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USGS2013

A quantitative analysis of the state of knowledge of turtles of the United States and Canada

The “information age” ushered in an explosion of knowledge and access to knowledge that continues to revolutionize society. Knowledge about turtles, as measured by number of published papers, has been growing at an exponential rate since the early 1970s, a phenomenon mirrored in all scientific disciplines. Although knowledge about turtles, as measured by number of citations for papers in scientific journals, has been growing rapidly, this taxonomic group remains highly imperiled suggesting that knowledge is not always successfully translated into effective conservation of turtles. We reviewed the body of literature on turtles of the United States and Canada and found that: 1) the number of citations is biased toward large-bodied species, 2) the number of citations is biased toward wide-ranging species, and 3) conservation status has little effect on the accumulation of knowledge for a species, especially after removing the effects of body size or range size. The dispersion of knowledge, measured by Shannon Weiner diversity and evenness indices across species, was identical from 1994 to 2009 suggesting that poorly studied species remained poorly-studied species while well-studied species remained well studied. Several species listed as threatened or endangered under the U.S. Endangered Species Act (e.g., Pseudemys alabamensis, Sternotherus depressus, and Graptemys oculifera) remain poorly studied with the estimated number of citations for each ranging from only 13-24. The low number of citations for these species could best be explained by their restricted distribution and/or their smaller size. Despite the exponential increase in knowledge of turtles in the United States and Canada, no species of turtle listed under the Endangered Species Act has ever been delisted for reason of recovery. Therefore, increased knowledge does not necessarily contribute appreciably to recovery of threatened turtles.

Amphibia-Reptilia↗

USGS1995

Two-year simulation of the Great Lakes region with a coupled modeling system

In this paper, we report on an experiment aimed at evaluating the feasibility of the application of our coupled regional climate modeling system to long-term climate simulations over the Great Lakes region. The simulation analyzed covers a continuous 24-month period beginning 1 September 1990 and extending to 1 September 1992. Many aspects of this simulation agreed well with observations. Compared with European Centre for Medium-Range Weather Forecasts (ECMWF) analyses, area-averaged atmospheric temperature and moisture biases were generally small. The largest temperature biases were found in the simulated boundary layer, up to 1–1.5 K colder than observed in most months. Atmospheric moisture biases were of both signs and small in magnitude, almost universally less than 0.5 g kg −1 . Comparison of simulated surface air temperatures with station observations also indicated that model simulated temperatures generally display a cold bias. Simulated precipitation values agreed well with observations during the cold portions of the year while during warm months precipitation was overpredicted by 10%–50%. Spatial patterns of precipitation over the model domain agreed well with observations during the winter months but were not as well simulated during the other seasons. A one-dimensional lake model was coupled to the atmospheric component of the model to capture the effects of the Great Lakes on regional climate. Lake surface temperatures were generally well simulated by the lake model in the summer and fall seasons, and lake ice extent agreed well with the analysis over at least three of the five lakes. The greatest shortcomings in lake temperature simulation were the earlier-than-observed warm-up in the spring and warmer than observed peak temperatures in the summer over the northern portions of the lakes. Also, lake ice extent was generally overpredicted over Lake Superior and underpredicted over Lake Erie. In summary, the coupled modeling system described in this paper shows promise for use in climate simulators over regions where lakes are important such as the Great Lakes. It has been shown that many aspects of the simulation are in good agreement with available observations. Areas in which the results point to the need for further work are the model's convective parameterization, the eddy diffusivities in the lake model, and the treatment of clouds in the radiation package.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS2004

Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3°C . In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases he accuracy of precipitation forecasts over the northeastern United States, but overall, the accuracy of MOS-based precipitation forecasts is slightly lower than the raw NCEP forecasts. Four basins in the United States were chosen as case studies to evaluate the value of MRF output for predictions of streamflow. Streamflow forecasts using MRF output were generated for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado: East Fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). Hydrologic model output forced with measured-station data were used as "truth" to focus attention on the hydrologic effects of errors in the MRF forecasts. Eight-day streamflow forecasts produced using the MOS-corrected MRF output as input (MOS) were compared with those produced using the climatic Ensemble Streamflow Prediction (ESP) technique. MOS-based streamflow forecasts showed increased skill in the snowmelt-dominated river basins, where daily variations in streamflow are strongly forced by temperature. In contrast, the skill of MOS forecasts in the rainfall-dominated basin (the Alapaha River) were equivalent to the skill of the ESP forecasts. Further improvements in streamflow forecasts require more accurate local-scale forecasts of precipitation and temperature, more accurate specification of basin initial conditions, and more accurate model simulations of streamflow.

Journal of Hydrometeorology↗

USGS2011

Watershed-scale response to climate change through the twenty-first century for selected basins across the United States

The hydrologic response of different climate-change emission scenarios for the twenty-first century were evaluated in 14 basins from different hydroclimatic regions across the United States using the Precipitation-Runoff Modeling System (PRMS), a process-based, distributed-parameter watershed model. This study involves four major steps: 1) setup and calibration of the PRMS model in 14 basins across the United States by local U.S. Geological Survey personnel; 2) statistical downscaling of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 climate-change emission scenarios to create PRMS input files that reflect these emission scenarios; 3) run PRMS for the climate-change emission scenarios for the 14 basins; and 4) evaluation of the PRMS output. This paper presents an overview of this project, details of the methodology, results from the 14 basin simulations, and interpretation of these results. A key finding is that the hydrological response of the different geographical regions of the United States to potential climate change may be very different, depending on the dominant physical processes of that particular region. Also considered is the tremendous amount of uncertainty present in the climate emission scenarios and how this uncertainty propagates through the hydrologic simulations. This paper concludes with a discussion of the lessons learned and potential for future work.

Earth Interactions↗

USGS2005

An alternative approach to characterize nonlinear site effects

This paper examines the rationale of a method of nonstationary processing and analysis, referred to as the Hilbert-Huang transform (HHT), for its application to a recording-based approach in quantifying influences of soil nonlinearity in site response. In particular, this paper first summarizes symptoms of soil nonlinearity shown in earthquake recordings, reviews the Fourier-based approach to characterizing nonlinearity, and offers justifications for the HHT in addressing nonlinearity issues. This study then uses the HHT method to analyze synthetic data and recordings from the 1964 Niigata and 2001 Nisqually earthquakes. In doing so, the HHT-based site response is defined as the ratio of marginal Hilbert amplitude spectra, alternative to the Fourier-based response that is the ratio of Fourier amplitude spectra. With the Fourier-based approach in studies of site response as a reference, this study shows that the alternative HHT-based approach is effective in characterizing soil nonlinearity and nonlinear site response.

Earthquake Spectra↗

USGS2006

Real-time seismic monitoring of the new Cape Girardeau Bridge and preliminary analyses of recorded data: An overview

This paper introduces the state-of-the-art seismic monitoring system implemented for the 1,206-m-long (3,956 ft ) cable-stayed Bill Emerson Memorial Bridge in Cape Girardeau (Missouri), a new Mississippi River crossing, approximately 80 km from the epicentral region of the 1811 and 1812 New Madrid earthquakes. The real-time seismic monitoring system for the bridge includes a broadband network consisting of superstructure and free-field arrays and comprises a total of 84 channels of accelerometers deployed on the superstructure (towers and deck), pier foundations (caisson tops and bents), and in the vicinity of the bridge (e.g., free-field, both surface and downhole). The paper also introduces the high-quality response data obtained from the broadband network that otherwise would not have been possible with older instruments. Such data is aimed to be used by the owner, researchers, and engineers to (1) assess the performance of the bridge, (2) check design parameters, including the comparison of dynamic characteristics with actual response, and (3) better design future similar bridges. Preliminary spectral analyses of low-amplitude ambient vibration data and that from a small earthquake reveal specific response characteristics of this new bridge and the free-field in its proximity. There is coherent tower-cable-deck interaction that sometimes results in amplified ambient motions. Also, while the motions at the lowest (triaxial) downhole accelerometers on both Missouri and Illinois sides are practically free from any feedback of motions of the bridge, the motions at the middle downhole and surface accelerometers are influenced significantly even by amplified ambient motions of the bridge.

Missouri↗

USGS2011

Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice

The ground-motion prediction equations (GMPEs) developed as part of the Next Generation Attenuation of Ground Motions (NGA-West) project in 2008 are becoming widely used in seismic hazard analyses. However, these new models are considerably more complicated than previous GMPEs, and they require several more input parameters. When employing the NGA models, users routinely face situations in which some of the required input parameters are unknown. In this paper, we present a framework for estimating the unknown source, path, and site parameters when implementing the NGA models in engineering practice, and we derive geometrically-based equations relating the three distance measures found in the NGA models. Our intent is for the content of this paper not only to make the NGA models more accessible, but also to help with the implementation of other present or future GMPEs.

Earthquake Spectra↗

USGS2014

Damping scaling factors for elastic response spectra for shallow crustal earthquakes in active tectonic regions: "average" horizontal component

Ground motion prediction equations (GMPEs) for elastic response spectra are typically developed at a 5% viscous damping ratio. In reality, however, structural and nonstructural systems can have other damping ratios. This paper develops a new model for a damping scaling factor (DSF) that can be used to adjust the 5% damped spectral ordinates predicted by a GMPE for damping ratios between 0.5% to 30%. The model is developed based on empirical data from worldwide shallow crustal earthquakes in active tectonic regions. Dependencies of the DSF on potential predictor variables, such as the damping ratio, spectral period, ground motion duration, moment magnitude, source-to-site distance, and site conditions, are examined. The strong influence of duration is captured by the inclusion of both magnitude and distance in the DSF model. Site conditions show weak influence on the DSF. The proposed damping scaling model provides functional forms for the median and logarithmic standard deviation of DSF, and is developed for both RotD50 and GMRotI50 horizontal components. A follow-up paper develops a DSF model for vertical ground motion.

Earthquake Spectra↗

USGS2013

Spatially explicit models for inference about density in unmarked or partially marked populations

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

Annals of Applied Statistics↗

USGS2001

Online bibliographic sources in hydrology

Traditional commercial bibliographic databases and indexes provide some access to hydrology materials produced by the government; however, these sources do not provide comprehensive coverage of relevant hydrologic publications. This paper discusses bibliographic information available from the federal government and state geological surveys, water resources agencies, and depositories. In addition to information in these databases, the paper describes the scope, styles of citing, subject terminology, and the ways these information sources are currently being searched, formally and informally, by hydrologists. Information available from the federal and state agencies and from the state depositories might be missed by limiting searches to commercially distributed databases.

Science and Technology Libraries↗

USGS2016

Defining ecosystem assets for natural capital accounting

In natural capital accounting, ecosystems are assets that provide ecosystem services to people. Assets can be measured using both physical and monetary units. In the international System of Environmental-Economic Accounting, ecosystem assets are generally valued on the basis of the net present value of the expected flow of ecosystem services. In this paper we argue that several additional conceptualisations of ecosystem assets are needed to understand ecosystems as assets, in support of ecosystem assessments, ecosystem accounting and ecosystem management. In particular, we define ecosystems’ capacity and capability to supply ecosystem services, as well as the potential supply of ecosystem services. Capacity relates to sustainable use levels of multiple ecosystem services, capability involves prioritising the use of one ecosystem service over a basket of services, and potential supply considers the ability of ecosystems to generate services regardless of demand for these services. We ground our definitions in the ecosystem services and accounting literature, and illustrate and compare the concepts of flow, capacity, capability, and potential supply with a range of conceptual and real-world examples drawn from case studies in Europe and North America. Our paper contributes to the development of measurement frameworks for natural capital to support environmental accounting and other assessment frameworks.

PLoS ONE↗

USGS2024

Design, development, and implementation of IsoBank: A centralized repository for isotopic data

Stable isotope data have made pivotal contributions to nearly every discipline of the physical and natural sciences. As the generation and application of stable isotope data continues to grow exponentially, so does the need for a unifying data repository to improve accessibility and promote collaborative engagement. This paper provides an overview of the design, development, and implementation of IsoBank , a community-driven initiative to create an open-access repository for stable isotope data implemented online in 2021. A central goal of IsoBank is to provide a web-accessible database supporting interdisciplinary stable isotope research and educational opportunities. To achieve this goal, we convened a multi-disciplinary group of over 40 analytical experts, stable isotope researchers, database managers, and web developers to collaboratively design the database. This paper outlines the main features of IsoBank and provides a focused description of the core metadata structure. We present plans for future database and tool development and engagement across the scientific community. These efforts will help facilitate interdisciplinary collaboration among the many users of stable isotopic data while also offering useful data resources and standardization of metadata reporting across eco-geoinformatics landscapes.

PLoS ONE↗

USGS2025

Climate change effects on ecosystem services: Disentangling drivers of mixed responses

Climate change is a pervasive hazard that impacts the supply and demand of ecosystem goods and services (EGS) that maintain human well-being. A recent review found that the impacts of climate change on EGS are sometimes mixed, posing challenges for managers who need to adapt to these changes. We expand on earlier work by exploring drivers of varying responses of EGS to climate within studies. We conducted a systematic review of English-language papers directly assessing climate change impacts on the supply, demand, or monetary value of ‘provisioning EGS’, ‘regulating EGS’, or ‘cultural EGS’. Ultimately, 44 papers published from December 2014 to March 2018 were analyzed. Nearly 66% of EGS were assessed for higher-income countries despite how lower-income countries disproportionately face negative climate impacts. Around 59% of observations or projections were mixed responses of EGS to climate change. Differences in climate impacts to EGS across space or climate scenarios were the most common causes of mixed responses, followed by mixed responses across time periods assessed. Disaggregating findings by drivers is valuable because mixed responses were often due to multiple drivers of variation. Carefully considering the decision context and desired outcome of a study will help select appropriate methodology to detect EGS variation. Although studies have often assessed relevant drivers of variation, assessing interactions of other sources of uncertainty and both climate and non-climate drivers may support more effective management decisions that holistically account for different values in the face of uncertainty.

PLoS↗

USGS2005

Initial results of rover localization and topographic mapping for the 2003 mars exploration rover mission

This paper presents the initial results of lander and rover localization and topographic mapping of the MER 2003 mission (by Sol 225 for Spirit and Sol 206 for Opportunity). The Spirit rover has traversed a distance of 3.2 km (actual distance traveled instead of odometry) and Opportunity at 1.2 km. We localized the landers in the Gusev Crater and on the Meridiani Planum using two-way Doppler radio positioning technology and cartographic triangulations through landmarks visible in both orbital and ground images. Additional high-resolution orbital images were taken to verify the determined lander positions. Visual odometry and bundle-adjustment technologies were applied to overcome wheel slippages, azimuthal angle drift and other navigation errors (as large as 21 percent). We generated timely topographic products including 68 orthophoto maps and 3D Digital Terrain Models, eight horizontal rover traverse maps, vertical traverse profiles up to Sol 214 for Spirit and Sol 62 for Opportunity, and five 3D crater models. A web-based landing-site Geographic Information System (GIS) has been set up at The Ohio State University to update and disseminate the daily localization and topographic information to support tactical and strategic operations of the mission. Also described in this paper are applications of the data for science operations planning, geological traverse survey, survey of wind-related features, and other science applications. The majority of the instruments onboard both rovers are healthy at this moment, and they will continue to explore the two landing sites on the Martian surface. We expect to report further localization and topographic mapping results to be achieved in the rest of the mission period and in post-mission data processing.

Photogrammetric Engineering and Remote Sensing↗

USGS2009

Spectral distance decay

Remotely sensed data represents key information for character-izing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance may allow us to quantitatively estimate how beta-diversity in species changes with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological datasets are characterized by a high number of zeroes that can add noise to the regression model. Quantile regression can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this paper, we used ordinary least square (OLS) and quantile regression to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.05) considering both OLS and quantile regression. Nonetheless, OLS regression estimate of mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when spectral distance approaches zero, was very low compared with the intercepts of upper quantiles, which detected high species similarity when habitats are more similar. In this paper we demonstrated the power of using quantile regressions applied to spectral distance decay in order to reveal species diversity patterns otherwise lost or underestimated by ordinary least square regression.

Photogrammetric Engineering and Remote Sensing↗

USGS2009

Developing collaborative classifiers using an expert-based model

This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada.

Nevada↗

USGS2009

Area sensitivity in North American grassland birds: Patterns and processes

Grassland birds have declined more than other bird groups in North America in the past 35-40 years (Vickery and Herkert 2001, Sauer et al. 2008), prompting a wide variety of research aimed at understanding these declines, as well as conservation programs trying to reverse the declines (Askins et al. 2007). Area sensitivity, whereby the pattern of a species’ occurrence and density increases with patch area (Robbins et al. 1989), has been invoked as an important issue in grassland-bird conservation, and understanding the processes that drive area sensitivity in grassland birds is a major conservation need (Vickery and Herkert 2001). Here, we review the literature on North American grassland bird species that is relevant to the following questions: (1) What is the evidence for area sensitivity in grassland birds? (2) What are the historical explanations for area sensitivity? (3) What ecological processes could produce area sensitivity? And (5) what are the conservation implications of knowing the processes behind area sensitivity? Because of space limitations, we could not cite every paper we reviewed; the cited papers are given as examples of the literature in this field

The Auk↗

USGS2015

Geological processes and orchid biogeography with applications to southeast central America

This contribution owes its origins to a paper presentation by Dr. Calloway H. Dodson at the Second International Conference on Neotropical Orchidology held in San José, Costa Rica in May of2003 (Dodson 2003). Dr. Dodson outlined some ofthe reasons to suspect that regional geological fac-tors may play important roles in orchid speciation and biogeography and gave examples from the northwestern South America. He also suggested that evolutionary change in orchid might occur over fairly short time periods, perhaps even as short as decades, centuries or millennia (Dodson 2003, SHK lecture notes). These ideas stimulated the author, a professional earth scientist, to begin thinking about how these exciting ideas could begin to be tested in Costa Rica neighboring and Central American countries, an area that has drawn him to return frequently over the last decade. The present contribution is a proposal for integrating geological observations, such as the chronology of arc volcanic activity in Nicaragua,Costa Rica, and Panama, in hypothesis forming and testing of the geographic distribution of orchids (and possibly other biota). I initially focus on comparisons between orchid inventories on the windward slopes of mountainous regions (elevation > 1000 m)with high rainfall (> 1-2 m) in tropical regions, the so-called tropical cloud forests. These regions represent the tropical pre-montane rain forestto lower montane tropical rain forest life zones of Holdridge(1967) and the montane vegetation zone applied to Costa Rica and Panama by Dressler (1993). An important message of this paper is that such tropical mountainous regions are not necessarily static, but may change in elevation over geologic time due to active tectonic deformation and uplift and that the presence of active volcanism in a mountain range may also introduce additional chemical factors, such as volcanic gases, acid rain, and volcanic soils, and also physical factors, such as interruption of gene flow by explosive eruptions and coverage by their air fall products such as ash (tephra), lava flows, and lahars (volcanic mudflows). Thus over a given geological time interval, forests may be slowly increasing in elevation by tectonic uplift or by the accumulation of volcanic products such as steep-sided strato volcanoes (built from both lavas and tephra), or by down-slope accumulations of lava flows or lahars. Mountains may also lose elevation by erosion or by tectonic subsidence. As we shall see, tropical Central America shows an extraordinarily high level of tectonic and volcanic history that has changed its geography and, by implication, climate, life zones,and likely orchid distribution. My working hypo thesis put forward for testing is that orchid adaptations to these changes may have led to the development of new species and endemism in this region.

Lankesteriana↗