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At least 73 records · Page 4Linked to original sources

USGS2020

Upper Mississippi River system weighted wind fetch analysis (1989, 2000, 2010/2011)

Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetches are limited by landforms surrounding the body of water. Fetch is an important characteristic of open water because longer fetches can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment resuspension (Rohweder and others 2012). Increases in sediment resuspension lead to increases in water turbidity, which in turn decreases light penetration and, therefore, create conditions less conducive to aquatic plant growth (Giblin and others 2010). A wind fetch model was developed by David Finlayson, U. S. Geological Survey, Pacific Science Center, while he was a Ph.D. student at the University of Washington (Finlayson 2005). This method calculates effective fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). Scientists at the United States Geological Survey, Upper Midwest Environmental Sciences Center (UMESC) and the United States Army Corps of Engineers (USACE) further refined this model (Rohweder and others 2012) and structured it to operate using the most recent version of the ArcMap Geographic Information System platform (Esri, 2019). At the time the analysis was performed, the version of ArcMap used was 10.7.1. The model refined in 2012 was used for the analyses described in this report. Using this model, UMESC performed an analysis to model weighted wind fetch for the Upper Mississippi River System (UMRS) corresponding to three separate time periods of land cover spatial data acquisition (1989, 2000, and 2010/2011). The purpose of the analysis was to examine how fetch varies over time and space within the UMRS for potential management applications. For more detailed information on the wind fetch model, examine the USGS Open-File Report by Rohweder and others (2012).

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗

USGS1986

An overview of environmental surveillance of waste management activities at the Idaho National Engineering Laboratory

The Idaho National Engineering Laboratory (INEL), in southeastern Idaho, is a principal center for nuclear energy development for the Department of Energy (DOE) and the U.S. Nuclear Navy. Fifty-two reactors have been built at the INEL, with 15 still operable. Extensive environmental surveillance is conducted at the INEL by DOE's Radiological Environmental Sciences Laboratory (RESL), and the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), EG&G Idaho, Inc., and Westinghouse Idaho Nuclear Company (WINCO). Surveillance of waste management facilities radiation is integrated with the overall INEL Site surveillance program. Air, warer, soil, biota, and environmental radiation are monitored or sampled routinely at INEL. Results to date indicate very small or no impacts from INEL on the surrounding environment. Environmental surveillance activities are currently underway to address key environmental issues at the INEL.

Idaho↗

USGS2013

Spatial Relation Predicates in Topographic Feature Semantics

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Book chapter↗

USGS2014

Geomorphological Fieldwork

Geomorphological Fieldwork addresses a topic that always remains popular within the geosciences and environmental science. More specifically, the volume conveys a growing legacy of field-based learning for young geomorphologists that can be used as a student book for field-based university courses and postgraduate research requiring fieldwork or field schools. The editors have much experience of field-based learning within geomorphology and extend this to physical geography. The topics covered are relevant to basic geomorphology as well as applied approaches in environmental and cultural geomorphology. The book integrates a physical-human approach to geography, but focuses on physical geography and geomorphology from an integrated field-based geoscience perspective.

Book↗

USGS2018

Quantifying population-level effects of water temperature, flow velocity and chemical-induced reproduction depression: A simulation study with smallmouth bass

Evaluating stochastic abiotic factors and their combined effects on fish and wildlife populations have been challenging in environmental sciences. Contributing to this challenge is the paucity of data describing how observations made on individuals related to exposure to chemical compounds ultimately effect population vital rates, and how this exposure interacts with other abiotic drivers. Using three smallmouth bass populations in Pennsylvania as a case study, we explored both single-factor and combined effects of water temperature, flow velocity and chemical exposure on populations through a model simulation. Although there are many pathways through which chemicals can affect population vital rates, we focused on one where chemical exposure leads to reduced reproduction. Among the three populations considered, two (the Juniata and Susquehanna populations) have experienced adverse health, including the potential adverse effects of environmental stress and chemical contamination that may cause disease and mortality of young-of-year (YOY), various skin lesions and a high prevalence of intersex or testicular oocytes in adults. The third population (The Alleghany population) has not encountered mortality events of YOY and intersex prevalence is much lower. The simulation involved projecting populations using a length-based model under different environmental conditions. In the simulations, abiotic factors influenced population dynamics through their impacts on growth, survival and recruitment. Response to the same environmental stress varied by population and life-stage of the species. Factors affecting young adult and adult life-stages had great influence on proportional stock density (PSD) and the probability of having PSD within the suggested range (PSD probability). Increases in water temperature had a negative effect and dominant role in the combined effect on population size structure (e.g., PSD and PSD probability) – increases in flow velocity during the spring season also had a negative effect on abundance. Populations with high recruitment rates sustained relatively large population size, even under high water temperature and/or high flow velocity, which suggests that factors and management strategies that benefit recruitment (such as reduced chemical contaminants) may compensate for the negative effects of warming water temperatures and high spring flow velocity on population size.

Ecological Modelling↗

USGS2020

An overview of agent-based models in plant biology and ecology

Agent-based modeling (ABM) has become an established methodology in many areas of biology, ranging from the cellular to the ecological population and community levels. In plant science, two different scales have predominated in their use of ABM. One is the scale of populations and communities, through the modeling of collections of agents representing individual plants, interacting with each other and with the environment. The other is the scale of the individual plant, through the modeling, by functional-structural plant models (FSPMs), of agents representing plant building blocks, or metamers, to describe the development of plant architecture and functions within individual plants. The purpose of this review is to show key results and parallels in ABM for growth, mortality, carbon allocation, competition, and reproduction across the scales from the plant organ to populations and communities on a range of spatial scale to the whole landscape. Several areas of application of ABMs are reviewed, showing that some issues are addressed by both population-level ABMs and FSPMs. Continued increase in the relevance of ABM to environmental science and management will be helped by greater integration of ABMs across these two scales.

Annals of Botany↗

USGS2021

Techniques to improve ecological interpretability of black box machine learning models

Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s H 2 "> H 2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests. Supplementary materials accompanying this paper appear on-line.

Journal of Agricultural, Biological, and Environme↗

USGS2019

Evaluating legacy effects of hyperabundant white-tailed deer (Odocoileus virginianus) in forested stands of Harriman and Bear Mountain State Parks, New York

Executive Summary White-tailed deer (Odocoileus virginianus) are among the most impactful herbivores in the eastern United States. Legacy forest effects, those accrued from intense herbivory over time, manifest as low seedling regeneration, high cover of plant species that are infrequently browsed by deer, presence or expansion of nonnative or invasive plant species, few herbaceous species, and diminished capacity for recovery. Interfering vegetation (that is, species that increase in cover and density due to avoidance by deer, such as American beech sprouts, Pennsylvania sedge, and hay-scented fern) increase competition for light and hinder recruitment of trees into the forest canopy. The lower Hudson Valley in New York has been heavily browsed by white-tailed deer since the early 20th century. The region has some of the lowest tree regeneration rates in New York State as a result of deer browsing and subsequent increases in interfering vegetation. The U.S. Geological Survey and the State University of New York College of Environmental Science and Forestry studied sites where deer hunting is permitted (case sites) and nearby sites where hunting is currently prohibited (control sites) to assess and identify forest structure and composition differences. Instead of using deer exclosures, which are time-consuming and expensive to install and maintain, we used a case-control study because such studies are well-suited to effects with long latency and rare outcomes. Case-control studies seek to describe the relation between an outcome of interest (in this study, forest understory recovery from chronic herbivory) and forest condition. We inferred recovery by comparing these characteristics on adjacent sites in the lower Hudson Valley with similar forest communities and land uses but different deer population management histories. Case plots were on lands where deer management has taken place annually for several decades. Control plots were on lands where deer populations have not been consistently managed to lowered abundance. We accounted for differences in forest recovery not attributable to deer by first matching case and control plots along several important environmental gradients (slope, aspect, elevation, moisture, canopy openness). By controlling for these gradients, we looked for associations between measured forest conditions and deer herbivory reduction through population management. We surveyed more than 200 plots in upland forest types across case and control sites where we assessed forest condition by estimating density (number per unit area) and composition and cover (percent) of important vegetation constituents in ground, shrub, subcanopy, and canopy layers of the forest. We recorded 37 tree species, 22 shrub species, 57 herbaceous species, and 19 species of grasses and sedges in our plot surveys, including a number of nonnative and invasive plants. We also estimated the ages of a number of common canopy trees by counting rings from cores extracted from individual stems. Effects of more than 100 years of chronic deer browsing manifested in low herbaceous ground cover and little to no tree recruitment (saplings) on lands without deer management. In contrast, sustained deer management resulted in forests with conditions that indicated substantial recovery from chronic herbivory in the ground, shrub, and subcanopy layers. Sites with ongoing deer management exhibited greater ground cover of tree seedlings and herbs and less ground cover of interfering vegetation and nonnative species. The well-developed sub-canopy layer of small trees, saplings, and tall shrubs on sites with deer management indicates a high potential for sapling recruitment to the canopy of the future forest. Of the 25 subcanopy trees sampled on control sites, most were more than 100 years old, indicating little to no regeneration in areas sampled for more than 100 years. The forest canopy, a relic of land uses of bygone days, requires a source of young trees to replace itself as older trees die. Without an abundant layer of young trees in the subcanopy, a forest cannot be sustained over time. Reduction in deer herbivory promotes forest recovery and could benefit Harriman and Bear Mountain State Parks (the control sites for the study), but removal of interfering vegetation may be necessary to mitigate legacy effects where they currently hinder ground layer recovery. To successfully promote a more desirable forest condition that includes elimination of nonnative plant species, promotion of tree recruitment into the forest canopy, and development of diverse and abundant herbaceous cover in ground layer vegetation, future management decisions could include information on herbivory reduction and management of interfering vegetation where necessary.

New York↗

USGS2016

Users and uses of Landsat 8 satellite imagery—2014 survey results

Executive Summary In 2013, Landsat 8 began adding high quality, global, moderate-resolution imagery to the more than 40-year archive of Landsat imagery. To assess the potential effects of the availability of Landsat 8 imagery on users and their work, the U.S. Geological Survey (USGS) Land Remote Sensing Program (LRS) initiated a survey of Landsat users. The objectives of the survey were to 1. Characterize various Landsat user groups, such as United States (U.S.) and international users and Landsat 8 and non-Landsat 8 users; 2. Identify any differences among user groups in uses and preferences; 3. Measure the importance of and satisfaction with Landsat 8 attributes; 4. Assess the importance to users of the frequency of usable imagery; and 5. Determine any challenges in using Landsat 8. The online survey was sent to 51,617 Landsat users registered with USGS in May 2014. Almost 13,000 people responded to the survey for a response rate of 25 percent (n = 12,966). Current Landsat users (users who had used Landsat in their work in the year prior to the survey) composed 89 percent of the sample (n = 11,549) and past Landsat users composed 11 percent (n = 1,417). The results reported here apply to current Landsat users registered with the USGS Earth Resources Observation and Science (EROS) Center. Users from 161 countries responded to the survey. Of those, 19 percent were citizens or permanent residents of the United States and 81 percent resided in other countries. More than 70 percent of current users had used Landsat 8 in the year prior to the survey. The majority of Landsat 8 users (65 percent) were established users who used Landsat imagery regularly both before and after Landsat 8 imagery became available. The average current Landsat user was male, 36 years old, and highly educated, with 9 years of experience using satellite imagery or geographic information system (GIS) software. Landsat 8 users had, on average, two more years of experience than non-Landsat 8 users. Users were employed predominantly by academic institutions (65 percent), followed by private businesses (13 percent), Federal governments (10 percent), State and local governments (6 percent), and nonprofit organizations (6 percent). Of the Landsat imagery obtained in the past year by current users, on average 31 percent came from a Landsat 8 sensor. An equivalent amount came from the Landsat 7 ETM+ sensor (33 percent); slightly less came from Landsats 4 and 5 TM sensors (27 percent). Much less came from Landsats 1 through 5 MSS sensors (5 percent). Overall, more than a third of users’ work used Landsat imagery (38 percent). Of this work, on average, 37 percent of the work was operational. Landsat 8 users considered a greater proportion of their work operational than non-Landsat 8 users (39 percent compared with 29 percent). Environmental sciences and management were the most commonly selected primary applications (selected by 42 percent of users). Land use/land cover (23 percent) was the second most commonly selected primary application, followed by education (12 percent), agriculture (9 percent), and planning and development (6 percent). Landsat 8 users were asked to rank the importance of certain attributes in determining whether to use Landsat 8 imagery in their work. The archive was ranked most important, followed by cost, spatial resolution, extent of coverage, data quality, and frequency of revisit. Users were asked how satisfied they were with these same attributes as they currently apply to Landsat 8 imagery. On average, users were most satisfied with lack of cost, extent of coverage, data quality, and the archive, but they were satisfied with all attributes. Users were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency of usable imagery for the following levels: 1. Threshold level—the minimum frequency of usable imagery needed to be of any value to their primary application. 2. Breakthrough level—the frequency of usable imagery that would result in a significant improvement for their primary application of the imagery. 3. Target level—the frequency of usable imagery that would only provide a limited additional increase in the expected performance for their primary application. To meet the threshold level, three-quarters of users needed usable imagery every 17 days or less frequently. At the breakthrough level, two-thirds of users (64 percent) needed a usable image every 5–16 days. The current constellation of two satellites (Landsat 7 and 8) is capable of meeting the threshold and breakthrough needs of most users at least some of the time, but a single satellite would be highly unlikely to do so. Two-fifths of users (40 percent) felt that usable imagery provided every 4 days or more frequently would meet their target level which the current Landsat constellation cannot provide. Landsat 8 users were significantly more likely than non-Landsat 8 users to need usable imagery more frequently to meet their target levels. Additionally, U.S. Landsat 8 users were significantly more likely than other Landsat users to need usable imagery more frequently in order meet both their breakthrough and target levels. To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.

Open-File Report↗

USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗

USGS2019

Simultaneous autoregressive (SAR) model

Simultaneous autoregressive (SAR) models are useful for accommodating various forms of dependence among data that have discrete support in a space of interest. These models are often specified hierarchically as mixed-effects regression models with first-moment structure controlled by a conventional linear regression term and second-moment structure induced by correlated random effects. In their general form, SAR models resemble conditional autoregressive (CAR) models, and can be made equivalent but are often parameterized differently. Importantly, SAR models can be specified by simultaneously regressing a discrete spatial process on itself. Thus, they allow one to construct statistical models for processes with directional graphical properties that pertain to data generating mechanisms. Most commonly SAR models have been used to account for structure among data with areal spatial support in applications involving ecology, epidemiology, sociology, and environmental science.

Book chapter↗

USGS2005

Quantitative assessment of pair formation behavior in captive whooping cranes (Grus americana)

Instantaneous scan sampling for mean distance and synchronous action patterns and all-occurrence sampling for unison call, dance, strut, and hoover-up behaviors were conducted for five potential whooping crane pairs at Patuxent Environmental Science Center, Laurel, Maryland. Dance, strut, and hoover-up differed among pairs, as did total frequency of social behaviors. It was unclear whether or not total frequency of social behaviors during pair formation can be used as an index for potential breeding success. The relative importance of different action patterns should be used as indices of pair compatibility in captive whooping cranes.

Zoo Biology↗

USGS2011

Stable isotopes of transition and post-transition metals as tracers in environmental studies

The transition and post-transition metals, which include the elements in Groups 3–12 of the Periodic Table, have a broad range of geological and biological roles as well as industrial applications and thus are widespread in the environment. Interdisciplinary research over the past decade has resulted in a broad understanding of the isotope systematics of this important group of elements and revealed largely unexpected variability in isotope composition for natural materials. Significant kinetic and equilibrium isotope fractionation has been observed for redox sensitive metals such as iron, chromium, copper, molybdenum and mercury, and for metals that are not redox sensitive in nature such as cadmium and zinc. In the environmental sciences, the isotopes are increasingly being used to understand important issues such as tracing of metal contaminant sources and fates, unraveling metal redox cycles, deciphering metal nutrient pathways and cycles, and developing isotope biosignatures that can indicate the role of biological activity in ancient and modern planetary systems.

Book↗

USGS2015

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Estuaries and Coasts↗

USGS2013

Introduction to the special issue on ‘Frontiers in gas geochemistry’

The study of the geochemistry of gases pervades the Earth and Environmental Sciences. This is due in no small measure to the well-established thermodynamic properties of gases which allow their application to a variety of processes occurring over a wide spectrum of natural conditions. In this respect, both major and associated minor gases have been proven useful: indeed, the trace gases have been particularly important given their role as sensitive geochemical tracers. Examples where gas geochemistry places key constraints on geochemical processes include the degassing history of the solid Earth to form the atmosphere and oceans, the origin and migration characteristics of hydrocarbon deposits, the scale of climate variability, the P–T characteristics of geothermal reservoirs, and the dynamics of the earthquake cycle and volcanic activity, to name but a few. This volume continues this rich tradition with an eclectic selection of papers aimed at exploring and exploiting gas geochemistry over a myriad set of research themes.

Chemical Geology↗

USGS2017

Acoustic deterrence of bighead carp ( Hypophthalmichthys nobilis ) to a broadband sound stimulus

Recent studies have shown the potential of acoustic deterrents against invasive silver carp ( Hypophthalmichthys molitrix ). This study examined the phonotaxic response of the bighead carp ( H. nobilis ) to pure tones (500–2000 Hz) and playbacks of broadband sound from an underwater recording of a 100 hp outboard motor (0.06–10 kHz) in an outdoor concrete pond (10 × 5 × 1.2 m) at the U.S. Geological Survey Upper Midwest Environmental Science Center in La Crosse, WI. The number of consecutive times the fish reacted to sound from alternating locations at each end of the pond was assessed. Bighead carp were relatively indifferent to the pure tones with median consecutive responses ranging from 0 to 2 reactions away from the sound source. However, fish consistently exhibited significantly (P < 0.001) greater negative phonotaxis to the broadband sound (outboard motor recording) with an overall median response of 20 consecutive reactions during the 10 min trials. In over 50% of broadband sound tests, carp were still reacting to the stimulus at the end of the trial, implying that fish were not habituating to the sound. This study suggests that broadband sound may be an effective deterrent to bighead carp and provides a basis for conducting studies with wild fish.

Journal of Great Lakes Research↗

USGS2017

Real-time specific surface area measurements via laser-induced breakdown spectroscopy

From healthcare to cosmetics to environmental science, the specific surface area (SSA) of micro- and mesoporous materials or products can greatly affect their chemical and physical properties. SSA results are also widely used to examine source rocks in conventional and unconventional petroleum resource plays. Despite its importance, current methods to measure SSA are often cumbersome, time-consuming, or require cryogenic consumables (e.g., liquid nitrogen). These methods are not amenable to high-throughput environments, have stringent sample preparation requirements, and are not practical for use in the field. We present a new application of laser-induced breakdown spectroscopy for rapid measurement of SSA. This study evaluates geological samples, specifically organic-rich oil shales, but the approach is expected to be applicable to many other types of materials. The method uses optical emission spectroscopy to examine laser-generated plasma and quantify the amount of argon adsorbed to a sample during an inert gas purge. The technique can accommodate a wide range of sample sizes and geometries and has the potential for field use. These advantages for SSA measurement combined with the simultaneous acquisition of composition information make this a promising new approach for characterizing geologic samples and other materials.

Energy and Fuels↗

USGS2011

Implementing a U.S. national phenology network

The passing of seasons, as gauged by annual events or phenophases in organisms' life cycles, is arguably one of the most pervasive environmental variations on Earth. Shifts in seasonal timing, or phenology, are observed in flowering and other stages of plant development, animal migration and reproduction, hibernation, and the seasonal activity of cold-blooded animals [e.g., Schwartz , 2003; Root et al ., 2005]. As an important life history trait, phenology is an object of natural selection; depending on timescales, shifts in phenology can lead to evolutionary change. Thus, phenology is not only an indicator of pattern in environmental science, but also its variation has fitness consequences for individuals, and these can scale up to broader ecological dynamics.

Eos, Transactions, American Geophysical Union↗