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At least 253 records · Page 14Linked to original sources

USGS2011

Stopover ecology of a migratory ungulate

1. Birds that migrate long distances use stopover sites to optimize fuel loads and complete migration as quickly as possible. Stopover use has been predicted to facilitate a time-minimization strategy in land migrants as well, but empirical tests have been lacking, and alternative migration strategies have not been considered. 2. We used fine-scale movement data to evaluate the ecological role of stopovers in migratory mule deer Odocoileus hemionus — a land migrant whose fitness is strongly influenced by energy intake rather than migration speed. 3. Although deer could easily complete migrations (range 18–144 km) in several days, they took an average of 3 weeks and spent 95% of that time in a series of stopover sites that had higher forage quality than movement corridors. Forage quality of stopovers increased with elevation and distance from winter range. Mule deer use of stopovers corresponded with a narrow phenological range, such that deer occupied stopovers 44 days prior to peak green-up, when forage quality was presumed to be highest. Mule deer used one stopover for every 5∙3 and 6∙7 km travelled during spring and autumn migrations, respectively, and used the same stopovers in consecutive years. 4. Study findings indicate that stopovers play a key role in the migration strategy of mule deer by allowing individuals to migrate in concert with plant phenology and maximize energy intake rather than speed. Our results suggest that stopover use may be more common among non-avian taxa than previously thought and, although the underlying migration strategies of temperate ungulates and birds are quite different, stopover use is important to both. 5. Exploring the role of stopovers in land migrants broadens the scope of stopover ecology and recognizes that the applied and theoretical benefits of stopover ecology need not be limited to avian taxa.

Journal of Animal Ecology↗

USGS2006

Relative Coastal Change-Potential Assessment of Glacier Bay National Park and Preserve

A change-potential index (CPI) was used to map the relative coastal change-potential of the shoreline to future sea-level fluctuation within Glacier Bay National Park and Preserve (GBNPP) in southeastern Alaska. The CPI ranks the following in terms of their physical contribution to coastal change: geomorphology, regional coastal slope, rate of relative sea-level change, historical shoreline change rates, mean tidal range and mean significant wave height. The rankings for each input variable were combined, and an index value calculated for 1-minute grid cells covering the park. The CPI highlights those regions where the physical effects of sea-level and coastal change might be the greatest. This approach combines the coastal system's potential for change with its natural ability to adapt to changing environmental conditions, yielding a quantitative, although relative, measure of the park's natural susceptibility to the effects of sea-level variation. The CPI provides an objective method for evaluation and long-term planning by scientists and park managers. The CPI was developed from a Coastal Vulnerability Index (CVI) typically applied to coastlines experiencing long-term sea-level rise. The CPI is modified from the CVI and applied to the emergent coast of GBNPP to understand the limits of applying this type of assessment method in a variety of sea level settings. GBNPP consists of sand and gravel beaches, rock cliffs, calving glaciers, mudflats, and alluvial fans. The areas within GBNPP that are likely to be most susceptible to coastal change as a result of sea-level change are tidewater glaciers and outer coast shorelines of unconsolidated sediment where wave energy is highest and the regional coastal slope is shallowest.

Open-File Report↗

USGS1997

Hydrogeology and ground-water flow in the Edwards-Trinity aquifer-system, west-central, Texas

Two finite-element ground-water flow models were developed for the Edwards–Trinity aquifer system, west-central Texas, to gain a better understanding of the flow system; one ground-water flow model was developed at a large scale to simulate the regional system and contiguous, hydraulically connected units, and one model was constructed at a smaller more detailed scale to simulate the most active areas of the system. The study area is divided into four geographic subareas: the Trans-Pecos (9,750 square miles), the Edwards Plateau (23,750 square miles), the Hill Country (5,500 square miles), and the Balcones fault zone (3,000 square miles). The major aquifers within the study area are the Edwards–Trinity aquifer underlying the Trans-Pecos and Edwards Plateau, the Trinity aquifer underlying the Hill Country, and the Edwards aquifer in the Balcones fault zone. Hydraulically connected aquifers include the High Plains aquifer north of the Edwards Plateau, and the Cenozoic Pecos alluvium aquifer adjacent to both the Trans-Pecos and the Edwards Plateau along the Pecos River. Minor contiguous aquifers include the Dockum, Ellenburger– San Saba, Marble Falls, Hickory, and Lipan, which is adjacent to the Colorado River in Tom Green and Concho Counties, Texas. The ground-water flow equations solved by the finite-element method are based on conservation of mass and energy. The equation for ground-water flow assumes laminar flow through a porous media. In places, the Edwards–Trinity aquifer system is a fractured karst system in which ground water flows through caverns and other features of secondary porosity development. The regional and subregional models were constructed to synthesize the known hydrologic boundaries and geologic structures into a heterogeneous continuum model of the karst ground-water flow system, rather than simulate the flow through specific fractures and caverns. A heterogeneous continuum or equivalent porous media approach uses an effective transmissivity and anisotropy for each element of the models. The models are calibrated both on water levels (representing potential energy) and estimates of recharge and discharge (for a realistic mass balance). A two-dimensional one-layer large-scale model (55,600 square miles) was developed for the Edwards–Trinity aquifer system and contiguous, hydraulically connected units, in westcentral Texas. A quasi-three-dimensional, multilayer more detailed scale ground-water flow model (12,300 square miles) was applied to the major aquifers of the Edwards–Trinity aquifer system in the Hill Country and the Balcones fault zone, and in part of the Edwards Plateau. The ground-water flow system in most of the study area within the Trans-Pecos and Edwards Plateau can be approximated with a one-layer regional model under steady-state conditions. Regionally, the Edwards–Trinity aquifer system in the Trans-Pecos and Edwards Plateau has been relatively static. Potentiometric maps from predevelopment and postdevelopment (winter 1974–75) indicate small differences in water levels. In local areas in the Trans-Pecos (in Pecos and Reeves Counties), ground-water withdrawals have exceeded recharge resulting in more than 300 feet of drawdown. Measurable differences between the 1974 and predevelopment potentiometric surfaces have been observed in small areas in the Trans-Pecos and in the northwestern part of the Edwards Plateau. The largest water-level declines in the Trans-Pecos have been observed in Pecos and Reeves Counties, and declines greater than 300 feet have been measured in Reeves County. Comparison of pre- and postdevelopment water budgets for the regional model indicates that the increase in groundwater withdrawals has captured 20 percent of the water that would have naturally discharged to streams, and 30 percent of the natural discharge to springs after ground-water development. Induced recharge from streams to the ground-water system increased by 12 percent in the postdevelopment simulation compared to the predevelopment simulation.

Texas↗

USGS2023

Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada

Well ER-5-3-2 is part of a well network designed to monitor long-term water levels and radionuclide concentrations downgradient from underground nuclear tests that occurred in Frenchman Flat, an area of the U.S. Department of Energy Nevada National Security Site in southern Nevada. Interpretation of monitoring records for well ER-5-3-2 was confounded by previously unexplained water-level fluctuations in the well hydrograph. This study integrated geologic, hydrologic, and water-chemistry data to evaluate potential stresses and hydrologic conditions that likely affected the well ER-5-3-2 hydrograph. Numerical groundwater models were applied to evaluate four model scenarios: (1) wellbore leakage without recharge, (2) wellbore leakage with recharge, (3) equilibration to vertical heterogeneities between shallow (low transmissivity) and deep (higher transmissivity) carbonate zones, and (4) equilibration to lateral heterogeneities in carbonate rocks. Meteoric recharge was not the cause of the 21-foot (ft) water-level rise in well ER-5-3-2 from 2001 to 2011 or the 4-ft decline from 2012 to 2016. Based on observed water-level fluctuations in nearby wells, the water-level rise and decline from recharge for these periods was less than 3 and 1 ft, respectively. The lateral-heterogeneity scenario is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was a natural water-level reequilibration following the pumping-induced depressurization of a large volume of high transmissivity and low-storage carbonate rock that is surrounded by low transmissivity and high-storage carbonate rock. The lateral-heterogeneity scenario was discounted because simulated water levels cannot match the well ER-5-3-2 hydrograph. Underground nuclear testing and temperature effects were discounted based on hydraulic connections and water-temperature data. Wellbore-leakage scenarios are based on the assumption that the water-level rise was sustained from leakage rates required to cause a localized mounding in the carbonate system near well ER-5-3-2, where the carbonate transmissivity is 530 square feet per day. Even though simulated and measured water levels compare favorably for scenarios of wellbore leakage with and without recharge, large volumes (178–184 million gallons) of groundwater from volcanic rocks would be required to leak into the carbonate system, which is not supported by water-chemistry data. An alternative conceptualization of wellbore leakage is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was sustained by the hydraulic disconnection of well ER-5-3-2 from the carbonate system. The disconnection occurred several months after a constant-rate test in well ER-5-3-2 when carbonate rocks were hydraulically disconnected from the well by either (1) the shifting of sloughed fill in the open hole or (2) the encrusting of carbonate precipitate in the well screen. The hydraulic disconnection effectively sealed the well and caused a 21-ft water-level rise from wellbore leakage during 2001–11. In this case, total wellbore leakage from 2001 to 2011 was about 50 gallons. The 4-ft water-level decline from 2012 to 2016 was conceptualized to have occurred from the slow breaking of the seal and reconnection of the well to the carbonate system. This alternative conceptualization of wellbore leakage was consistent with water-chemistry analyses because the computed wellbore leakage (50 gallons) was small relative to purged volumes (30,000–40,000 gallons) for sampling, and the water chemistry would not be expected to change. The shallow-deep carbonate scenario provided another explanation for the well ER-5-3-2 hydrograph. This scenario is based on the assumption that well-construction effects and vertical heterogeneity of the carbonate system explain the ER-5-3-2 water-level trend. Well-construction effects are attributed to a temporary clogging of the open interval below the well screen that was opened during pumping events, which affected the hydraulic connection of deep transmissive carbonate rocks to the wellbore. The 21-ft water-level rise from 2001 to 2011 was a natural equilibration to shallow, low-transmissivity carbonate rocks during a period when the lower open interval was clogged. The 4-ft decline from 2012 to 2016 represents equilibration between the shallow and deep intervals, because of a partial unclogging of the connection between the two intervals. The low water levels from 2016 to 2021 resulted from pumping for sampling and an unclogging of the open interval so that the low head in the deep carbonate dominated the water level. Despite potential well-construction effects, from either a wellbore leakage or shallow-deep carbonate scenario, samples collected from well ER-5-3-2 are representative of the carbonate system.

Nevada↗

USGS2013

Constraints on behaviour of a mining‐induced earthquake inferred from laboratory rock mechanics experiments

On December 12, 2004, an earthquake of magnitude 2.2, located in the TauTona Gold Mine at a depth of about 3.65 km in the ancient Pretorius fault zone, was recorded by the in-mine borehole seismic network, yielding an excellent set of ground motion data recorded at hypocentral distances of several km. From these data, the seismic moment tensor, indicating mostly normal faulting with a small implosive component, and the radiated energy were measured; the deviatoric component of the moment tensor was estimated to be M0 = 2.3×1012 N·m and the radiated energy ER = 5.4×108 J. This event caused extensive damage along tunnels within the Pretorius fault zone. What rendered this earthquake of particular interest was the underground investigation of the complex pattern of exposed rupture surfaces combined with laboratory testing of rock samples retrieved from the ancient fault zone (Heesakkers et al.2011a, 2011b). Event 12/12 2004 was the result of fault slip across at least four nonparallel fault surfaces; 25 mm of slip was measured at one location on the rupture segment that is most parallel with a fault plane inferred from the seismic moment tensor, suggesting that this segment accounted for much of the total seismic deformation. By applying a recently developed technique based on biaxial stick-slip friction experiments (McGarr2012, 2013) to the seismic results, together with the 25 mm slip observed underground, we estimated a maximum slip rate of at least 6.6 m/s, which is consistent with the observed damage to tunnels in the rupture zone. Similarly, the stress drop and apparent stress were found to be correspondingly high at 21.9 MPa and 6.6 MPa, respectively. The ambient state of stress, measured at the approximate depth of the earthquake but away from the influence of mining, in conjunction with laboratory measurements of the strength of the fault zone cataclasites, indicates that during rupture of the M 2.2 event, the normal stress acting on the large-slip fault segment was about 260 MPa, the yield stress was 172 MPa and the seismic efficiency was 0.05. Thus, for event 12/12 2004, 5% of the energy released by the earthquake was radiated and the remaining 95% was consumed in overcoming fault friction and expanding the zone of rupture.

Conference Paper↗

USGS2024

Restoration monitoring metric framework: Integrating innovative remote-sensing technologies: Comparisons between field and remotely sensed vegetation surveys of restored forested and grassland sites in Ohio

Restoration monitoring is generally perceived as costly and time-consuming, yet the concept of universal restoration monitoring metrics is trending for evaluation of restoration performance across spatial scales, project boundaries, and jurisdictions. Natural Resource Damage Assessment and Restoration (NRDAR) practitioners seek to restore natural resources injured by oil spills or hazardous substance releases into the environment. Therefore, a multiagency team [US Army Engineer Research and Development Center (ERDC), US Department of the Interior (DOI), and US Department of Energy (DOE)] developed and field-tested a multitiered monitoring framework, illustrating a range of field and remote-sensing techniques and methodologies. The restoration monitoring framework and field demonstration offer a unique methodology to acquire and evaluate simultaneously collected, multiscale/multiplatform data. The result of this research provides new insights to (1) assist planning, implementing, and monitoring restoration progress and effectiveness; and (2) apply common monitoring methods, endpoints, and metrics to other types of ecosystem restoration initiatives. Although the aim was to inform monitoring and management of areas that had been injured, these methods could also be used to inform restoration monitoring practices in a broader context, benefiting environmental stewardship missions of all project partners.

Final Technical Report↗

USGS1988

Linear solvation energy relationships for toxicity of selected organic chemicals to Daphnia pulex and Daphnia magna

In the Laurentian Great Lakes, more than 300 contaminants have been identified in fish, other biota, water, and sediment. Current hazard assessment of these chemicals by the National Fisheries Research Center-Great Lakes is based on their toxicity, occurrence in the environment, and source. Although scientists at the Center have tested over 70 chemicals with the crustacean Daphnia pulex , the number of experimental data needed to screen the huge array of chemicals in the Great Lakes exceeds the practical capabilities of conducting bioassays. This limitation can be partly circumvented, however, by using mathematical models based on quantitative structure-activity relationships (QSAR) to provide rapid, inexpensive estimates of toxicity. Many properties of chemicals, including toxicity, bioaccumulation and water solubility are well correlated and can be predicted by equations of the generalized linear solvation energy relationships (LSER). The equation we used to model solute toxicity is Toxicity = constant + m VI/100 + s (π* + dδ) + b βm + a αm where VI = intrinsic (Van der Waals) molar volume; π* = molecular dipolarity/polarizability; δ = polarizability 'correction term'; βm = solute hydrogen bond acceptor basicity; and αm = solute hydrogen bond donor acidity. The subscript m designates solute monomer values for α and β. We applied the LSER model to 48-h acute toxicity data (measured as immobilization) for six classes of chemicals detected in Great Lakes fish. The following regression was obtained for Daphnia pulex (concentration = μM): log EC50 = 4.86 - 4.35 VI/100; N = 38, r2 = 0.867, sd = 0.403 We also used the LSER modeling approach to analyze to a large published data set of 24-h acute toxicity for Daphnia magna ; the following regression resulted, for eight classes of compounds (concentration = mM): log EC50 = 3.88 - 4.52 VI/100 - 1.62 π* + 1.66 βm - 0.916 αm; N = 62, r2 = 0.859, sd = 0.375 In addition we developed computer software that identifies chemical structures, estimates the LSER parameters, and predicts toxicity. The LSER models promise to be effective in differentiating between reactive and nonreactive toxicity behavior where other models have failed. Contaminants with reactive behavior are generally the most toxic and rank highest in hazard assessment of environmental chemicals.

Proceedings of the QSAR↗

USGS2013

An automated cross-correlation based event detection technique and its application to surface passive data set

In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

Geophysical Prospecting↗

USGS2009

Web-Based Geospatial Tools to Address Hazard Mitigation, Natural Resource Management, and Other Societal Issues

Federal, State, and local government agencies in the United States face a broad range of issues on a daily basis. Among these are natural hazard mitigation, homeland security, emergency response, economic and community development, water supply, and health and safety services. The U.S. Geological Survey (USGS) helps decision makers address these issues by providing natural hazard assessments, information on energy, mineral, water and biological resources, maps, and other geospatial information. Increasingly, decision makers at all levels are challenged not by the lack of information, but by the absence of effective tools to synthesize the large volume of data available, and to utilize the data to frame policy options in a straightforward and understandable manner. While geographic information system (GIS) technology has been widely applied to this end, systems with the necessary analytical power have been usable only by trained operators. The USGS is addressing the need for more accessible, manageable data tools by developing a suite of Web-based geospatial applications that will incorporate USGS and cooperating partner data into the decision making process for a variety of critical issues. Examples of Web-based geospatial tools being used to address societal issues follow.

Fact Sheet↗

USGS2007

Visualization and Time-Series Analysis of Ground-Water Data for C-Area, Savannah River Site, South Carolina, 1984-2004

In 2004, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, initiated a study of historical ground-water data of C-Area on the Savannah River Site in South Carolina. The soils and ground water at C-Area are contaminated with high concentrations of trichloroethylene and lesser amounts of tetrachloroethylene. The objectives of the investigation were (1) to analyze the historical data to determine if data-mining techniques could be applied to the historical database to ascertain whether natural attenuation of recalcitrant contaminants, such as volatile organic compounds, is occurring and (2) to determine whether inferential (surrogate) analytes could be used for more cost-effective monitoring. Twenty-one years of data (1984-2004) were collected from 396 wells in the study area and converted from record data to time-series data for analysis. A Ground-Water Data Viewer was developed to allow users to spatially and temporally visualize the analyte data. Overall, because the data were temporally and spatially sparse, data analysis was limited to only qualitative descriptions.

South Carolina↗

USGS1981

Economics and coal resource appraisal: strippable coal in the Illinois Basin ( USA)

Coal-resource appraisals generally describe the location and general characteristics of coal beds. Estimates are made of the average overburden depth (depth of the coal bed below the surface), bed thickness, and perhaps certain chemical properties of the coal [1]. Although such resource compilations represent an important initial step, neither they nor current estimates provide sufficient information to determine the costs of alternative options for National energy policy. Because coal is expected to provide an increasing part of future overall U.S. energy supply, it is crucial for long term planning that coalresource appraisals convey sufficient information regarding the degree of economic resource scarcity (escalation of unit costs for mining remaining deposits as the best deposits in an area are mined out) expected as coal consumption increases. However, assumptions embodied in most large-scale models of coal supply [13; 20] imply that the coal reserves that exist can be commercially produced as needed. As demonstrated by the embargo of 1973-1974 and more recent difficulties in obtaining crude oil, even a slight temporary commodity shortfall will result in significant economic losses when the commodity supplies a large proportion of the total energy used by an economy. For the United States, crude oil resource estimates did not give warning of a decline in domestic petroleum product. In this paper we argue that coal-resource estimates, as they are now made, will not give warning of future supply difficulties. A method for incorporating an economic dimension into appraisals of strippable coal resources is presented and is applied to a major U.S. coal-producing region, the Illinois part of the Illinois basin. Illinois accounts for nearly 70% of the demonstrated strippable coal reserve base of the Illinois basin [12]. In particular, a long-run incremental cost function (that is unit costs vs. cumulative reserves extracted) is estimated for strippable coal in Illinois. The estimated cost function exhibits an initial range over which costs increase at a constant rate-followed by a range where costs increase very rapidly and the function becomes quite inelastic. This long-run incremental cost function is significant for two reasons. Comparison of the demonstrated reserve base for strippable coal (14.8 billion tons) with cumulative production (since 1920 of 1.1 billion tons) might suggest that future depletion will not be significant when, in fact, the cost function presented here indicates otherwise. Because the only states having more reserves of strippable coal than Illinois are Montana and Wyoming [18], these results have implications for national coal-resource appraisal. Secondly, most models used to study the effects of alternative public policies in coal markets are static in nature [15; 16] and cannot consider the effects of increasing costs. Furthermore, models which are multi-period in nature [11; 13] appear to have little empirical basis for their assumptions regarding the escalation of production costs resulting from depletion. The plan of the paper is as follows. First a description of the analytical approach for constructing the long-run incremental cost-reserve function is discussed. Following this, the descriptions of the Illinois basin and the basic physical data are presented. In the concluding section, the main results are presented and their implications are explored

Southern Economic Journal↗

USGS1983

The past is the key to the future

A new major frontier of geological research, which was initiated in the 1970's, involves predicting future geologic trends or events through study of the present and past, rather than trying to understand the past, often using what one knows about the present. Like most scientific frontiers, this one began from practical considerations—environmental concerns. The lack of formal recognition of this frontier results from fragmentation among many Federal agencies and highly focused mission-oriented programs ( e.g. , earthquake prediction, CO 2 , nuclear-energy safety, etc.). Most programs aim to predict only the next 50–100 years, but much longer periods of the past need to be studied to do this. Nuclear-waste disposal has sometimes been considered in terms of the next million years, a period of time permitting significant and broad geologic changes. Decreasing public interest in environmental concerns relegates many questions from the realm of applied research back to that of basic research. Most of these questions are so fascinating, however, that the frontier is still worth pursuing. Such questions include whether a phenomenon will or will not take place and the rates at which it can develop ( e.g. , how fast do rifts form, how fast can a caldera event begin, and how quickly can a glacial maximum arrive?). Common elements of all studies include the historic record, trends in the Quaternary, analogues in various periods of the geologic time scale, and allowance for phenomena never experienced before. Other examples of studies include the Cretaceous as a period of a climatic extreme, an especially interesting time period; establishing the amount of paleocloudiness, a particularly challenging and important research area; acid rain as a possible new phenomenon. Geochemistry has much to contribute to this frontier science.

Geochimica et Cosmochimica Acta↗

USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗

USGS2018

Development of new information to inform fish passage decisions at the Yale and Merwin hydro projects on the Lewis River, Washington—Final report, 2018

The reintroduction of extirpated salmonids to historically occupied areas is becoming increasingly common as a conservation and recovery strategy. Often, reintroductions are implemented after the factors that originally led to species extirpation have been reduced, eliminated, or mitigated. For anadromous Oncorhynchus spp. (Pacific salmon) and O. mykiss (steelhead), addressing barriers to migration, which have been a primary factor in the decline and extirpation of many populations, has been an integral component of recovery efforts. Mitigation has included barrier removal, developing fish passage opportunities, and (or) actively trapping and hauling juvenile and adult anadromous salmonids around barriers. With any reintroduction, there are a number of concerns regarding the ecological impact of the reintroduction efforts. Three of the main tenets to consider when assessing reintroductions are (1) the potential benefits if reintroduction is successful, (2) the biological risk through interactions of reintroduced strains with existing populations, and (3) the factors potentially limiting a successful reintroduction. This report focuses on information and data to address the second and third factors as they apply to the upper Lewis River in Washington. The upper Lewis River historically contained wild populations of O. tshawytscha (Chinook salmon), O. kisutch (coho salmon), and steelhead. These populations were extirpated after completion of hydropower facilities on Lake Merwin in 1932, Yale Lake in 1953, and Swift Reservoir in 1958, which prevented fish from migrating to and from ocean environments. However, recent licenses issued by the Federal Energy Regulatory Commission require the installation and operation of an upstream fish passage facility at Lake Merwin and a downstream fish passage facility at Swift Reservoir. The licenses were developed in consultation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service. The overarching goal of this fish reintroduction project is to establish viable, self-sustaining, naturally reproducing, harvestable populations of spring Chinook salmon, winter steelhead, and coho salmon at levels higher than minimum viable populations. This report uses a combination of field data and existing information to address six key objectives related to the reintroduction in order to inform decisions about passage at the Yale Lake and Lake Merwin hydropower projects. The objectives are (1) a review of information relevant to anadromous fish reintroduction and full fish passage; (2) a habitat assessment of tributaries to Swift Reservoir, Yale Lake, and Lake Merwin; (3) a field study to assess adult potential for spawning success; (4) an assessment of juvenile production and outmigration success; (5) a Lake Merwin predator impact study; and (6) a set of studies assessing interactions between anadromous and resident fish.

Washington↗

USGS2023

Stream temperature prediction in a shifting environment: The influence of deep learning architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process-guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

Delaware River Basin↗

USGS2009

Thiamine content of eggs and lengths of coho salmon (Oncorhynchus kisutch) in relation to abundance of alewife (Alosa pseudoharengus) in eastern Lake ontario, 2003 to 2006

Early mortality syndrome in fry of Great Lakes salmonines is linked to reduced levels of thiamine in eggs, which reflects maternal consumption of forage fishes such as alewife (Alosa pseudoharengus) that contain thiaminase, an enzyme that destroys thiamine. We assessed annual variations in abundance and condition of alewives and thiamine status of coho salmon (Oncorhynchus kisutch) in Lake Ontario. We analyzed total thiamine in eggs of 20 coho salmon collected annually between 2003 and 2006 at the Salmon River Hatchery on the Salmon River, New York. Alewife abundance was assessed annually in southern and eastern Lake Ontario with bottom trawls during late April and early May. Mean thiamine concentration in eggs varied annually, with those collected in 2003 (2.5 nmol/g) being significantly higher than those collected in 2004 to 2006 (1.5 to 1.7 nmol/g). Although we did not test survival of fry, if reported threshold levels of thiamine for preventing mortality of Lake Michigan coho salmon fry apply, then many or most Lake Ontario coho salmon produced fry were likely to incur thiamine-deficiency mortality, especially during years 2004 to 2006. Comparison to indices of annual abundance of alewife in Lake Ontario with thiamine concentration in coho salmon eggs failed to show any significant correlations (P > 0.05). However, total length of female spawning coho salmon was positively correlated (P < 0.05) with increasing condition and estimated energy content of adult alewives in the previous spring. These results suggest that growth of coho salmon in Lake Ontario was first limited by energy intake, whereas the amount of thiamine provided by alewives was sufficient for growth (in length) but not for producing thiamine-adequate eggs.

East Lake Ontario↗

USGS2021

Protocol for route restoration in California’s desert renewable energy conservation plan area

In the deserts of the Southwestern United States, increased off-highway vehicle use can lead to widespread vehicular damage to desert ecosystems. As the popularity and intensity of vehicle use on public lands continues, the Bureau of Land Management (BLM) is challenged to manage the routes used by recreationists while minimizing activity beyond designated routes and mitigating environmental impacts. Ecosystem function and habitat quality can be degraded by vehicle activities, especially when the activities are occurring outside authorized routes or authorized open areas. Restoration mitigates damage to soils and vegetation; however, methods vary across the desert, results appear to be inconsistent, and standardized monitoring plans do not exist. The Desert Renewable Energy Conservation Plan Land Use Plan Amendment to the California Desert Conservation Area Land Use Plan identified the need for, and directed implementation of, standardized monitoring of restoration, which includes minimizing surface disturbance to agency prescribed levels in areas of critical environmental concern and on California Desert National Conservation Lands. To assist the BLM in implementing the Desert Renewable Energy Conservation Plan Land Use Plan Amendment, we define ecological restoration as the process of halting or minimizing future degradation while simultaneously assisting the recovery of ecosystem function and community composition in relation to intact reference sites. The monitoring strategies provided in this protocol are used to restore degraded ecosystems after use of non-routes has ceased (non-designated routes or vehicle-caused linear disturbances) by applying techniques to improve edaphic properties, hydrologic function, and biotic community composition. This protocol also provides criteria that can be used to distinguish the status of non-routes and land parcels as “restored” or “disturbed.” This protocol was developed by the U.S. Geological Survey, in collaboration with BLM restoration practitioners, to identify standard restoration methods and establish criteria to determine when restoration is achieved. This protocol also develops new methods to increase restoration rates and successes on public lands in the southern California deserts. BLM’s long-term implementation plan for the evaluation of road restoration described in this report is to transition toward managing the work, including developing the workforce and long-term storage and management of the data during the next several years. This report is intended to be regularly updated as the program develops.

California↗

USGS2023

Enhancing the predictability of ecology in a changing world: A call for an organism-based approach

Ecology is usually very good in making descriptive explanations of what is observed, but is often unable to make predictions of the response of ecosystems to change. This has implications in a human-dominated world where a suite of anthropogenic stresses are threatening the resilience and functioning of ecosystems that sustain mankind through a range of critical regulating and supporting services. In ecosystems, cause-and-effect relationships are difficult to elucidate because of complex networks of negative and positive feedbacks. Therefore, being able to effectively predict when and where ecosystems could pass into different (and potentially unstable) new states is vitally important under rapid global change. Here, we argue that such better predictions may be reached if we focus on organisms instead of species, because organisms are the principal biotic agents in ecosystems that react directly on changes in their environment. Several studies show that changes in ecosystems may be accurately described as the result of changes in organisms and their interactions. Organism-based theories are available that are simple and derived from first principles, but allow many predictions. Of these we discuss Trait-based Ecology, Agent Based Models, and Maximum Entropy Theory of Ecology and show that together they form a logical sequence of approaches that allow organism-based studies of ecological communities. Combining and extending them makes it possible to predict the spatiotemporal distribution of groups of organisms in terms of how metabolic energy is distributed over areas, time, and resources. We expect that this “Organism-based Ecology” (OE) ultimately will improve our ability to predict ecosystem dynamics.

Frontiers in Applied Mathematics and Statistics↗