USGS Science⌕ Search

SEARCH · USGS Science

Results for “Statistical Methods & Applications”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21Linked to original sources
USGS2014

Assessment of tsunami hazard to the U.S. Atlantic margin

Tsunami hazard is a very low-probability, but potentially high-risk natural hazard, posing unique challenges to scientists and policy makers trying to mitigate its impacts. These challenges are illustrated in this assessment of tsunami hazard to the U.S. Atlantic margin. Seismic activity along the U.S. Atlantic margin in general is low, and confirmed paleo-tsunami deposits have not yet been found, suggesting a very low rate of hazard. However, the devastating 1929 Grand Banks tsunami along the Atlantic margin of Canada shows that these events continue to occur. Densely populated areas, extensive industrial and port facilities, and the presence of ten nuclear power plants along the coast, make this region highly vulnerable to flooding by tsunamis and therefore even low-probability events need to be evaluated. We can presently draw several tentative conclusions regarding tsunami hazard to the U.S. Atlantic coast. Landslide tsunamis likely constitute the biggest tsunami hazard to the coast. Only a small number of landslides have so far been dated and they are generally older than 10,000 years. The geographical distribution of landslides along the margin is expected to be uneven and to depend on the distribution of seismic activity along the margin and on the geographical distribution of Pleistocene sediment. We do not see evidence that gas hydrate dissociation contributes to the generation of landslides along the U.S. Atlantic margin. Analysis of landslide statistics along the fluvial and glacial portions of the margin indicate that most of the landslides are translational, were probably initiated by seismic acceleration, and failed as aggregate slope failures. How tsunamis are generated from aggregate landslides remains however, unclear. Estimates of the recurrence interval of earthquakes along the continental slope may provide maximum estimates for the recurrence interval of landslide along the margin. Tsunamis caused by atmospheric disturbances and by coastal earthquakes may be more frequent than those generated by landslides, but their amplitudes are probably smaller. Among the possible far-field earthquake sources, only earthquakes located within the Gulf of Cadiz or west of the Tore-Madeira Rise are likely to affect the U.S. coast. It is questionable whether earthquakes on the Puerto Rico Trench are capable of producing a large enough tsunami that will affect the U.S. Atlantic coast. More information is needed to evaluate the seismic potential of the northern Cuba fold-and-thrust belt. The hazard from a volcano flank collapse in the Canary Islands is likely smaller than originally stated, and there is not enough information to evaluate the magnitude and frequency of flank collapse from the Azores Islands. Both deterministic and probabilistic methods to evaluate the tsunami hazard from the margin are available for application to the Atlantic margin, but their implementation requires more information than is currently available.

Marine Geology↗
USGS1982

Guidelines for determining flood flow frequency: Bulletin #17B of the Hydrology Subcommittee

In December 1967, Bulletin No. 15, "A Uniform Technique for Determining Flood Flow Frequencies," was issued by the Hydrology Committee of the Water Resources Council. The report recommended use of the Pearson Type III distribution with log transformation of the data (log-Pearson Type III distribution) as a base method for flood flow frequency studies. As pointed out in that report, further studies were needed covering various aspects of flow frequency determinations. In March 1976, Bulletin 17, "Guidelines for Determining Flood Flow Frequency" was issued by the Water Resources Council. The guide was an extension and update of Bulletin No. 15. It provided a more complete guide for flood flow frequency analysis incorporating currently accepted technical methods with sufficient detail to promote uniform application. It was limited to defining flood potentials in terms of peak discharge and exceedance probability at locations where a systematic record of peak flood flows is available. The recommended set of procedures was selected from those used or described in the literature prior to 1976, based on studies conducted for this purpose at the Center for Research in Water Resources of the University of Texas at Austin (summarized in Appendix 14) and on studies by the Work Group on Flood Flow Frequency. The "Guidelines" were revised and reissued in June 1977 as Bulletin 17A. Bulletin 17B is the latest effort to improve and expand upon the earlier publications. Bulletin 17B provides revised procedures for weighting a station skew value with the results from a generalized skew study, detecting and treating outliers, making two station comparisons, and computing confidence limits about a frequency curve. The Work Group that prepared this revision did not address the suitability of the original distribution or the generalized skew map. Major problems are encountered when developing guides for flood flow frequency determinations. There is no procedure or set of procedures that can be adopted which, when rigidly applied to the available data, will accurately define the flood potential of any given watershed. Statistical analysis alone will not resolve all flood frequency problems. As discussed in subsequent sections of this guide, elements of risk and uncertainty are inherent in any flood frequency analysis. User decisions must be based on properly applied procedures and proper interpretation of results considering risk and uncertainty. Therefore, the judgment of a professional experienced in hydrologic analysis will enhance the usefulness of a flood frequency analysis and promote appropriate application. It is possible to standarize many elements of flood frequency analysis. This guide describes each major element of the process of defining the flood potential at a specific location in terms of peak discharge and exceedance probability. Use is confined to stations where available records are adequate to warrant statistical analysis of the data. Special situations may require other approaches. In those cases where the procedures of this guide are not followed, deviations must be supported by appropriate study and accompanied by a comparison of results using the recommended procedures. As a further means of achieving consistency and improving results, the Work Group recommends that studies be coordinated when more than one analyst is working currently on data for the same location. This recommendation holds particularly when defining exceedance probabilities for rare events, where this guide allows more latitude. Flood records are limited. As more years of record become available at each location, the determination of flood potential may change. Thus, an estimate may be outdated a few years after it is made. Additional flood data alone may be sufficient reason for a fresh assessment of the flood potential. When making a new assessment, the analyst should incorporate in his study a review of earlier estimates. Where differences appear, they should be acknowledged and explained.

Bulletin↗
USGS2006

Polychlorinated biphenyl congener patterns in tree swallows (Tachycineta bicolor) nesting in the Housatonic River watershed, western Massachusetts, USA, using a novel statistical approach

A novel application of a commonly used statistical approach was used to examine differences in polychlorinated biphenyl (PCB) congener Patterns among locations and sample matrices in tree swallows (Tachycineta bicolor) nesting in the Housatonic River watershed in western Massachusetts. USA. The most prevalent PCB congeners in tree swallow tissue samples from the Housatonic River watershed were Ballsmitter Zell numbers 153. 138 180, 187 149, 101, and 170. These congeners were seven of the eight most prevalent congeners in Aroclor (R) 1260, the PCB mixture that was the primary source of contamination in the Housatonic River system. Using paired-Euclidean distances and tolerance limits, it was demonstrated that conuener patterns in swallow tissues from sites on the main stem of the Housatonic River were more similar to one another than to two sites upstream of the contamination or from a nearby reference area. The congener patterns also differed between the reference area and the two upstream tributaries and between the two tributaries. These pattern differences were the same in both pipper (eggs or just hatched nestlings) and 12-day-old nestling samples. Lower-chlorinated congeners appeared to be metabolized in nestlings and pippers compared to diet. and metabolized more in pippers compared to nestlings. Euclidean distances and tolerance limits provide a simple and statistically valid method to compare PCB congener patterns among groups. Published by Elsevier Ltd.

Environmental Pollution↗
USGS2008

Importance of sampling design and analysis in animal population studies: a comment on Sergio et al

1. The use of predators as indicators and umbrellas in conservation has been criticized. In the Trentino region, Sergio et al. (2006; hereafter SEA) counted almost twice as many bird species in quadrats located in raptor territories than in controls. However, SEA detected astonishingly few species. We used contemporary Swiss Breeding Bird Survey data from an adjacent region and a novel statistical model that corrects for overlooked species to estimate the expected number of bird species per quadrat in that region. 2. There are two anomalies in SEA which render their results ambiguous. First, SEA detected on average only 6.8 species, whereas a value of 32 might be expected. Hence, they probably overlooked almost 80% of all species. Secondly, the precision of their mean species counts was greater in two-thirds of cases than in the unlikely case that all quadrats harboured exactly the same number of equally detectable species. This suggests that they detected consistently only a biased, unrepresentative subset of species. 3. Conceptually, expected species counts are the product of true species number and species detectability p. Plenty of factors may affect p, including date, hour, observer, previous knowledge of a site and mobbing behaviour of passerines in the presence of predators. Such differences in p between raptor and control quadrats could have easily created the observed effects. Without a method that corrects for such biases, or without quantitative evidence that species detectability was indeed similar between raptor and control quadrats, the meaning of SEA's counts is hard to evaluate. Therefore, the evidence presented by SEA in favour of raptors as indicator species for enhanced levels of biodiversity remains inconclusive. 4. Synthesis and application. Ecologists should pay greater attention to sampling design and analysis in animal population estimation. Species richness estimation means sampling a community. Samples should be representative for the community studied and the sampling fraction among communities compared should be the same on average, otherwise formal estimation approaches must be applied to avoid misleading inference.

Journal of Applied Ecology↗
USGS2016

Adjusted peak-flow frequency estimates for selected streamflow-gaging stations in or near Montana based on data through water year 2011: Chapter D in Montana StreamStats

The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011. The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. The at-site frequency estimates were adjusted by weighting with frequency estimates from RREs using the WIE program for 438 selected gaging stations in Montana. These 438 selected gaging stations (1) had periods of record less than or equal to 40 years, (2) represented unregulated or minor regulation conditions, and (3) had drainage areas less than about 2,750 square miles. The weighted-average frequency estimates obtained by weighting with RREs generally are considered to provide improved frequency estimates. In some cases, there are substantial differences among the at-site frequency estimates, the regression-equation frequency estimates, and the weighted-average frequency estimates. In these cases, thoughtful consideration should be applied when selecting the appropriate frequency estimate. Some factors that might be considered when selecting the appropriate frequency estimate include (1) whether the specific gaging station has peak-flow characteristics that distinguish it from most other gaging stations used in developing the RREs for the hydrologic region; and (2) the length of the peak-flow record and the general climatic characteristics during the period when the peak-flow data were collected. For critical structure-design applications, a conservative approach would be to select the higher of the at-site frequency estimate and the weighted-average frequency estimate. The mixed-station MOVE.1 procedure generally was applied in cases where three or more gaging stations were located on the same large river and some of the gaging stations could not be adjusted using the weighted-average method because of regulation or drainage areas too large for application of RREs. The mixed-station MOVE.1 procedure was applied to 66 selected gaging stations on 19 large rivers. The general approach for using mixed-station record extension procedures to adjust at-site frequencies involved (1) determining appropriate base periods for the gaging stations on the large rivers, (2) synthesizing peak-flow data for the gaging stations with incomplete peak-flow records during the base periods by using the mixed-station MOVE.1 procedure, and (3) conducting frequency analysis on the combined recorded and synthesized peak-flow data for each gaging station. Frequency estimates for the combined recorded and synthesized datasets for 66 gaging stations with incomplete peak-flow records during the base periods are presented. The uncertainties in the mixed-station record extension results are difficult to directly quantify; thus, it is important to understand the intended use of the estimated frequencies based on analysis of the combined recorded and synthesized datasets. The estimated frequencies are considered general estimates of frequency relations among gaging stations on the same stream channel that might be expected if the gaging stations had been gaged during the same long-term base period. However, because the mixed-station record extension procedures involve secondary statistical analysis with accompanying errors, the uncertainty of the frequency estimates is larger than would be obtained by collecting systematic records for the same number of years in the base period.

Montana↗
USGS2003

A stream-gaging network analysis for the 7-day, 10-year annual low flow in New Hampshire streams

The 7-day, 10-year (7Q10) low-flow-frequency statistic is a widely used measure of surface-water availability in New Hampshire. Regression equations and basin-characteristic digital data sets were developed to help water-resource managers determine surface-water resources during periods of low flow in New Hampshire streams. These regression equations and data sets were developed to estimate streamflow statistics for the annual and seasonal low-flow-frequency, and period-of-record and seasonal period-of-record flow durations. generalized-least-squares (GLS) regression methods were used to develop the annual 7Q10 low-flow-frequency regression equation from 60 continuous-record stream-gaging stations in New Hampshire and in neighboring States. In the regression equation, the dependent variables were the annual 7Q10 flows at the 60 stream-gaging stations. The independent (or predictor) variables were objectively selected characteristics of the drainage basins that contribute flow to those stations. In contrast to ordinary-least-squares (OLS) regression analysis, GLS-developed estimating equations account for differences in length of record and spatial correlations among the flow-frequency statistics at the various stations. A total of 93 measurable drainage-basin characteristics were candidate independent variables. On the basis of several statistical parameters that were used to evaluate which combination of basin characteristics contribute the most to the predictive power of the equations, three drainage-basin characteristics were determined to be statistically significant predictors of the annual 7Q10: (1) total drainage area, (2) mean summer stream-gaging station precipitation from 1961 to 90, and (3) average mean annual basinwide temperature from 1961 to 1990. To evaluate the effectiveness of the stream-gaging network in providing regional streamflow data for the annual 7Q10, the computer program GLSNET (generalized-least-squares NETwork) was used to analyze the network by application of GLS regression between streamflow and the climatic and basin characteristics of the drainage basin upstream from each stream-gaging station. Improvement to the predictive ability of the regression equations developed for the network analyses is measured by the reduction in the average sampling-error variance, and can be achieved by collecting additional streamflow data at existing stations. The predictive ability of the regression equations is enhanced even further with the addition of new stations to the network. Continued data collection at unregulated stream-gaging stations with less than 14 years of record resulted in the greatest cost-weighted reduction to the average sampling-error variance of the annual 7Q10 regional regression equation. The addition of new stations in basins with underrepresented values for the independent variables of the total drainage area, average mean annual basinwide temperature, or mean summer stream-gaging station precipitation in the annual 7Q10 regression equation yielded a much greater cost-weighted reduction to the average sampling-error variance than when more data were collected at existing unregulated stations. To maximize the regional information obtained from the stream-gaging network for the annual 7Q10, ranking of the streamflow data can be used to determine whether an active station should be continued or if a new or discontinued station should be activated for streamflow data collection. Thus, this network analysis can help determine the costs and benefits of continuing the operation of a particular station or activating a new station at another location to predict the 7Q10 at ungaged stream reaches. The decision to discontinue an existing station or activate a new station, however, must also consider its contribution to other water-resource analyses such as flood management, water quality, or trends in land use or climatic change.

Water-Resources Investigations Report↗
USGS2017

Statistical design and analysis for plant cover studies with multiple sources of observation errors

Effective wildlife habitat management and conservation requires understanding the factors influencing distribution and abundance of plant species. Field studies, however, have documented observation errors in visually estimated plant cover including measurements which differ from the true value (measurement error) and not observing a species that is present within a plot (detection error). Unlike the rapid expansion of occupancy and N-mixture models for analysing wildlife surveys, development of statistical models accounting for observation error in plants has not progressed quickly. Our work informs development of a monitoring protocol for managed wetlands within the National Wildlife Refuge System. Zero-augmented beta (ZAB) regression is the most suitable method for analysing areal plant cover recorded as a continuous proportion but assumes no observation errors. We present a model extension that explicitly includes the observation process thereby accounting for both measurement and detection errors. Using simulations, we compare our approach to a ZAB regression that ignores observation errors (naïve model) and an “ad hoc” approach using a composite of multiple observations per plot within the naïve model. We explore how sample size and within-season revisit design affect the ability to detect a change in mean plant cover between 2 years using our model. Explicitly modelling the observation process within our framework produced unbiased estimates and nominal coverage of model parameters. The naïve and “ad hoc” approaches resulted in underestimation of occurrence and overestimation of mean cover. The degree of bias was primarily driven by imperfect detection and its relationship with cover within a plot. Conversely, measurement error had minimal impacts on inferences. We found >30 plots with at least three within-season revisits achieved reasonable posterior probabilities for assessing change in mean plant cover. For rapid adoption and application, code for Bayesian estimation of our single-species ZAB with errors model is included. Practitioners utilizing our R-based simulation code can explore trade-offs among different survey efforts and parameter values, as we did, but tuned to their own investigation. Less abundant plant species of high ecological interest may warrant the additional cost of gathering multiple independent observations in order to guard against erroneous conclusions.

Methods in Ecology and Evolution↗
USGS2019

River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model

Accurate quantification of riverine water‐quality concentration and flux is challenging because monitoring programs typically collect concentration data at lower frequencies than discharge data. Statistical methods are often used to estimate concentration and flux on days without observations. One recently developed approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS), which has been shown to provide among the most accurate estimates compared to other common methods. The main objective of this work was to improve WRTDS estimation by accounting for the autocorrelation structure of model residuals using the first‐order autoregressive model (AR1). This modified approach, called WRTDS‐Kalman Filter (WRTDS‐K), was compared with WRTDS for six constituents including nitrate‐plus‐nitrite (NO x ), total phosphorus, total Kjeldahl nitrogen, soluble reactive phosphorus, suspended sediment, and chloride. Near‐daily concentration records at nine sites were used to generate subsets through Monte Carlo sampling for five different sampling scenarios. Results show that WRTDS‐K provided generally better daily estimates of concentration and flux than WRTDS under these sampling scenarios for all constituents, especially NO x . The degree of improvement is strongly affected by the underlying sampling scenario, with WRTDS‐K gaining more advantage when more samples are available, and hence more residuals can be exploited. The performance of WRTDS‐K depends on the AR1 coefficient (ρ) and that relationship varies with constituents and sampling scenarios. These results provided recommendations on the optimal ρ for each constituent and sampling scenario. Overall, WRTDS‐K has the potential for broad applications to monitoring records elsewhere, as demonstrated by a pilot application to Chesapeake Bay tributaries.

Ohio↗
USGS2012

Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana

Potential wetland extents were estimated for a 14-mile reach of the Wabash River near Terre Haute, Indiana. This pilot study was completed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS). The study showed that potential wetland extents can be estimated by analyzing streamflow statistics with the available streamgage data, calculating the approximate water-surface elevation along the river, and generating maps by use of flood-inundation mapping techniques. Planning successful restorations for Wetland Reserve Program (WRP) easements requires a determination of areas that show evidence of being in a zone prone to sustained or frequent flooding. Zone determinations of this type are used by WRP planners to define the actively inundated area and make decisions on restoration-practice installation. According to WRP planning guidelines, a site needs to show evidence of being in an "inundation zone" that is prone to sustained or frequent flooding for a period of 7 consecutive days at least once every 2 years on average in order to meet the planning criteria for determining a wetland for a restoration in agricultural land. By calculating the annual highest 7-consecutive-day mean discharge with a 2-year recurrence interval (7MQ2) at a streamgage on the basis of available streamflow data, one can determine the water-surface elevation corresponding to the calculated flow that defines the estimated inundation zone along the river. By using the estimated water-surface elevation ("inundation elevation") along the river, an approximate extent of potential wetland for a restoration in agricultural land can be mapped. As part of the pilot study, a set of maps representing the estimated potential wetland extents was generated in a geographic information system (GIS) application by combining (1) a digital water-surface plane representing the surface of inundation elevation that sloped in the downstream direction of flow and (2) land-surface elevation data. These map products from the pilot study will aid the NRCS and its partners with the onsite inundation-zone verification in agricultural land for a potential restoration and will assist in determining at what elevation to plant hardwood trees for increased survivability on ground above frequently flooded terraces.

Indiana↗
USGS2017

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis , and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua . Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive divergence in Sphaeralcea . We describe multivariate statistical approaches for interpolating spatial patterns of adaptive divergence while accounting for potential bias due to neutral genetic structure. Through a spatial bootstrapping procedure, we also visualize patterns in the magnitude of model uncertainty. Finally, we introduce an interactive, distance-based mapping approach that explicitly links marker-based models of adaptive divergence with local or admixture seed sourcing strategies, promoting effective native plant restoration.

Mojave Desert↗
USGS2013

Comparing effects of transmitters within and among populations: application to swimming performance of juvenile Chinook salmon

The sensitivity of fish to a transmitter depends on factors such as environmental conditions, fish morphology, life stage, rearing history, and tag design. However, synthesizing general trends across studies is difficult because each study focuses on a particular performance measure, species, life stage, and transmitter model. These differences motivated us to develop simple metrics that allow effects of transmitters to be compared among different species, populations, or studies. First, we describe how multiple regression analysis can be used to quantify the effect of tag burden (transmitter mass relative to fish mass) on measures of physiological performance. Next, we illustrate how the slope and intercept parameters can be used to calculate two summary statistics: θ, which estimates the tag burden threshold above which the performance of tagged fish begins to decline relative to untagged fish; and k, which measures the percentage change in performance per percentage point increase in tag burden. When θ = 0, k provides a single measure of the tag's effect that can be compared among species, populations, or studies. We apply this analysis to two different experiments that measure the critical swimming speed (U crit) of tagged juvenile Chinook Salmon Oncorhynchus tshawytscha. In both experiments, U crit declined as tag burden increased, but we found no significant threshold in swimming performance. Estimates of θ ranged from −0.6% to 2.1% among six unique treatment groups, indicating that swimming performance began to decline at a relatively low tag burden. Estimates of k revealed that U crit of tagged fish declined by −2.68% to −4.86% for each 1% increase in tag burden. Both θ and k varied with the tag's antenna configuration, tag implantation method, and posttagging recovery time. Our analytical approach can be used to gain insights across populations to better understand factors affecting the ability of fish to carry a transmitter.

Transactions of the American Fisheries Society↗
USGS2023

A genetic warning system for a hierarchically structured wildlife monitoring framework

Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse ( Centrocercus urophasianus ) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhood-scale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations. We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern. Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.

Ecological Applications↗
USGS2021

Water-quality trends of urban streams in Independence, Missouri, 2005–18

The U.S. Geological Survey and the city of Independence, Missouri, Water Pollution Control Department has studied the water quality and ecological condition of urban streams within Independence since 2005. Selected physical properties, nutrients, chloride, fecal indicator bacteria (Escherichia coli and total coliform), total dissolved solids, and suspended-sediment concentration data for base-flow and stormflow samples were used to document temporal trends in concentrations and flow-weighted concentrations; and annual loads were computed and investigated for selected nutrients, chloride, and suspended sediment. The six study sites included in this report are located on five urban streams: Rock Creek, a tributary in the city that drains to the Missouri River; three tributaries of the Little Blue River within the city (East Fork Little Blue River, Adair Creek, and Spring Branch Creek); and two sites on the main stem of the Little Blue River (one upstream from the city and one downstream from the three tributaries). Many factors such as population, land use, and climate, and combinations of these factors contributed to the significant changes in the concentrations and transport of nutrients, chloride, fecal indicator bacteria, and suspended sediment in the urban streams within Independence. The population of Independence and the amount of developed land in the urban watersheds remained unchanged during the 2005–18 study. Differences were noted in precipitation and in streamflow during the study. Annual precipitation and streamflow were separated into two time periods within the study—period 1 (2006–10), having greater annual streamflow and precipitation, and period 2 (2011–18), having about 30 percent lower annual streamflow and less precipitation. Streamflow was an important factor in the transport of nitrogen, phosphorus, chloride, and suspended sediment from the urban watersheds. Changes in data collection methodology during the study period and improvements to the city stormwater and wastewater infrastructure also could have contributed to some of the trends. Between 2009 and 2015, more than 35 million dollars of improvements were made to stormwater and wastewater infrastructure within the city. These improvements, such as additional sewage overflow holding tanks, removal of septic tanks, and improved and expanded sanitary sewer lines and storm overflows, also could have affected the decreased nutrients and fecal indicator bacteria trends among the urban streams in the study area. Models were used for analyzing streamflow-related variability in constituent concentrations and loads to determine if the water quality changed significantly during the study period. Trends in concentration data at four sites were analyzed using a statistical package called R–QWTREND and trends in load data were analyzed at six sites using a statistical package called Weighted Regressions on Time, Discharge, and Season-Kalman filter (WRTDS–K); both developed by the U.S. Geological Survey and publicly available for use. Statistically significant trends in flow-weighted nutrient concentrations and loads generally were downward during the study period. The only nutrient compound with a statistically significant upward trend in flow-weighted concentration was dissolved orthophosphate as phosphorus at the Rock Creek site and the upstream site on the Little Blue River. A statistically significant downward trend in annual dissolved ammonia load was identified at the downstream Little Blue River site. A significant upward linear trend in annual orthophosphate as phosphorus load was identified on Adair Creek. A statistically significant upward trend in dissolved chloride concentrations was identified at the downstream Little Blue River site. Road salt application near the site during the winter could have resulted in higher concentrated runoff during wet weather conditions. Annual chloride loads significantly decreased in Adair Creek and Spring Branch Creek. The mean annual chloride load transported in the drier (2011–18) period 2 was significantly less than during the wetter (2006–10) period 1, indicating that trends in precipitation runoff are an important factor in trends in annual transport of chloride. Statistically significant downward trends in flow-weighted fecal indicator bacteria Escherichia coli (E. coli) population densities were noted for Rock Creek and the down-stream site on the Little Blue River. However, no trend was identified in E. coli population density at the upstream Little Blue River site. The downward trend in E. coli population density at the downstream site could be a result of decreased streamflow and precipitation over the study period, storage of fecal indicator bacteria in the Little Blue River streambed within the study area, die-off of fecal indicator bacteria during travel from upstream to downstream, changes in the sample collection methodology, improvements to the city’s storm-water and wastewater infrastructures, or a combination of these factors. The statistically significant downward trend in suspended-sediment concentration identified at the upstream Little Blue River site could be affected by the decreased streamflow and precipitation during the study period, by changes in sampling methods within the study period, and by the decrease in construction and urban land development upstream from the city. No statistically significant change was indicated in the annual suspended-sediment load transported from Independence to the Little Blue River during the study period. More than one-half the suspended sediment transported in the Little Blue River originated in the watershed upstream from Independence. The Little Blue River and many of its tributaries that drain Independence have been designated as recreational waters classified for whole-body contact class B and secondary contact recreation, and some have been listed as impaired for E. coli by the Missouri Department of Natural Resources from urban runoff and storm sewers. Observations were made among the available E. coli population density data for both Little Blue River sites to further understand water-quality conditions over the study period. Both Little Blue River sites had similar medians and geometric means for the recreational season (April through October) and during the full study period, both of which are greater than the regulatory population density for both recreational classes. The Little Blue River drainage area nearly doubles in size from the upstream to downstream site; therefore, the consistent geometric mean and median of E. coli population densities at the upstream and downstream Little Blue River sites could be primarily due to the larger volume of streamflow creating a dilution effect. Other possible factors could be storage of fecal indicator bacteria in stream bed sediments, die-off of fecal indicator bacteria during transport, improvements to the city’s wastewater and stormwater infrastructure, changes to sampling methodology, or a combination of these factors. Specific sources of the E. coli are currently (2019) unknown.

Missouri↗
USGS2020

A multi-state occupancy modelling framework for robust estimation of disease prevalence in multi-tissue disease systems

Given the public health, economic and conservation implications of zoonotic diseases, their effective surveillance is of paramount importance. The traditional approach to estimating pathogen prevalence as the proportion of infected individuals in the population is biased because it fails to account for imperfect detection. A statistically robust way to reduce bias in prevalence estimates is to obtain repeated samples (or sample many tissues in multi‐tissue disease systems) and to apply statistical methods that account for imperfect detection and permit the interdependence of the infection process across multiple tissues. We developed a multi‐state occupancy modelling framework which considers two scenarios about the infection process, one where no assumptions about the dependencies among the tissues are made (general), and another where dependence among tissues is not permitted (constrained). We applied this framework to pseudorabies virus (PrV) DNA detection data obtained from whole blood; and oral, nasal and genital mucosa of 510 feral swine Sus scrofa during the years 2014–2016 in Florida, USA. The constrained model was better supported by data. PrV prevalence estimates varied among tissues and were higher than the naïve estimates, ranging from to 0.06 (CI: 0.02–0.14) in genital to 0.54 (CI: 0.14 ‐ 0.82) in nasal tissue. Probability of PrV detection ranged from 0.11 (CI: 0.06–0.18) in nasal to 0.51 (CI: 0.21–0.81) in genital tissue. PrV prevalence was not affected by the age or sex of the animal or the year of sampling, but prevalence increased as drought severity increased. The conditional probability of detecting PrV given infection in at least one tissue type within an individual was highest for nasal tissue, suggesting that nasal is the best tissue to sample for PrV surveillance if only one tissue can be sampled, at least for systems with tissue‐specific prevalence and detection probabilities similar to ours. Synthesis and applications . We focused on inferences about pathogen prevalence in multi‐tissue disease systems, dealing with both nondetection and potential dependencies among tissues in infection status. We found strong evidence of variation in both prevalence and detection probabilities among tissues. Our results emphasize the importance of sampling multiple tissues and of applying inference methods that account for imperfect detection in the surveillance of systemic diseases. The multi‐state modelling framework is broadly applicable to the surveillance of pathogens that infect multiple tissues and can be used even when the infection status of the pathogen in one tissue may depend on the infection status of the pathogen in other tissue(s).

Journal of Applied Ecology↗
USGS2016

Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada

Zircon geochronology is a critical tool for establishing geologic ages and time scales of processes in the Earth's crust. However, for zircons compromised by open system behavior, achieving robust dates can be difficult. Chemical abrasion (CA) is a routine step prior to thermal ionization mass spectrometry (TIMS) dating of zircon to remove radiation-damaged parts of grains that may have experienced open system behavior and loss of radiogenic Pb. While this technique has been shown to improve the accuracy and precision of TIMS dating, its application to high-spatial resolution dating methods, such as secondary ion mass spectrometry (SIMS), is relatively uncommon. In our efforts to U-Pb date zircons from the late Eocene Caetano caldera by SIMS (SHRIMP-RG: sensitive high resolution ion microprobe, reverse geometry), some grains yielded anomalously young U-Pb ages that implicated Pb-loss and motivated us to investigate with a comparative CA and non-CA dating study. We present CA and non-CA 206 Pb/ 238 U ages and trace elements determined by SHRIMP-RG for zircons from three Caetano samples (Caetano Tuff, Redrock Canyon porphyry, and a silicic ring-fracture intrusion) and for R33 and TEMORA-2 reference zircons. We find that non-CA Caetano zircons have weighted mean or bimodal U-Pb ages that are 2–4% younger than CA zircons for the same samples. CA Caetano zircons have mean U-Pb ages that are 0.4–0.6 Myr older than the 40 Ar/ 39 Ar sanidine eruption age (34.00 ± 0.03 Ma; error-weighted mean, 2σ), whereas non-CA zircons have ages that are 0.7–1.3 Myr younger. U-Pb ages do not correlate with U (~ 100–800 ppm), Th (~ 50–300 ppm) or any other measured zircon trace elements (Y, Hf, REE), and CA and non-CA Caetano zircons define identical trace element ranges. No statistically significant difference in U-Pb age is observed for CA versus non-CA R33 or TEMORA-2 zircons. Optical profiler measurements of ion microprobe pits demonstrate consistent depths of ~ 1.6 μm for CA and non-CA Caetano, R33 and TEMORA-2 zircons, and do not indicate variations in secondary ion sputtering rates due to chemical or structural changes from the CA treatment. Our new data underscore the potential for cryptic Pb-loss to go unrecognized in other geologically young magmatic centers that do not have zircons with high U, statistically discordant isotope ratios, high common Pb, or metamict textures.

Nevada↗
USGS2018

A geostatistical state‐space model of animal densities for stream networks

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty underestimated. We developed a novel statistical method to account for spatiotemporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 yr. Increasing the number of survey sites within the network improved the performance of the nonspatial model but only marginally improved the density estimates in the spatiotemporal model. We applied this model to brook trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 yr from 1981 to 2014. We found the model including temporal and spatiotemporal autocorrelation best described young of the year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately high spatiotemporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatiotemporal correlation and higher temporal autocorrelation.

Ecological Applications↗
USGS2026

Breeding shorebird surveys in the Arctic National Wildlife Refuge, Alaska, suggest population declines over two decades for most species

Shorebird populations are declining globally but it generally remains unclear how those declines translate to changes at the regional scale. We conducted the first longitudinal surveys of breeding shorebirds in Alaska under the Program for Regional and International Shorebird Monitoring (PRISM), resurveying the Coastal Plain (1002 Area) of the Arctic National Wildlife Refuge (NWR) in 2019 and 2022 to compare with initial surveys conducted in 2002 and 2004. Our goals were to (1) estimate contemporary population sizes of breeding shorebirds across this 6,249 km 2 area, and (2) assess population trends for the species detected in both survey periods. We estimated population sizes for 16 species, with a combined total of 135,178 (95% CI: 113,532–156,824) in 2019 and 2022—a decline of approximately 17% (90% CI: –34% to + 3%) from 2002 and 2004 when the same survey methods were used. Four species showed a statistically significant decrease (α = 0.10): Calidris alpina arcticola (Dunlin), Limnodromus scolopaceus (Long-billed Dowitcher), Phalaropus lobatus (Red-necked Phalarope), and P. fulicarius (Red Phalarope). Only C. melanotos (Pectoral Sandpiper) showed a significant increase. Overall, 5 of 10 species—and all species combined—had a > 90% probability of decline. Population changes for the polygamous species (i.e., Phalaropus sp. and C. melanotos ), which show irruptive breeding and low breeding site fidelity, may reflect temporary immigration or emigration driven by annual environmental variation, rather than true population change. Nevertheless, the overall pattern of declines aligns with migration surveys outside the Arctic. These findings highlight the vulnerability of Arctic-breeding shorebirds to threats throughout their annual cycles and underscore the potential for sustained long-term monitoring in this rapidly changing region to inform effective, flyway-scale conservation strategies across the Western Hemisphere.

Alaska↗
USGS2026

Methods for estimating selected low-flow frequency and mean annual flow statistics at gaged and ungaged locations on streams in Georgia, North Carolina, and South Carolina

The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources (Environmental Protection Division), North Carolina Department of Environmental Quality (Division of Water Resources), North Carolina Department of Public Safety (Office of Recovery and Resiliency), and South Carolina Department of Environmental Services, updated low-flow frequency, mean annual flow, and flow-duration statistics at 843 streamgages in and near Georgia, North Carolina, and South Carolina. The low-flow frequency statistics are annual minimum 1-day average flow with a 10-year recurrence interval (1Q10), annual minimum 7-day average flow for 2- and 10-year recurrence intervals (7Q2 and 7Q10, respectively), and annual minimum 30-day average flow with 2- and 3-year recurrence intervals (30Q2 and 30Q3, respectively). Monthly 1Q10 and 7Q10, and W7Q10 flow statistics for the winter period (November–March) also are presented. By using data from 604 of the streamgages on streams with streamflows that are not substantially affected by regulation or diversion and are not tidally influenced, regional regression equations were developed to predict flow statistics with prediction intervals at ungaged locations on streams with those same criteria. The regional regression analysis included data from 132 streamgages from adjacent States Alabama, Florida, Tennessee, and Virginia. The final regional regression equations include variables such as drainage area, streamflow variability, precipitation, percentage of impervious area, and percentage of the basin in various ecoregions. The low-flow statistics for the streamgages analyzed and the regional regression equations will be integrated into the U.S. Geological Survey StreamStats application ( https://www.usgs.gov/streamstats ) for Georgia, North Carolina, and South Carolina. StreamStats generates basin characteristics needed to compute low-flow frequency statistics for ungaged locations. A trend analysis of annual minimum 7-day average flows was done for 78 streamgages with at least 30 years of continuous record. Trends were evaluated for 30-, 50‑, 70-, and 90-year periods, ending in climate year 2021, and independence and short- and long-term persistence assumptions were considered. For all trend analysis assumptions, most streamgages did not exhibit significant trends in annual minimum 7-day average flows. Trends in annual precipitation and air temperature were similarly evaluated for the period 1895–2021 to assess the variability of climate for Georgia, North Carolina, and South Carolina.

Georgia, North Carolina, South Carolina↗