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USGS2025

Update of the 2008 provisional Enhanced Geothermal Systems (EGS) assessment for the Great Basin, USA

In response to the Energy Act of 2020, the U.S. Geological Survey (USGS) is updating the Enhanced Geothermal Systems (EGS) resource assessment for the Great Basin, USA. The previous 2008 provisional assessment estimated how much electricity could be generated from EGS resources of the western United States using models of electric-grade heat, models of heat extraction over time, and estimates of how much rock might be stimulated to produce viable amounts of heat. Herein, a similar conceptual strategy is applied, using updated models of heat extraction as a function of fracture spacing and well distance. Previously used reservoir heat delivery models are updated to have a dependence on fracture and well spacing, potentially improving future estimates of EGS resources as ongoing research provides a better understanding about the success of reservoir stimulation as a function of geology and location. For a range of well distances (250-1000 m) and fracture spacings (1-50 m), heat extraction efficiency ranges from 25-62%, demonstrating the importance of accounting for the most likely results of proven viable fracturing technologies. Although fracturing is important, the biggest uncertainty by far in estimating the EGS resource for the Great Basin is estimating which geologic units at what depths can be stimulated sufficiently to produce geothermal energy economically and efficiently. Uncertainties in these factors yield estimates that range over two orders of magnitude with an upper limit of ~174 terawatts-thermal (TWth) produced for 30 years from the upper 7 km of the crust. This upper limit would require significant technological advances to access most of the electric-grade resource across the Great Basin. Assuming that 1% of this estimate will be accessible in the next few decades gives a resource estimate similar to that made in the 2008 provisional assessment. These estimated EGS heat extraction rates far exceed ( greater than 100x) the natural geothermal heat production rate, thus geothermal electricity production at these rates might not be sustainable unless heat is also recharged from other sources (e.g., excess solar energy when supply exceeds demand). In addition to assessment maps and cumulative estimates, the new models of fractured reservoirs developed herein can be used to estimate steady power production given a set of fractures and well spacing, and estimates can be made for setback distances to ensure no thermal interference with nearby powerplants.

Arizona, California, Idaho, Nevada, Oregon, Utah↗

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↗

USGS2012

Recent scientific advances and their implications for sand management near San Francisco, California: The influences of the ebb tidal delta

Recent research in the San Francisco, California, U.S.A., coastal region has identified the importance of the ebb tidal delta to coastal processes. A process-based numerical model is found to qualitatively reproduce the equilibrium size and shape of the delta. The ebb tidal delta itself has been contracting over the past century, and the numerical model is applied to investigate the sensitivity of the delta to changes in forcing conditions. The large ebb tidal delta has a strong influence upon regional coastal processes. The prominent bathymetry of the ebb tidal delta protects some of the coast from extreme storm waves, but the delta also focuses wave energy toward the central and southern portions of Ocean Beach. Wave focusing likely contributes to a chronic erosion problem at the southern end of Ocean Beach. The ebb tidal delta in combination with non-linear waves provides a potential cross-shore sediment transport pathway that probably supplies sediment to Ocean Beach.

California↗

USGS2026

A simplified two-station approach for modeling metabolism in dam tailwaters subject to diel flow variation

Tailwaters are ubiquitous and highly managed ecosystems whose food webs often rely disproportionately on autochthonous energy. In situ continuous dissolved oxygen data are increasingly being used to estimate gross primary productivity and ecosystem respiration in rivers, but this approach is complicated in tailwaters, where upriver discontinuities (i.e., dams) violate commonly employed one-station approaches. In such cases, two-station metabolism models can be applied, although substantial diel variation in flow (a common outcome of hydropower production) requires more complex treatment of water parcel travel times. Here, we present a new two-station metabolism model that allows estimation of reach-scale gross primary productivity and ecosystem respiration in streams and rivers that experience within-day variation in flow. Our approach simplifies two-station variable flow model implementation compared to previous efforts. We apply our model to a 6-yr dissolved oxygen time series and use Bayesian inference to estimate daily gross primary productivity, ecosystem respiration, and gas exchange velocity ( k 600 ) for a ~12-km reach of the Colorado River downriver of Glen Canyon Dam. We compare our model's performance to a more mechanistically detailed and computationally intensive Eulerian dynamic flow model and also to a widely-used one-station model that uses assumptions of reach uniformity that are often strongly violated in tailwaters. These comparisons show that our metabolism estimates conform with output from the more detailed dynamic flow model and that the one-station approach deviates substantially from both two-station approaches. Our new stream metabolism model can help resolve a fundamental analytical impediment in tailwater ecology.

Arizona↗

USGS2007

A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields

Accurate crop performance monitoring and production estimation are critical for timely assessment of the food balance of several countries in the world. Since 2001, the Famine Early Warning Systems Network (FEWS NET) has been monitoring crop performance and relative production using satellite-derived data and simulation models in Africa, Central America, and Afghanistan where ground-based monitoring is limited because of a scarcity of weather stations. The commonly used crop monitoring models are based on a crop water-balance algorithm with inputs from satellite-derived rainfall estimates. These models are useful to monitor rainfed agriculture, but they are ineffective for irrigated areas. This study focused on Afghanistan, where over 80 percent of agricultural production comes from irrigated lands. We developed and implemented a Simplified Surface Energy Balance (SSEB) model to monitor and assess the performance of irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250m Normalized Difference Vegetation Index (NDVI) data, both from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. We estimated seasonal actual evapotranspiration (ETa) over a period of six years (2000-2005) for two major irrigated river basins in Afghanistan, the Kabul and the Helmand, by analyzing up to 19 cloud-free thermal and NDVI images from each year. These seasonal ETa estimates were used as relative indicators of year-to-year production magnitude differences. The temporal water-use pattern of the two irrigated basins was indicative of the cropping patterns specific to each region. Our results were comparable to field reports and to estimates based on watershed-wide crop water-balance model results. For example, both methods found that the 2003 seasonal ETa was the highest of all six years. The method also captured water management scenarios where a unique year-to-year variability was identified in addition to water-use differences between upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water-balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields. ?? 2007 by MDPI.

Sensors↗

USGS2011

On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

Earth Interactions↗

USGS2023

Field observations and long short-term memory modeling of spectral wave evolution at living shorelines in Chesapeake Bay, USA

Living shorelines as a nature-based solution for climate change adaptation were constructed in many places around the world. The success of this type of projects requires long-term monitoring for adaptive management. The paper presents a novel framework leveraging scientific machine learning methods for accurate and rapid prediction of long-term hydrodynamic forcing impacting living shorelines using short-term measurements of water levels and wind waves in the largest estuary in the U.S. Different from existing data-driven wave prediction models focusing on significant wave heights, this study is focused on the prediction of wave energy spectra in shallow water using winds and tides as the input feature and short-term measurements of wave spectra and water depths as the label. Long Short-Term Memory (LSTM) models were developed using four-month wave measurements in the stormy seasons to predict integral wave parameters and energy spectra for multiple years. The developed models accurately predicted wave heights, peak periods, and energy spectra around the living shorelines, capturing complex wave dynamics, such as wave generation by wind, nonlinear wave-wave interactions, and depth-limited wave breaking in the shallow water of a large estuary. The validated models were then used to determine the long-term wave forcing impacting the living shorelines based on the modeled wave characteristics and spectra. Model results show that the surrogate models utilizing LSTM to predict wave spectra in the frequency domain enable long-term predictions of spectral wave evolution with a minimal computational cost. Our findings provide valuable insights into the efficacy of living shorelines in attenuating wave energy and demonstrate the utility of this approach in assessing the effectiveness of such living shoreline structures.

Applied Ocean Research↗

USGS2011

Assessing conceptual models for subsurface reactive transport of inorganic contaminants

In many subsurface situations where human health and environmental quality are at risk (e.g., contaminant hydrogeology petroleum extraction, carbon sequestration, etc.),scientists and engineers are being asked by federal agency decision-makers to predict the fate of chemical species under conditions where both reactions and transport are processes of first-order importance. In 2002, a working group (WG) was formed by representatives of the U.S. Geological Survey, Environmental Protection Agency, Department of Energy Nuclear Regulatory Commission, Department of Agriculture, and Army Engineer Research and Development Center to assess the role of reactive transport modeling (RTM) in addressing these situations. Specifically the goals of the WG are to (1) evaluate the state of the art in conceptual model development and parameterization for RTM, as applied to soil,vadose zone, and groundwater systems, and (2) prioritize research directions that would enhance the practical utility of RTM.

Eos, Transactions, American Geophysical Union↗

USGS2020

Learning from real-world experience to understand renewable energy impacts to wildlife

The project team sought to use real-world data to understand adverse effects to wildlife of renewable energy production that is critical to meeting California’s climate and clean energy goals. The project had three main components. First, a systematic literature review studied 20 peer-reviewed publications and 612 reports from other nonreviewed sources from 231 wind and solar facilities in North America. Within California, 50 percent of facilities collected pre- and post-construction data, 30 percent had experimental study designs, and fewer than 7 percent estimated detection probability during habitat use surveys. Mitigation at wind power plants focused on repowering to reduce risk to soaring birds and at solar facilities emphasized wildlife deterrence and compensatory mitigation. Second, the authors developed a best-practices approach to employ environmental isotopes (for example, hydrogen obtained from animal tissue) and rescaling functions (a statistical approach to modeling the relationship between variables) to assign individual birds or bats to their place of origin. The team applied this approach to feathers from 411 individuals of 12 species killed at wind facilities and 515 individuals of 19 species killed at solar facilities. From 24 percent to 100 percent (mean +/- SD = 49 percent +/- 33 percent) and 25 percent to 100 percent (73 percent +/- 25 percent) of birds grew feathers at a location outside the collection site at wind and solar facilities, respectively. Third, the authors constructed Bayesian integrated population models (probability models) for 29 focal species affected by wind or solar energy generation in California. Species predominantly local in origin generally had lower population growth rates than did species that were predominantly nonlocal in origin. These patterns illustrate the complex linkages between behavioral ecology, vulnerability to mortality, and population-level impacts to wildlife from fatalities at renewable energy facilities. This project benefits the renewable energy sector by providing a framework and specific tools for understanding environmental impacts of renewable energy generation.

California↗

USGS2018

A simple method for partitioning total solar radiation into diffuse/direct components in the United States

Solar radiation is a major sustainable and clean energy resource, and use of solar radiation is expected to increase. The utilization efficiency of solar energy varies with the relative proportions of the direct and diffuse components that compose total solar radiation and with the slope and aspect of the irradiated surface. The purpose of this paper is to develop a simple method for estimating diffuse and direct solar radiation at sites with observation of only total solar radiation. An existing model for estimating diffuse radiation, i.e., a linear relationship between the diffuse fraction (the ratio of diffuse radiation to total solar radiation) and the clearness index (the ratio of total solar radiation to extraterrestrial radiation), is applied to 7 sites across the continental United States with observations of diffuse and total radiation. The linear model shows good monthly performance. The model parameters (slope and interception) show a strong seasonal pattern that exhibits small variation across the 7 sites; therefore, the average values of the two monthly parameters may be used for estimating diffuse radiation for other locations with observations of total radiation.

International Journal of Green Energy↗

USGS2018

Efficiently optimizing for dendritic connectivity on tree-structured networks in a multi-objective framework

We provide an exact and approximation algorithm based on Dynamic Programming and an approximation algorithm based on Mixed Integer Programming for optimizing for the so-called dendritic connectivity on tree-structured networks in a multi-objective setting. Dendritic connectivity describes the degree of connectedness of a network. We consider different variants of dendritic connectivity to capture both network connectivity with respect to long and short-to-middle distances. Our work is motivated by a problem in computational sustainability concerning the evaluation of trade-offs in ecosystem services due to the proliferation of hydropower dams throughout the Amazon basin. In particular, we consider trade-offs between energy production and river connectivity. River fragmentation can dramatically affect fish migrations and other ecosystem services, such as navigation and transportation. In the context of river networks, different variants of dendritic connectivity are important to characterize the movements of different fish species and human populations. Our approaches are general and can be applied to optimizing for dendritic connectivity for a variety of multi-objective problems on tree-structured networks.

Conference Paper↗

USGS2024

The impact of source time function complexity on stress drop estimates

Earthquake stress drop—a key parameter for describing the energetics of earthquake rupture—can be estimated in several different, but theoretically equivalent, ways. However, independent estimates for the same earthquakes sometimes differ significantly. We find that earthquake source complexity plays a significant role in why theoretically (for simple rupture models) equivalent methods produce different estimates. We apply time‐ and frequency‐domain methods to estimate stress drops for real earthquakes in the SCARDEC (Seismic source ChAracteristics Retrieved from DEConvolving teleseismic body waves, Vallée and Douet, 2016 ) source time function (STF) database and analyze how rupture complexity drives stress‐drop estimate discrepancies. Specifically, we identify two complexity metrics—Brune relative energy (BRE) and spectral decay—that parameterize an earthquake’s complexity relative to the standard Brune model and strongly correlate with the estimate discrepancies. We find that the observed systematic magnitude–stress‐drop trends may reflect underlying changes in STF complexity, not necessarily trends in actual stress drop. Both the decay and BRE parameters vary systematically with magnitude, but whether this magnitude–complexity relationship is real remains unresolved.

Bulletin of the Seismological Society of America↗

USGS2019

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report↗

USGS2007

Comparison of 15 evaporation methods applied to a small mountain lake in the northeastern USA

Few detailed evaporation studies exist for small lakes or reservoirs in mountainous settings. A detailed evaporation study was conducted at Mirror Lake, a 0.15 km2 lake in New Hampshire, northeastern USA, as part of a long-term investigation of lake hydrology. Evaporation was determined using 14 alternate evaporation methods during six open-water seasons and compared with values from the Bowen-ratio energy-budget (BREB) method, considered the standard. Values from the Priestley-Taylor, deBruin-Keijman, and Penman methods compared most favorably with BREB-determined values. Differences from BREB values averaged 0.19, 0.27, and 0.20 mm d-1, respectively, and results were within 20% of BREB values during more than 90% of the 37 monthly comparison periods. All three methods require measurement of net radiation, air temperature, change in heat stored in the lake, and vapor pressure, making them relatively data intensive. Several of the methods had substantial bias when compared with BREB values and were subsequently modified to eliminate bias. Methods that rely only on measurement of air temperature, or air temperature and solar radiation, were relatively cost-effective options for measuring evaporation at this small New England lake, outperforming some methods that require measurement of a greater number of variables. It is likely that the atmosphere above Mirror Lake was affected by occasional formation of separation eddies on the lee side of nearby high terrain, although those influences do not appear to be significant to measured evaporation from the lake when averaged over monthly periods.

New Hampshire↗

USGS2018

Managing the water-energy-food nexus: Opportunities in Central Asia

This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.

Journal of Hydrology↗

USGS2022

Monitoring offshore CO2 sequestration using marine CSEM methods; constraints inferred from field- and laboratory-based gas hydrate studies

Offshore geological sequestration of CO 2 offers a viable approach for reducing greenhouse gas emissions into the atmosphere. Strategies include injection of CO 2 into the deep-ocean or ocean-floor sediments, whereby depending on pressure–temperature conditions, CO 2 can be trapped physically, gravitationally, or converted to CO 2 hydrate. Energy-driven research continues to also advance CO 2 -for-CH 4 replacement strategies in the gas hydrate stability zone (GHSZ), producing methane for natural gas needs while sequestering CO 2 . In all cases, safe storage of CO 2 requires reliable monitoring of the targeted CO 2 injection sites and the integrity of the repository over time, including possible leakage. Electromagnetic technologies used for oil and gas exploration, sensitive to electrical conductivity, have long been considered an optimal monitoring method, as CO 2 , similar to hydrocarbons, typically exhibits lower conductivity than the surrounding medium. We apply 3D controlled-source electromagnetic (CSEM) forward modeling code to simulate an evolving CO 2 reservoir in deep-ocean sediments, demonstrating sufficient sensitivity and resolution of CSEM data to detect reservoir changes even before sophisticated inversion of data. Laboratory measurements place further constraints on evaluating certain systems within the GHSZ; notably, CO 2 hydrate is measurably weaker than methane hydrate, and >1 order of magnitude more conductive, properties that may affect site selection, stability, and modeling considerations.

Energies↗

USGS2018

Monitoring responses to variation in food supply for a migratory waterfowl: American Black Duck (Anas rubripes) in winter

Wintering Black Ducks ( Anas rubripes ) concentrate in wetlands along the Atlantic coast where natural and anthropogenic disturbances have increased over the last 50 years, a period in which the population of Black Ducks has declined. We studied the sensitivity of Black Ducks to perturbations in food supply that often result from disturbances by storms, predators, and people. In the paper, we characterize the responses of captive Black Ducks to shifts in food quality and availability during winter and apply those measures to a comparison of wild birds. Captive ducks that were fed intermittently (3 consecutive days/week) compensated for fasted days to achieve similar body mass and body fat to control birds that were fed every day on both animal- and plant-based diets. However, birds that were fed intermittently expended 15% more energy each day than controls when both groups were fed (536 vs. 464 kJ/kg 0.75 ), which indicates that variable food supply increases the costs of maintenance and thus reduces the number of birds that can be supported on the same resource of food without interruptions to foraging. Egg production was not affected by diet quality provided in spring or by the frequency of feeding during the preceding winter months. Black Ducks lost body fat through winter in captivity and in the wild. Fat stores of birds in New Jersey were greater than those of birds in Maine (13.3 vs. 8.3% of body mass) in January, which reflected the high energy demands of cold temperatures in Maine. Values for ∂ 15 N were greater in Maine than in New Jersey for both red blood cells and plasma, which indicated a consistent diet of marine invertebrates in Maine. Greater isotopic variation in red blood cells indicated that diets were more diverse in New Jersey than in Maine for both ∂ 15 N (9.7 ± 1.1 vs. 11.2 ± 0.4‰) and for ∂ 13 C (− 15.1 ± 2.2 vs. − 13.8 ± 1.4‰). Plasma ∂ 13 C was enriched over red blood cells in wild birds especially those with low fat stores, which suggested birds with low energy stores were shifting diets. Black Ducks can compensate for disturbances in feeding by increasing intakes if they have access to high quality wetlands where they are able to find abundant food. High energy demands at cold temperatures may constrain fat stores and thus the tolerance of feeding disturbances especially at the northern limits of the winter range. We hypothesize that decreasing variation in diet may indicate an increase in vulnerability to disturbance in winter when body fat is low. Recent efforts to assess and improve habitat quality of Black Ducks could be enhanced by monitoring the body composition and diet of birds to assess their vulnerability to disturbances in food supply and energy demands.

Journal of Comparative Physiology B: Biochemical, ↗

USGS1996

Implications of fault constitutive properties for earthquake prediction

The rate- and state-dependent constitutive formulation for fault slip characterizes an exceptional variety of materials over a wide range of sliding conditions. This formulation provides a unified representation of diverse sliding phenomena including slip weakening over a characteristic sliding distance D(c), apparent fracture energy at a rupture front, time- dependent healing after rapid slip, and various other transient and slip rate effects. Laboratory observations and theoretical models both indicate that earthquake nucleation is accompanied by long intervals of accelerating slip. Strains from the nucleation process on buried faults generally could not be detected if laboratory values of D, apply to faults in nature. However, scaling of D(c) is presently an open question and the possibility exists that measurable premonitory creep may precede some earthquakes. Earthquake activity is modeled as a sequence of earthquake nucleation events. In this model, earthquake clustering arises from sensitivity of nucleation times to the stress changes induced by prior earthquakes. The model gives the characteristic Omori aftershock decay law and assigns physical interpretation to aftershock parameters. The seismicity formulation predicts large changes of earthquake probabilities result from stress changes. Two mechanisms for foreshocks are proposed that describe observed frequency of occurrence of foreshock-mainshock pairs by time and magnitude. With the first mechanism, foreshocks represent a manifestation of earthquake clustering in which the stress change at the time of the foreshock increases the probability of earthquakes at all magnitudes including the eventual mainshock. With the second model, accelerating fault slip on the mainshock nucleation zone triggers foreshocks.

Conference Paper↗