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At least 163 records · Page 9Linked to original sources
USGS2020

Forecasting for a fractured land: A case study of the communication and use of aftershock forecasts from the Mw 7.8 2016 Kaikōura earthquake in Aotearoa New Zealand

Operational earthquake forecasts (OEFs) are represented as time‐dependent probabilities of future earthquake hazard and risk. These probabilities can be presented in a variety of formats, including tables, maps, and text‐based scenarios. In countries such as Aotearoa New Zealand, the U.S., and Japan, OEFs have been released by scientific organizations to agencies and the public, with the intent of providing information about future earthquake hazard and risk, so that people can use this information to inform their decisions and activities. Despite questions being raised about the utility of OEF for decision‐making, past earthquake events have shown that agencies and the public have indeed made use of such forecasts. Responses have included making decisions about safe access into buildings, cordoning, demolition safety, timing of infrastructure repair and rebuild, insurance, postearthquake building standards, postevent land‐use planning, and public communication about aftershocks. To add to this body of knowledge, we undertook a survey to investigate how agencies and GNS Science staff used OEFs that were communicated following the M w 7.8 2016 Kaikōura earthquake in Aotearoa New Zealand. We found that agencies utilized OEFs in many of the ways listed previously, and we document individual employee’s actions taken in their home‐life context. Challenges remain, however, regarding the interpretation of probabilistic information and applying this to practical decision‐making. We suggest that science agencies cannot expect nontechnical users to understand and utilize forecasts without additional support. This might include developing a diversity of audience‐relevant OEF information for communication purposes, alongside advice on how such information could be utilized.

northern part of South Island↗
USGS2014

The global dispersion of pathogenic microorganisms by dust storms and its relevance to agriculture

Dust storms move an estimated 500–5000 Tg of soil through Earth’s atmosphere every year. Dust-storm transport of topsoils may have positive effects such as fertilization of aquatic and terrestrial ecosystems and the evolution of soils in proximal and distal environments. Negative effects may include the stripping of nutrient-rich topsoils from source regions, sandblasting of plant life in downwind environments, the fertilization of harmful algal blooms, and the transport of toxins (e.g., metals, pesticides, herbicides, etc.) and pathogenic microorganisms. With respect to the long-range dispersion of microorganisms and more specifically pathogens, research is just beginning to demonstrate the quantity and diversity of organisms that can survive this type of transport. Most studies to date have utilized different assays to identify microorganisms and microbial communities using predominately culture-based, and more recently nonculture-based, methodologies. There is a clear need for international-scale research efforts that apply standardized methods to advance this field of science. Here we present a review of dust-borne microorganisms with a focus on their relevance to agronomy.

Book chapter↗
USGS2011

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples ( n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R 2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Applied and Environmental Soil Science↗
USGS2010

Locating inputs of freshwater to Lynch Cove, Hood Canal, Washington, using aerial infrared photography

The input of freshwater and associated nutrients into Lynch Cove and lower Hood Canal (fig. 1) from sources such as groundwater seeps, small streams, and ephemeral creeks may play a major role in the nutrient loading and hydrodynamics of this low dissolved-oxygen (hypoxic) system. These disbursed sources exhibit a high degree of spatial variability. However, few in-situ measurements of groundwater seepage rates and nutrient concentrations are available and thus may not represent adequately the large spatial variability of groundwater discharge in the area. As a result, our understanding of these processes and their effect on hypoxic conditions in Hood Canal is limited. To determine the spatial variability and relative intensity of these sources, the U.S. Geological Survey Washington Water Science Center collaborated with the University of Washington Applied Physics Laboratory to obtain thermal infrared (TIR) images of the nearshore and intertidal regions of Lynch Cove at or near low tide. In the summer, cool freshwater discharges from seeps and streams, flows across the exposed, sun-warmed beach, and out on the warm surface of the marine water. These temperature differences are readily apparent in aerial thermal infrared imagery that we acquired during the summers of 2008 and 2009. When combined with co-incident video camera images, these temperature differences allow identification of the location, the type, and the relative intensity of the sources.

Fact Sheet↗
USGS2010

Conifer health classification for Colorado, 2008

Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.

Scientific Investigations Map↗
USGS1998

Lake bed classification using acoustic data

As part of our effort to identify the lake bed surficial substrates using remote sensing data, this work designs pattern classifiers by multivariate statistical methods. Probability distribution of the preprocessed acoustic signal is analyzed first. A confidence region approach is then adopted to improve the design of the existing classifier. A technique for further isolation is proposed which minimizes the expected loss from misclassification. The devices constructed are applicable for real-time lake bed categorization. A mimimax approach is suggested to treat more general cases where the a priori probability distribution of the substrate types is unknown. Comparison of the suggested methods with the traditional likelihood ratio tests is discussed.

Applied Mathematics and Computer Science↗
USGS2016

Developing integrated methods to address complex resource and environmental issues

Introduction This circular provides an overview of selected activities that were conducted within the U.S. Geological Survey (USGS) Integrated Methods Development Project, an interdisciplinary project designed to develop new tools and conduct innovative research requiring integration of geologic, geophysical, geochemical, and remote-sensing expertise. The project was supported by the USGS Mineral Resources Program, and its products and acquired capabilities have broad applications to missions throughout the USGS and beyond. In addressing challenges associated with understanding the location, quantity, and quality of mineral resources, and in investigating the potential environmental consequences of resource development, a number of field and laboratory capabilities and interpretative methodologies evolved from the project that have applications to traditional resource studies as well as to studies related to ecosystem health, human health, disaster and hazard assessment, and planetary science. New or improved tools and research findings developed within the project have been applied to other projects and activities. Specifically, geophysical equipment and techniques have been applied to a variety of traditional and nontraditional mineral- and energy-resource studies, military applications, environmental investigations, and applied research activities that involve climate change, mapping techniques, and monitoring capabilities. Diverse applied geochemistry activities provide a process-level understanding of the mobility, chemical speciation, and bioavailability of elements, particularly metals and metalloids, in a variety of environmental settings. Imaging spectroscopy capabilities maintained and developed within the project have been applied to traditional resource studies as well as to studies related to ecosystem health, human health, disaster assessment, and planetary science. Brief descriptions of capabilities and laboratory facilities and summaries of some applications of project products and research findings are included in this circular. The work helped support the USGS mission to “provide reliable scientific information to describe and understand the Earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life.” Activities within the project include the following: Spanned scales from microscopic to planetary; Demonstrated broad applications across disciplines; Included life-cycle studies of mineral resources; Incorporated specialized areas of expertise in applied geochemistry including mineralogy, hydrogeology, analytical chemistry, aqueous geochemistry, biogeochemistry, microbiology, aquatic toxicology, and public health; and Incorporated specialized areas of expertise in geophysics including magnetics, gravity, radiometrics, electromagnetics, seismic, ground-penetrating radar, borehole radar, and imaging spectroscopy. This circular consists of eight sections that contain summaries of various activities under the project. The eight sections are listed below: Laboratory Facilities and Capabilities, which includes brief descriptions of the various types of laboratories and capabilities used for the project; Method and Software Development, which includes summaries of remote-sensing, geophysical, and mineralogical methods developed or enhanced by the project; Instrument Development, which includes descriptions of geophysical instruments developed under the project; Minerals, Energy, and Climate, which includes summaries of research that applies to mineral or energy resources, environmental processes and monitoring, and carbon sequestration by earth materials; Element Cycling, Toxicity, and Health, which includes summaries of several process-oriented geochemical and biogeochemical studies and health-related research activities; Hydrogeology and Water Quality, which includes descriptions of innovative geophysical, remote-sensing, and geochemical research pertaining to hydrogeology and water-quality applications; Hazards and Disaster Assessment, which includes summaries of research and method development that were applied to natural hazards, human-caused hazards, and disaster assessments; and Databases and Framework Studies, which includes descriptions of fundamental applications of geophysical studies and of the importance of archived data.

Circular↗
USGS2009

Maintaining the competitiveness of the American Fisheries Society journals: An assessment based on influence and cost-effectiveness

Recent changes in the landscape of scientific publishing prompted the Publications Overview Committee of the American Fisheries Society (AFS) to review the Society's portfolio of scientific journals. We evaluated journals based on metrics in two categories: (1) citation-based measures of the influence of a journal on the scientific literature, and (2) measures of the cost-effectiveness of a journal (citation rate adjusted for subscription cost). Over the long-term, we found that ecology journals had far stronger citation-based influence than fisheries and aquatic sciences journals, and that journals publishing primarily basic research had stronger influence than journals publishing applied research (including four AFS journals and Fisheries magazine). In evaluating the current status of fisheries and aquatic sciences journals, we found that metrics of influence and cost-effectiveness provided considerably different portrayals of journals relative to their peers. In terms of citation-based influence, we found that the AFS journal Transactions of the American Fisheries Society (TAFS) and Fisheries magazine were competitive with highly regarded peer fisheries journals, but that North American Journal of Aquaculture (NAJA) and Journal of Aquatic Animal Health (JAAH) were less influential than their peers. The citation-based influence of North American Journal of Fisheries Management (NAJFM) was intermediate between TAFS/Fisheries and NAJA/JAAH . For journals like NAJFM and NAJA , we expect that much of the scientific influence on policy and management is not captured by citations in the primary literature, and alternative methods of evaluation may be needed. All of the AFS journals ranked highly with regard to cost-effectiveness because their subscription costs are low, and these rankings are in accordance with membership needs and the strategic mission of AFS to provide broad and timely dissemination of scientific information. We conclude by suggesting ways to increase the influence of AFS journals without compromising their accessibility and affordability, and offer advice about methods and frequency for future journal evaluations.

Fisheries↗
USGS2017

Cooperative Fish and Wildlife Research Units Program—2016 year in review postcard

Cooperative Fish and Wildlife Research Units Program—2016 Year in Review postcard This postcard provides details about the Cooperative Fish and Wildlife Research Units (CRU) Program—2016 Year in Review, Circular 1424. This Circular provides information relating to fish and wildlife science, students, staffing, vacancies, research funding, outreach and training, science themes, background on the CRU program, accolades, and professional services. Snapshots of Unit projects with information on how results have been or are being applied by cooperators are included. This is the essence of what we do: science that matters. Throughout the year, keep up with our research projects at www.coopunits.org .

General Information Product↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2017

The HayWired Earthquake Scenario

Foreword The 1906 Great San Francisco earthquake (magnitude 7.8) and the 1989 Loma Prieta earthquake (magnitude 6.9) each motivated residents of the San Francisco Bay region to build countermeasures to earthquakes into the fabric of the region. Since Loma Prieta, bay-region communities, governments, and utilities have invested tens of billions of dollars in seismic upgrades and retrofits and replacements of older buildings and infrastructure. Innovation and state-of-the-art engineering, informed by science, including novel seismic-hazard assessments, have been applied to the challenge of increasing seismic resilience throughout the bay region. However, as long as people live and work in seismically vulnerable buildings or rely on seismically vulnerable transportation and utilities, more work remains to be done. With that in mind, the U.S. Geological Survey (USGS) and its partners developed the HayWired scenario as a tool to enable further actions that can change the outcome when the next major earthquake strikes. By illuminating the likely impacts to the present-day built environment, well-constructed scenarios can and have spurred officials and citizens to take steps that change the outcomes the scenario describes, whether used to guide more realistic response and recovery exercises or to launch mitigation measures that will reduce future risk. The HayWired scenario is the latest in a series of like-minded efforts to bring a special focus onto the impacts that could occur when the Hayward Fault again ruptures through the east side of the San Francisco Bay region as it last did in 1868. Cities in the east bay along the Richmond, Oakland, and Fremont corridor would be hit hardest by earthquake ground shaking, surface fault rupture, aftershocks, and fault afterslip, but the impacts would reach throughout the bay region and far beyond. The HayWired scenario name reflects our increased reliance on the Internet and telecommunications and also alludes to the interconnectedness of infrastructure, society, and our economy. How would this earthquake scenario, striking close to Silicon Valley, impact our interconnected world in ways and at a scale we have not experienced in any previous domestic earthquake? The area of present-day Contra Costa, Alameda, and Santa Clara Counties contended with a magnitude-6.8 earthquake in 1868 on the Hayward Fault. Although sparsely populated then, about 30 people were killed and extensive property damage resulted. The question of what an earthquake like that would do today has been examined before and is now revisited in the HayWired scenario. Scientists have documented a series of prehistoric earthquakes on the Hayward Fault and are confident that the threat of a future earthquake, like that modeled in the HayWired scenario, is real and could happen at any time. The team assembled to build this scenario has brought innovative new approaches to examining the natural hazards, impacts, and consequences of such an event. Such an earthquake would also be accompanied by widespread liquefaction and landslides, which are treated in greater detail than ever before. The team also considers how the now-prototype ShakeAlert earthquake early warning system could provide useful public alerts and automatic actions. Scientific Investigations Report 2017–5013 and accompanying data releases are the products of an effort led by the USGS, but this body of work was created through the combined efforts of a large team including partners who have come together to form the HayWired Coalition (see chapter A). Use of the HayWired scenario has already begun. More than a full year of intensive partner engagement, beginning in April 2017, is being directed toward producing the most in-depth look ever at the impacts and consequences of a large earthquake on the Hayward Fault. With the HayWired scenario, our hope is to encourage and support the active ongoing engagement of the entire community of the San Francisco Bay region by providing the scientific, engineering, and economic and social science inputs for use in exercises and planning well into the future. As HayWired volumes are published, they will be made available at https://doi.org/10.3133/sir20175013 .

California↗
USGS2015

Applied groundwater modeling, 2nd Edition

This second edition is extensively revised throughout with expanded discussion of modeling fundamentals and coverage of advances in model calibration and uncertainty analysis that are revolutionizing the science of groundwater modeling. The text is intended for undergraduate and graduate level courses in applied groundwater modeling and as a comprehensive reference for environmental consultants and scientists/engineers in industry and governmental agencies.

Book↗
USGS2000

Origin of the 17 July 1998 Papua New Guinea tsunami: Earthquake or landslide

The tsunami that struck Papua New Guinea on 17 July 1998 shortly after a M w 7.0 earthquake ( Figure 1 ) was one of the deadliest tsunamis in this century. At least 2,200 people died from this event, essentially destroying an entire generation in some communities. In the months following the tsunami, several international survey teams collected data in an attempt to better understand the cause of this event. Elevations of waterline marks and displaced debris measured by the first International Tsunami Survey Team (ITST; Kawata et al., 1999 ) indicated an average runup of 10 m occurring over a 25 km length of coastline in the vicinity of Sissano Lagoon ( Figure 2 ). The maximum runup from this event was approximately 15 m. Tsunami runup heights of this size are commonly associated either with earthquakes of much larger magnitude or with “tsunami earthquakes” as defined by Kanamori ( 1972 ) and later discussed by Kanamori and Kikuchi ( 1993 ). Even for tsunami earthquakes, however, runup heights of 10-15 m seem only to occur for earthquakes M w > 7.5. Because these runup heights appear anomalously high for a M 7 earthquake, other sources have been postulated for the tsunami, including a submarine landslide or mass flow. Earlier this year, the bathymetry north of Papua New Guinea was surveyed by the Japan Marine Science and Technology Center (JAMSTEC) and the South Pacific Applied Geoscience Commission (SOPAC). In a report describing the preliminary results from these cruises ( Tappin et al. , 1999 ), bathymetric images are presented that show evidence both of a 40-km-long fault scarp and of collapse features within an approximately 10-km-wide bathymetric amphitheater ( Figure 2 ). The report suggests that a landslide was the sole cause for the tsunami. In this paper, I revisit the common assumption that local tsunami runup scales directly with moment magnitude and demonstrate that the tsunami generated by the earthquake cannot be disregarded to explain the runup observations.

Seismological Research Letters↗
USGS2020

Landslide disparities, flume discoveries, and Oso despair

Landslide dynamics is the branch of science that seeks to understand the motion of landslides by applying Newton's laws. This memoir focusses on a 40‐year effort to understand motion of highly mobile—and highly lethal—landslides such as debris avalanches and debris flows. A major component of this work entailed development and operation of the U.S. Geological Survey debris flow flume, a unique, large‐scale experimental facility in Oregon. Experiments there yielded new insights that informed development of mathematical models that were aimed not only at explaining landslide dynamics but also at evaluating landslide and debris flow hazards. The most sophisticated of these models, called D‐Claw, found its first practical application during investigations of the 2014 Oso, Washington, landslide disaster. That event provided indelible lessons about the utility and sociology of science in the real world.

Washington↗
USGS2019

Occupancy models for citizen-science data

Large‐scale citizen‐science projects, such as atlases of species distribution, are an important source of data for macroecological research, for understanding the effects of climate change and other drivers on biodiversity, and for more applied conservation tasks, such as early‐warning systems for biodiversity loss. However, citizen‐science data are challenging to analyse because the observation process has to be taken into account. Typically, the observation process leads to heterogeneous and non‐random sampling, false absences, false detections, and spatial correlations in the data. Increasingly, occupancy models are being used to analyse atlas data. We advocate a dual approach to strengthen inference from citizen science data for the questions the programme is intended to address: (a) the survey design should be chosen with a particular set of questions and associated analysis strategy in mind and (b) the statistical methods should be tailored not only to those questions but also to the specific characteristics of the data. We review the consequences of particular survey design choices that typically need to be made in atlas‐style citizen‐science projects. These include spatial resolution of the sampling units, allocation of effort in space, and collection of information about the observation process. On the analysis side, we review extensions of the basic occupancy models that are frequently necessary with atlas data, including methods for dealing with heterogeneity, non‐independent detections, false detections, and violation of the closure assumption. New technologies, such as cell‐phone apps and fixed remote detection devices, are revolutionizing citizen‐science projects. There is an opportunity to maximize the usefulness of the resulting datasets if the protocols are rooted in robust statistical designs and data analysis issues are being considered. Our review provides guidelines for designing new projects and an overview of the current methods that can be used to analyse data from such projects.

Methods in Ecology and Evolution↗
USGS2021

Citizen science data collection for integrated wildlife population analyses

Citizen science, or community science, has emerged as a cost-efficient method to collect data for wildlife monitoring. To inform research and conservation, citizen science sampling designs should collect data that match the robust statistical analyses needed to quantify species and population patterns. Further increasing the contributions of citizen science, integrating citizen science data with other datasets and datatypes can improve population estimates and expand the spatiotemporal extent of inference. We demonstrate these points with a citizen science program called iSeeMammals developed in New York state in 2017 to supplement costly systematic spatial capture-recapture sampling by collecting opportunistic data from one-off observations, hikes, and camera traps. iSeeMammals has initially focused on the growing population of American black bear ( Ursus americanus ), with integrated analysis of iSeeMammals camera trap data with systematic data for a region with a growing bear population. The triumvirate of increased spatial and temporal coverage by at least twofold compared to systematic sampling, an 83% reduction in annual sampling costs, and improved density estimates when integrated with systematic data highlight the benefits of collecting presence-absence data in citizen science programs for estimating population patterns. Additional opportunities will come from applying presence-only data, which are oftentimes more prevalent than presence-absence data, to integrated models. Patterns in data submission and filtering also emphasize the importance of iteratively evaluating patterns in engagement, usability, and accessibility, especially focusing on younger adult and teenage demographics, to improve data quality and quantity. We explore how the development and use of integrated models may be paired with citizen science project design in order to facilitate repeated use of datasets in standalone and integrated analyses for supporting wildlife monitoring and informing conservation.

Frontiers in Ecology and Evolution↗
USGS2020

Statistical methods in water resources

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report. The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.

Techniques and Methods↗
USGS2008

Identifying habitat sinks: A case study of Cooper's hawks in an urban environment

We studied a population of Cooper's hawks (Accipiter cooperii) in Tucson, Arizona from 1994 to 2005. High rates of mortality of nestlings from an urban-related disease prompted speculation that the area represented an ecological trap and habitat sink for Cooper's hawks. In this paper, we used estimates of survival and productivity from 11years of monitoring to develop an estimate of the rate of population change, ??, for Cooper's hawks in the area. We used a Cormack-Jolly-Seber approach to estimate survival of breeding hawks, and a stochastic, stage-based matrix to estimate ??. Despite the urban-related disease, the estimate of ?? indicated that the area does not function as a habitat sink for Cooper's hawks (?? = 1.11 ?? 0.047; P = 0.0073 for the null of ?? 1). Because data required to reliably identify habitat sinks are extensive and difficult to acquire, we suggest that the concept of habitat sinks be applied cautiously until substantiated with reliable empirical evidence. ?? 2008 Springer Science+Business Media, LLC.

Urban Ecosystems↗