or energy release of the volcanic system. Rate coefficients, A and α, may be derived from appropriate data sets to provide an estimate of time to “failure”. As the method is still an experimental technique, it should be used with appropriate judgment during times of volcanic crisis. Limitations of the approach are identified and discussed. Several kinds of eruption precursory phenomena, all simulating accelerating creep during the mechanical deformation of the system, can be used with FFM. Among these are tilt data, slope-distance measurements, crater fault movements and seismicity. The use of seismic coda, seismic amplitude-derived energy release and time-integrated amplitudes or coda lengths are examined. Usage of cumulative coda length directly has some practical advantages to more rigorously derived parameters, and RSAM and SSAM technologies appear to be well suited to real-time applications. One graphical and four numerical techniques of applying FFM are discussed. The graphical technique is based on an inverse representation of rate versus time. For α = 2, the inverse rate plot is linear; it is concave upward for α < 2 and concave downward for α > 2. The eruption time is found by simple extrapolation of the data set toward the time axis. Three numerical techniques are based on linear least-squares fits to linearized data sets. The “linearized least-squares technique” is most robust and is expected to be the most practical numerical technique. This technique is based on an iterative linearization of the given rate-time series. The hindsight technique is disadvantaged by a bias favouring a too early eruption time in foresight applications. The “log rate versus log acceleration technique”, utilizing a logarithmic representation of the fundamental differential equation, is disadvantaged by large data scatter after interpolation of accelerations. One further numerical technique, a nonlinear least-squares fit to rate data, requires special and more complex software. PC-oriented computer codes were developed for data manipulation, application of the three linearizing numerical methods, and curve fitting. Separate software is required for graphing purposes. All three linearizing techniques facilitate an eruption window based on a data envelope according to the linear least-squares fit, at a specific level of confidence, and an estimated rate at time of failure.

Journal of Volcanology and Geothermal Research↗

USGS2013

Photogrammetric monitoring of lava dome growth during the 2009 eruption of Redoubt Volcano

The 2009 eruption of Redoubt Volcano, Alaska, began with a phreatic explosion on 15 March followed by a series of at least 19 explosive events and growth and destruction of at least two, and likely three, lava domes between 22 March and 4 April. On 4 April explosive activity gave way to continuous lava effusion within the summit crater. We present an analysis of post-4 April lava dome growth using an oblique photogrammetry approach that provides a safe, rapid, and accurate means of measuring dome growth. Photogrammetric analyses of oblique digital images acquired during helicopter observation flights and fixed-wing volcanic gas surveys produced a series of digital elevation models (DEMs) of the lava dome from 16 April to 23 September. The DEMs were used to calculate estimates of volume and time-averaged extrusion rates and to quantify morphological changes during dome growth. Effusion rates ranged from a maximum of 35 m 3 s − 1 during the initial two weeks to a low of 2.2 m 3 s − 1 in early summer 2009. The average effusion rate from April to July was 9.5 m 3 s − 1 . Early, rapid dome growth was characterized by extrusion of blocky lava that spread laterally within the summit crater. In mid-to-late April the volume of the dome had reached 36 × 10 6 m 3 , roughly half of the total volume, and dome growth within the summit crater began to be limited by confining crater walls to the south, east, and west. Once the dome reached the steep, north-sloping gorge that breaches the crater, growth decreased to the south, but the dome continued to inflate and extend northward down the gorge. Effusion slowed during 16 April–1 May, but in early May the rate increased again. This rate increase was accompanied by a transition to exogenous dome growth. From mid-May to July the effusion rate consistently declined. The decrease is consistent with observations of reduced seismicity, gas emission, and thermal anomalies, as well as declining rates of geodetic deflation or inflation. These trends suggest dome growth ceased by July 2009. The volume of the dome at the end of the 2009 eruption was about 72 × 10 6 m 3 , more than twice the estimated volume of the largest dome extruded during the 1989–1990 eruption. In total, the 2009 dome extends over 400 m down the glacial gorge on the north end of the crater, with a total length of 1 km, width of 500 m and an average thickness of 200 m.

Alaska↗

USGS1965

Effects of heptachlor-contaminated earthworms on woodcocks

The effects on woodcocks ( Philohela minor ) of eating heptachlor-contaminated earthworms were studied experimentally in a series of feeding trials in Louisiana in the winter of 1960-61. Six of 12 woodcocks fed worms which had been contaminated at an average of 2.86 ppm of heptachlor epoxide died within 35 days; 4 more had died by the fifty-third day, when the other 2 were killed for analysis. Worms from areas in Louisiana treated with 2 pounds of heptachlor per acre often contain more than 3 ppm of heptachlor epoxide. Eleven of 12 woodcocks fed worms contaminated at an average of 0.65 ppm survived the full 60 days of the experiment; one died on the forty-fifth day, apparently from other causes. All 11 untreated birds survived. Survivors were kept on one-quarter rations of untreated worms for 11 days. Two woodcocks, untreated previously, died during this starvation period. Five previously treated died; two were observed in spasms at death, and these contained 5.9 and 7.2 ppm heptachlor epoxide in their tissues, suggesting that the previous contaminated diet may have influenced mortality, even though the difference between two of nine dying and five of nine dying is not statistically significant. Surviving starved birds given an unrestricted supply of treated or untreated worms for 5 days survived and gained weight. Residues accumulated in their tissues in this time approached levels in birds that died of heptachlor poisoning. Residues in tissues of birds with different histories suggested residue loss at a rate of approximately 2.8 percent per day. Toxicant absorption was estimated to be in the approximate range of 16-20 percent. Residues in birds fed worms containing 0.65 ppm heptachlor epoxide were in the same general magnitude as those in field-caught birds, suggesting a similar average contamination of food supply. Weights and weight changes did not differ significantly between untreated birds and those receiving the lower level of toxicant. Among birds on one-quarter rations, the percentage of weight that could be lost without danger seemed to be near 20 percent. Woodcocks ate 18-208 grams of worms per day (average, 121 grams), representing 11-143 percent (average, 77 percent) of their body weights; birds ate contaminated and uncontaminated food in essentially equivalent amounts. Symptoms of heptachlor poisoning differed considerably between birds.

Journal of Wildlife Management↗

USGS2020

Combining ash analyses with remote sensing to identify juvenile magma involvement and fragmentation mechanisms during the 2018/19 small eruption of Peteroa volcano (Southern Andes)

The Planchón Peteroa Volcanic Complex (PPVC) is located on the border of Chile and Argentina, and is one of the most active volcanic systems in the Andes. Holocene activity has included magma-water interaction with an evolving series of crater lakes, mainly sourced from Peteroa volcano. This study examines data from the 2018/19 eruption, together with the volcanic history of the PPVC, to elucidate the complex interplay between magmatic activity and summit water and ice. From February 2016 to mid-2019, three seismic swarms occurred in the PPVC, preceding the explosive eruption from September 2018 to April 2019. The activity originated from a small vent nested within the easternmost crater, the most active portion of the complex (Peteroa). The explosions interacted with a crater lake, producing ash plumes up to 2 km above the crater and building a small tephra cone. To investigate the eruption mechanisms, we performed remote sensing analysis of plume dispersal, thermal anomalies and ground deformation, and characterized the volcanic products, including grain size, componentry, morphology, internal textures, composition and mineralogy. Our results suggest that the precursory seismicity beginning in 2016 was related to the intrusion of a new magma batch that reached the surface during the 2018/19 eruption. The eruption was also preceded by thermal anomalies, geomorphic changes and increased hydrothermal activity at the surface, though without any ground deformation recognized through radar interferometry (InSAR). The eruption initially produced predominantly recycled ash (phreatic activity), then evolved to increasing proportions of juvenile magma (phreatomagmatic) by April 2019. The juvenile clasts had a trachyandesite composition (~59 wt% SiO 2 ), with vesicular and dense scoria containing plagioclase and pyroxene. The ash surfaces show external quenching cracks and step fractures consistent with phreatomagmatic fragmentation within the active crater lake. Textural characteristics also point to a slowly ascending batch of magma that was relatively viscous by the time it interacted with water in the crater lake. Notably, these juvenile particles are distinctive from the pre-2018 products. Ash erupted from 2010/11 did not contain recognizable juvenile material, and is inferred to have been a mainly phreatic eruption. Our findings suggest that the interplay between phreatic and phreatomagmatic eruptions fed by small magma batches intruding at shallow levels characterize much of the eruptive behavior of the PPVC during the last three decades. Multi-parametric assessment is a powerful tool to discriminate between phreatic and phreatomagmatic eruptions.

Southern Andes↗