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Groundwater-quality data in the Santa Barbara study unit, 2011: Results from the California GAMA Program

Groundwater quality in the 48-square-mile Santa Barbara study unit was investigated by the U.S. Geological Survey (USGS) from January to February 2011, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The Santa Barbara study unit was the thirty-fourth study unit to be sampled as part of the GAMA-PBP. The GAMA Santa Barbara study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system, and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The primary aquifer system is defined as those parts of the aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the Santa Barbara study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination. In the Santa Barbara study unit located in Santa Barbara and Ventura Counties, groundwater samples were collected from 24 wells. Eighteen of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and six wells were selected to aid in evaluation of water-quality issues (understanding wells). The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], pesticides and pesticide degradates, and pharmaceutical compounds); constituents of special interest (perchlorate and N-nitrosodimethylamine [NDMA]); naturally occurring inorganic constituents (trace elements, nutrients, major and minor ions, silica, total dissolved solids [TDS], alkalinity, and arsenic, chromium, and iron species); and radioactive constituents (radon-222 and gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stables isotopes of inorganic carbon and boron dissolved in water, isotope ratios of dissolved strontium, tritium activities, and carbon-14 abundances) and dissolved noble gases also were measured to help identify the sources and ages of the sampled groundwater. In total, 281 constituents and water-quality indicators were measured. Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 12 percent of the wells in the Santa Barbara study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 82 percent of the compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. All organic constituents and most inorganic constituents that were detected in groundwater samples from the 18 grid wells in the Santa Barbara study unit were detected at concentrations less than drinking-water benchmarks. Of the 220 organic and special-interest constituents sampled for at the 18 grid wells, 13 were detected in groundwater samples; concentrations of all detected constituents were less than regulatory and non-regulatory health-based benchmarks. In total, VOCs were detected in 61 percent of the 18 grid wells sampled, pesticides and pesticide degradates were detected in 11 percent, and perchlorate was detected in 67 percent. Polar pesticides and their degradates, pharmaceutical compounds, and NDMA were not detected in any of the grid wells sampled in the Santa Barbara study unit. Eighteen grid wells were sampled for trace elements, major and minor ions, nutrients, and radioactive constituents; most detected concentrations were less than health-based benchmarks. Exceptions are one detection of boron greater than the CDPH notification level (NL-CA) of 1,000 micrograms per liter (μg/L) and one detection of fluoride greater than the CDPH maximum contaminant level (MCL-CA) of 2 milligrams per liter (mg/L). Results for constituents with non-regulatory benchmarks set for aesthetic concerns from the grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in three grid wells. Manganese concentrations greater than the SMCL-CA of 50 μg/L were detected in seven grid wells. Chloride was detected at a concentration greater than the SMCL-CA recommended benchmark of 250 mg/L in four grid wells. Sulfate concentrations greater than the SMCL-CA recommended benchmark of 250 mg/L were measured in eight grid wells, and the concentration in one of these wells was also greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 17 grid wells, and concentrations in six of these wells were also greater than the SMCL-CA upper benchmark of 1,000 mg/L.

California↗

Methylmercury exposure in wildlife: A review of the ecological and physiological processes affecting contaminant concentrations and their interpretation

Exposure to methylmercury (MeHg) can result in detrimental health effects in wildlife. With advances in ecological indicators and analytical techniques for measurement of MeHg in a variety of tissues, numerous processes have been identified that can influence MeHg concentrations in wildlife. This review presents a synthesis of theoretical principals and applied information for measuring MeHg exposure and interpreting MeHg concentrations in wildlife. Mercury concentrations in wildlife are the net result of ecological processes influencing dietary exposure combined with physiological processes that regulate assimilation, transformation, and elimination. Therefore, consideration of both physiological and ecological processes should be integrated when formulating biomonitoring strategies. Ecological indicators, particularly stable isotopes of carbon, nitrogen, and sulfur, compound-specific stable isotopes, and fatty acids, can be effective tools to evaluate dietary MeHg exposure. Animal species differ in their physiological capacity for MeHg elimination, and animal tissues can be inert or physiologically active, act as sites of storage, transformation, or excretion of MeHg, and vary in the timing of MeHg exposure they represent. Biological influences such as age, sex, maternal transfer, and growth or fasting are also relevant for interpretation of tissue MeHg concentrations. Wildlife tissues that represent current or near-term bioaccumulation and in which MeHg is the predominant mercury species (such as blood and eggs) are most effective for biomonitoring ecosystems and understanding landscape drivers of MeHg exposure. Further research is suggested to critically evaluate the use of keratinized external tissues to measure MeHg bioaccumulation, particularly for less-well studied wildlife such as reptiles and terrestrial mammals. Suggested methods are provided to effectively use wildlife for quantifying patterns and drivers of MeHg bioaccumulation over time and space, as well as for assessing the potential risk and toxicological effects of MeHg on wildlife.

Science of the Total Environment↗

Approaches to highly parameterized inversion: PEST++ Version 5, a software suite for parameter estimation, uncertainty analysis, management optimization and sensitivity analysis

PEST++ Version 5 extends and enhances the functionality of the PEST++ Version 3 software suite, providing environmental modeling practitioners access to updated Version 3 tools as well as new tools to support decision making with environmental models. Version 5 of PEST++ includes tools for global sensitivity analysis (PESTPP-SEN); least-squares parameter estimation with integrated first-order, second-moment parameter and forecast uncertainty estimation (PESTPP-GLM); an iterative, localized ensemble smoother (PESTPP-IES); and a tool for management optimization under uncertainty (PESTPP-OPT). Additionally, all PEST++ Version 5 tools have a built-in fault-tolerant, multithreaded parallel run manager and are model independent, using the same protocol as the widely used PEST software suite. PEST++ Version 5 is consistent with PEST++ Version 3 conventions and design philosophy. The software’s emphasis continues to target efficient and optimized algorithms that have proven beneficial in decision-support settings and can accommodate large, highly parameterized problems. Expanded and new capabilities are now available to express uncertainty using Monte Carlo and analytical uncertainty approaches and allow evaluation of thousands to millions of parameters. New management optimization capabilities in Version 5 also allow environmental models to be used to answer management questions using multiple societal constraints in a risk-based framework. The PEST++ Version 5 software suite can be compiled for Microsoft Windows® and Unix-based operating systems such as Apple and Linux®; the source code is available with a Microsoft Visual Studio® 2019 solution; and CMake support for all three operating system is also provided. PEST++ Version 5 continues to build a foundation for an open-source framework capable of producing model-independent, robust, and efficient decision-support tools for large environmental models. The functionality of each of the PEST++ tools are demonstrated on a simple example problem. Implications of decisions used when using the PEST++ suite tools are also discussed.

Techniques and Methods↗

Field determination of microgram quantities of niobium in rocks

A rapid, simple, and moderately accurate method was needed for the determination of traces of niobium in rocks. The method developed is based on the reaction of niobium(V) with thiocyanate ion in a 4 M hydrochloric acid and 0.5 M tartaric acid medium, after which the complex is extracted with ethyl ether. The proposed procedure is applicable to rocks containing from 50 to 2000 p.p.m. of niobium, and, with modifications, can be used on rocks containing larger amounts. Five determinations on two rocks containing 100 p.p.m. or less of niobium agree within 5 p.p.m. of the mean, and the confidence limits at the 95% level are, respectively, ± 6 and ± 4 p.p.m. The addition of acetone to the ether extract of the niobium thiocyanate inhibits the polymerization of the thiocyanate ion and stabilizes the solution for at least 20 hours. The proposed procedure permits the determination of 20 γ of niobium in the presence of 1000 γ of iron, titanium, or uranium; 500 γ of vanadium; or 100 γ of tungsten or molybdenum or both.

Analytical Chemistry↗

Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon

In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al. 2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural production can provide critical insights into future management actions for this at-risk population. Multistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin. Typically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al. 2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model. The intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments. As is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because: • It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions. • Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty. • It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data. Thus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.

Idaho, Oregon, Washington, Wyoming↗

Reduction of taxonomic bias in diatom species data

Inconsistency in taxonomic identification and analyst bias impede the effective use of diatom data in regional and national stream and lake surveys. In this study, we evaluated the effect of existing protocols and a revised protocol on the precision of diatom species counts. The revised protocol adjusts four elements of sample preparation, taxon identification and enumeration, and quality control (QC). We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by three laboratories with a total of five analysts following established protocols (Charles et al. 2002), or their slight variations. The remaining datasets were produced by 1-3 laboratories with a total of 2-3 analysts following a revised protocol. The revised protocol included the following modifications: 1) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 2) random assignment of samples to analysts, 3) post-count identification and documentation of taxa (as opposed to an approach in which analysts assign names while they enumerate), and 4) increased use of QC samples. The revised protocol reduced taxonomic bias, as measured by reduction in analyst signal, and improved similarity among QC samples. Reduced taxonomic bias improves the performance of biological assessments, facilitates transparency across studies, and refines estimates of diatom species distributions.

Limnology and Oceanography: Methods↗

Comparison of δ13C analyses of individual foraminifer (Orbulina universa) shells by secondary ion mass spectrometry and gas source mass spectrometry

Rationale: The use of secondary ion mass spectrometry (SIMS) to perform micrometer-scale in situ carbon isotope (δ 13 C) analyses of shells of marine microfossils called planktic foraminifers holds promise to explore calcification and ecological processes. The potential of this technique, however, cannot be realized without comparison to traditional whole-shell δ 13 C values measured by gas source mass spectrometry (GSMS). Methods: Paired SIMS and GSMS δ 13 C values measured from final chamber fragments of the same shell of the planktic foraminifer Orbulina universa are compared. The SIMS–GSMS δ 13 C differences (Δ 13 C SIMS-GSMS ) were determined via paired analysis of hydrogen peroxide-cleaned fragments of modern cultured specimens and of fossil specimens from deep-sea sediments that were either untreated, sonicated, and cleaned with hydrogen peroxide or vacuum roasted. After treatment, fragments were analyzed by a CAMECA IMS 1280 SIMS instrument and either a ThermoScientific MAT-253 or a Fisons Optima isotope ratio mass spectrometer (GSMS). Results: Paired analyses of cleaned fragments of cultured specimens ( n = 7) yield no SIMS–GSMS δ 13 C difference. However, paired analyses of untreated ( n = 18) and cleaned ( n = 12) fragments of fossil shells yield average Δ 13 C SIMS-GSMS values of 0.8‰ and 0.6‰ (±0.2‰, 2 SE), respectively, while vacuum roasting of fossil shell fragments ( n = 11) removes the SIMS–GSMS δ 13 C difference. Conclusions: The noted Δ 13 C SIMS-GSMS values are most likely due to matrix effects causing sample–standard mismatch for SIMS analyses but may also be a combination of other factors such as SIMS measurement of chemically bound water. The volume of material analyzed via SIMS is ~10 5 times smaller than that analyzed by GSMS; hence, the extent to which these Δ 13 C SIMS-GSMS values represent differences in analyte or instrument factors remains unclear.

Rapid Communications in Mass Spectrometry↗

Age constraints on Jerritt Canyon and other Carlin-type gold deposits in the western United States-relationship to mid-Tertiary extension and magmatism

Carlin-type gold deposits are difficult to date and a wide range of ages has been reported for individual deposits. Therefore, several methods were employed to constrain the age of the gold deposits in the Jerritt Canyon district. Dated igneous rocks with well-documented crosscutting relationships to ore provided the most reliable constraints. K/Ar and 40 Ar/ 39 Ar dates on igneous rocks are as follows: andesite dikes 324 Ma, sericitic alteration in andesite dikes 118 Ma, basalt dikes 40.8 Ma, quartz monzonite dikes 39.2 Ma, and calc-alkaline ignimbrites 43.1 to 40.1 Ma. Of these, only the andesite and basalt dikes are clearly altered and mineralized. The gold deposits are, therefore, younger than the 40.8 Ma basalt dikes. The sericitic alteration in the andesite dikes is unrelated to the gold deposits. A number of dating techniques did not work. K/Ar and 40 Ar/ 39 Ar dates on mica from mineralized Ordovician to Devonian sedimentary rocks gave misleading results. The youngest date of 149 Ma from the smallest <0.1-mu m-size fraction shows that the temperature (120 degrees -260 degrees C) and duration (?) of hydrothermal activity was insufficient to reset preexisting fine-grained micas in the host rocks. The temperature and duration was also insufficient to anneal fission tracks in zircon from Ordovician quartzites as they yield Middle Proterozoic dates in both mineralized and barren samples. Apatites were too small for fission track dating. Hydrothermal sulfides have pronounced crustal osmium isotope signatures ( 187 Os/ 188 Os initial = 0.9-3.6) but did not yield a meaningful isochron due to very low Re and Os concentrations and large analytical uncertainties. Paleomagnetic dating techniques failed because the hydrothermal fluids sulfidized nearly all of the iron in the host rocks leaving no remnant magnetism.When published isotopic dates from other Carlin-type deposits in Nevada and Utah are subject to the rigorous evaluation developed for the Jerritt Canyon study, most deposits can be shown to have formed between 42 and 30 Ma. K/Ar and 40 Ar/ 39 Ar dates on the youngest preore igneous rocks range from 41 to 32 Ma, whereas the oldest postore igneous rocks range from 35 to 33 Ma. Hydrothermal adularia from the Twin Creeks deposit yields similar 40 Ar/ 39 Ar dates of 42 Ma. K/Ar dates on supergene alunite range from 4 to 30 Ma. K/Ar and 40 Ar/ 39 Ar dates on micas separated from sedimentary (395-43 Ma) and igneous (145-38 Ma) rocks are usually much older than the gold deposits and most are suspect because they are from incompletely reset preore micas or from mixtures of preore and ore-stage mica. Fission track dates on zircons are also generally older than the deposits (169-35 Ma) and are not completely reset by mineralization. Apatites are likley to be reset by the hydrothermal systems (and by younger thermal events) and yield dates (83-22 Ma) that are younger than those from zircon. Independent support of a mid-Tertiary age is provided by the low delta D (sub H 2 O) values of hydrothermal fluids from 10 widely separated Carlin-type deposits (-134 + or - 23ppm). The low delta D (sub H 2 O) values are consistent with a mid-Tertiary age when the climate was cool but are inconsistent with the Cretaceous and Jurassic ages favored by some workers when the climate was warm. The age and distribution of Carlin-type deposits coincides with areas that underwent extension and calc-alkaline magmatism over the same time period. Despite this relationship, the deposits lack clear spatial or genetic relationships to mid-Tertiary epizonal plutons. Rather, many deposits are localized along preexisting crustal fault zones. In the Getchell trend, structures tapped deep-sourced metamorphic (or magmatic) fluids and subsequently variably exchanged meteoric water. In the other trends and districts only variably exchanged meteoric water has been detected. These relationships suggest either that all of the deposits formed from deep-sourced fluids and were subsequently flooded by meteoric water, or, that fluids from different sources evolved to produce deposits with similar charateristics.

Economic Geology↗

Groundwater-quality data in the northern Coast Ranges study unit, 2009: Results from the California GAMA Program

Groundwater quality in the 633-square-mile Northern Coast Ranges (NOCO) study unit was investigated by the U.S. Geological Survey (USGS) from June to November 2009, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program's Priority Basin Project (PBP) and the U.S. Geological Survey National Water-Quality Assessment Program (NAWQA). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The NOCO study unit was the thirtieth study unit to be sampled as part of the GAMA-PBP. The GAMA Northern Coast Ranges study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer systems, and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer systems (hereinafter referred to as primary aquifers) are defined as that part of the aquifer corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the NOCO study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from the quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to surficial contamination. In the NOCO study unit, groundwater samples were collected from 58 wells in 2 study areas (Interior Basins and Coastal Basins) in Napa, Lake, Mendocino, Glenn, Humboldt, and Del Norte Counties. The 58 wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study areas. GAMA-PBP wells sampled as part of the spatially-distributed, randomized grid-cell network are referred to as "grid wells."The groundwater samples were analyzed for organic and special-interest constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, and perchlorate), naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and alkalinity), radioactive constituents (radon-222, radium isotopes, gross alpha and gross beta radioactivity, lead-210, and polonium-210), and microbial indicators (F-specific and somatic coliphage, Escherichia coli [E. coli] and total coliform). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), and dissolved noble gases also were measured to identify the sources and ages of the sampled groundwater. In total, 239 constituents and 12 field water-quality indicators were measured. Three types of quality-control samples (blanks, replicates, and matrix-spikes) were collected at up to 12 percent of the wells in the NOCO study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples generally were within the limits of acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 89 percent of the compounds. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwa

Data Series↗

Magnitude and Frequency of Floods on Nontidal Streams in Delaware

Reliable estimates of the magnitude and frequency of annual peak flows are required for the economical and safe design of transportation and water-conveyance structures. This report, done in cooperation with the Delaware Department of Transportation (DelDOT) and the Delaware Geological Survey (DGS), presents methods for estimating the magnitude and frequency of floods on nontidal streams in Delaware at locations where streamgaging stations monitor streamflow continuously and at ungaged sites. Methods are presented for estimating the magnitude of floods for return frequencies ranging from 2 through 500 years. These methods are applicable to watersheds exhibiting a full range of urban development conditions. The report also describes StreamStats, a web application that makes it easy to obtain flood-frequency estimates for user-selected locations on Delaware streams. Flood-frequency estimates for ungaged sites are obtained through a process known as regionalization, using statistical regression analysis, where information determined for a group of streamgaging stations within a region forms the basis for estimates for ungaged sites within the region. One hundred and sixteen streamgaging stations in and near Delaware with at least 10 years of non-regulated annual peak-flow data available were used in the regional analysis. Estimates for gaged sites are obtained by combining the station peak-flow statistics (mean, standard deviation, and skew) and peak-flow estimates with regional estimates of skew and flood-frequency magnitudes. Example flood-frequency estimate calculations using the methods presented in the report are given for: (1) ungaged sites, (2) gaged locations, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. Regional regression equations applicable to ungaged sites in the Piedmont and Coastal Plain Physiographic Provinces of Delaware are presented. The equations incorporate drainage area, forest cover, impervious area, basin storage, housing density, soil type A, and mean basin slope as explanatory variables, and have average standard errors of prediction ranging from 28 to 72 percent. Additional regression equations that incorporate drainage area and housing density as explanatory variables are presented for use in defining the effects of urbanization on peak-flow estimates throughout Delaware for the 2-year through 500-year recurrence intervals, along with suggestions for their appropriate use in predicting development-affected peak flows. Additional topics associated with the analyses performed during the study are also discussed, including: (1) the availability and description of more than 30 basin and climatic characteristics considered during the development of the regional regression equations; (2) the treatment of increasing trends in the annual peak-flow series identified at 18 gaged sites, with respect to their relations with maximum 24-hour precipitation and housing density, and their use in the regional analysis; (3) calculation of the 90-percent confidence interval associated with peak-flow estimates from the regional regression equations; and (4) a comparison of flood-frequency estimates at gages used in a previous study, highlighting the effects of various improved analytical techniques.

Scientific Investigations Report↗

Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem

Identifying and understanding status and trends in ecological indicators motivates continual monitoring over decades. Many programs rely on probability surveys and their companion design-based estimators for status assessments (e.g. Horvitz–Thompson). Design-based estimators do not easily extend to trend estimation nor situations with observation errors. Field-based monitoring efforts inevitably have turnover of field crew members which may affect consistency and accuracy of data collection over time. Additionally, design-based estimators ignore the complexities of spatial and temporal heterogeneity in an ecological indicator and how this variability may be linked to environmental or biological dynamics. We propose monitoring programs should re-evaluate their prescribed statistical methods, consider model-based approaches and adapt their sampling designs as needed to improve inferences. The Greater Yellowstone Ecosystem, home to two of the most iconic U.S. National Parks, has experienced significant declines in whitebark pine Pinus albicaulis communities due to forest pathogens, insect outbreaks, wildland fires and drought. Whitebark pine is a keystone species found in mountainous environments throughout the Western U.S. and Canada. We assessed the design-based ratio estimator originally recommended for estimating prevalence of white pine blister rust Cronartium ribicola . We compared the design-based estimator to a model-based approach that accounts for the sampling design, imperfect detection and allows for infection probabilities to vary over space and time. Ignoring observation errors led to lower estimated prevalence of white pine blister rust in the general population. Using model-based approaches, we found that the probability of infection has increased since 2004. However, overall prevalence likely has not changed because of the mountain pine beetle Dendroctonus ponderosae -induced shift towards smaller diameter trees that have a lower probability of infection compared to their larger cohorts. Synthesis and Applications . Using a design-based approach to detect change in ecological indicators falls short because of the inability to account for observation errors or to explore environmental or biological factors explaining temporal dynamics. Inherently understanding the mechanisms leading to changes in an ecological indicator over time informs potential management actions. Our assessment underscores the need for continued evaluation and updating of a monitoring program's sampling design and analytical procedures to maintain relevancy.

Wyoming↗

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

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

Southern Economic Journal↗

Applications of optical sensors for high-frequency water-quality monitoring and research

The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects &ndash; as well as the continued development of common methodologies and protocols for sensor use &ndash; will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013&ndash;5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En

Conference Paper↗

Summary of studies supporting cumulative effects analysis of upper Yellowstone River channel modifications

During the last several decades, portions of the upper Yellowstone River have been modified for flood control and erosion prevention. The U.S. Army Corps of Engineers is responsible for administration of a permit program for evaluating construction activities affecting rivers, streams, and wetlands. The Corps regulates activities under the authority of Section 10 of the Rivers and Harbors Act and Section 404 of the Clean Water Act. Since assumption of jurisdiction in the mid-1970&rsquo;s, the Corps has processed a total of 156 permit actions for the upper Yellowstone River. Over two-thirds of the permit actions occurred during or after two consecutive large floods during 1996 and 1997. In response to concern regarding the potential environmental and ecological consequences of channel modification, the Corps, in conjunction with State and local government agencies, initiated a series of scientific studies to better understand the effects of channel modification in the upper Yellowstone River (Figure 1). These included preparation of wetland and riparian inventory maps (Bon, 2001); hydraulic modeling and flood-plain delineation; watershed land-cover assessment (Pick and Potter, 2003); historic bottomland use analysis (Brelsford and others, 2003); analysis of channel modification effects on fish habitat (Bowen and others, 2003); comparison of juvenile salmonid use of modified and unmodified habitats (Zale and Rider, 2003); analysis of riparian vegetation and flood-plain turnover (Merigliano and Polzin, 2003); study of the relations between riparian habitat and bird communities (Hansen and others, 2003); analyses of geomorphology and historical channel changes (Dalby and Robinson, 2003); socioeconomic assessment (BBC Research and Consulting, 2002); and sediment transport investigations and modeling (Holnbeck, 2003). This report is a summary of results from the individual scientific studies as they bear on future programmatic cumulative effects analyses of channel modification of the upper Yellowstone River. We do not attempt a formal, cumulative impact assessment in the sense of evaluating alternatives or future scenarios. The first section presents major findings of the resource studies in terms of temporal comparisons, spatial comparisons, and causal relations. In this section, we present a series of conceptual models or flow diagrams of the major causal pathways of cumulative impacts from channel modification. These represent major pathways of potential impact based on knowledge from other rivers, concerns expressed about the upper Yellowstone, and results from the scientific studies. These diagrams serve to focus interpretation of study results as either supporting or not supporting the importance and magnitude of particular causal relations and to identify key linking variables appearing in multiple causal pathways. These key variables that connect channel modification actions to multiple, valued environmental attributes can serve as the foundation for both projecting and monitoring future responses of the system. A section on analytical realities outlines some of the limitations of projecting cumulative impacts from channel modification of the upper Yellowstone River on meaningful spatial and temporal scales and some of the difficulties of interpreting results from studies conducted shortly after two extreme floods and substantial increases in channel modification. A section on classification describes the two primary geomorphic classification systems of the upper Yellowstone River used in the various individual resource studies. Each of these systems has been valuable in supporting field sampling and expressing results concerning patterns of variation. Their integration or revision into a classification system to achieve some new purpose, such as a regulatory program or monitoring system, will depend on a crisp articulation of riverine management or regulatory objectives. A section on key variables identifies those that are central to the causal pathways connecting channel modification to impacts and provides a rationale for key variables as an alternative to other tools such as Proper Functioning Condition (Barrett and others, 1993), Index of Biotic Integrity (Karr, 1981), or the Synoptic Approach (Liebowitz and others, 1992). This section also explains relations among key variable to Hydrogeomorphic (HGM) assessment procedures (Hauer and Smith, 1998; Hauer and others, 2001) and outlines how these 2 variables might be monitored to track cumulative impacts. Examples of how selected key variables can be quantified using Geographic Information System data sets developed from the resource studies are presented for one reach. The largest portion of the document is an Appendix that summarizes each of the individual scientific studies in terms of scope and methods, findings, principal variables, and metrics used in the study or suggested by the study results, and important needs for further study.

Montana↗

A comparison of simultaneous plasma, atomic absorption, and iron colorimetric determinations of major and trace constituents in acid mine waters

Sixty-three water samples collected during June to October 1982 from the Leviathan/Bryant Creek drainage basin were originally analyzed by simultaneous multielement direct-current plasma (DCP) atomic-emission spectrometry, flame atomic-absorption spectrometry, graphite-furnace atomic-absorption spectrometry (GFAAS) (thallium only), ultraviolet-visible spectrometry, and hydride-generation atomic-absorption spectrometry.Determinations were made for the following metallic and semi-metallic constituents: AI, As, B, Ba, Be, Bi, Cd, Ca, Cr, Co, Cu, Fe(11), Fe(total), Li, Pb, Mg, Mn, Mo, Ni, K, Sb, Se, Si, Na, Sr, TI, V, and Zn. These samples were re-analyzed later by simultaneous multielement inductively coupled plasma (ICP) atomic-emission spectrometry and Zeeman-corrected GFAAS to determine the concentrations of many of the same constituents with improved accuracy, precision, and sensitivity. The result of this analysis has been the generation of comparative concentration values for a significant subset of the solute constituents. Many of the more recently determined values replace less-than-detection values for the trace metals; others constitute duplicate analyses for the major constituents. The multiple determinations have yielded a more complete, accurate, and precise set of analytical data. They also have resulted in an opportunity to compare the performance of the plasma-emission instruments operated in their respective simultaneous multielement modes. Flame atomic-absorption spectrometry was judged best for Na and K and hydride-generation atomic-absorption spectrometry was judged best for As because of their lower detection limit and relative freedom from interelement spectral effects. Colorimetric determination using ferrozine as the color agent was judged most accurate, precise, and sensitive for Fe. Cadmium, lead, and vanadium concentrations were too low in this set of samples to enable a determination of whether ICP or DCP is a more suitable technique. Of the remaining elements, Ba, Be, Ca, Cr, Mg, Mn, Sr, and Zn have roughly equivalent accuracy, precision, and detection limit by ICP and DCP. Cobalt and Ni were determined to be better analyzed by ICP, because of lower detection limits; B, Cu, Mo, and Si were determined to be better analyzed by DCP, because of relative freedom from interferences. The determination oral by DCP was far more sensitive, owing to the use of a more sensitive wavelength, compared with the ICP. However, there is a very serious potential interference from a strong Ca emission line near the 396.15 nanometer DCP wavelength. Thus, there is no clear choice between the plasma techniques tested, for the determination oral. The ICP and DCP detection limits are typically between 0.001 and 0.5 milligrams per liter in acid mine waters. For those metals best analyzed by ICP and/or DCP, but below these limits, GFAAS is the method of choice because of its relatively greater sensitivity and specificity. Six of the elements were not determined by DCP, ICP or Zeeman-corrected GFAAS, and are not discussed in this report. These elements are: Bi, Fe(11), Li, Sb, Se, and TI.

Water-Resources Investigations Report↗

A comparison of hydrocarbon-related landscape disturbance patterns along the New York-Pennsylvania border, 2004–2013

Executive Summary The New York-Pennsylvania area has a long history of hydrocarbon extraction, and the addition of shale gas extraction methods contributes to landscape disturbance borne by previously developed oil and non-shale gas resources. The main unconventional extraction method used to extract shale gas from the Marcellus Shale located in New York and Pennsylvania is hydraulic fracturing, or “fracking,” although other conventional methods are used extensively. All forms of hydrocarbon extraction disturb the surrounding landscape to some extent, primarily in the form of land clearance and degradation, road construction, and pipeline development, although the effects of these disturbances are not fully understood. In this study, landscape-change metrics and indicators are used to analyze change in a 10-county region along the New York-Pennsylvania border—the New York counties of Allegany, Steuben, Chemung, Tioga, and Broome, and the Pennsylvania counties of McKean, Potter, Tioga, Bradford, and Susquehanna. This 10-county region was selected due to the differences in policies between the States of New York and Pennsylvania. While fracking occurred extensively in Pennsylvania over the past 10 years or more, the State of New York issued a temporary moratorium against hydraulic fracturing in 2010—citing repercussions that might affect air quality, water quality, and public health—and officially banned hydraulic fracturing in June 2015. The quantification of landscape disturbance due to hydrocarbon extraction activities is presented in this report as land-use and land-cover (LULC) change between 2004 and 2013 and defined using specific disturbance categories (including well sites, roads, and pipelines) to compare the disturbances and changes, by county, on both sides of the New York-Pennsylvania border. The quantification was accomplished by gathering the signatures of disturbance from high-resolution aerial images, comparing the derived totals of disturbance, and then computing landscape metrics in a geographic information system (GIS) environment. The collected data represent a summation of landscape disturbance from oil and gas development, as some of the data represented were established decades earlier. The Analytical Tools Interface for Landscape Assessments (ATtILA) software was used to calculate land-cover area and landscape metrics for each shale gas, non-shale gas, oil, and other infrastructure types associated with hydrocarbons across each county and both five-county regions in the study area. The three primary metrics used to describe changes in forest structure were (1)forest area, (2) interior forest area, and (3) forest edge area. The changes in metrics were subsequently evaluated using the Pearson correlation coefficient. Overall, the disturbed-area footprint in the Pennsylvania region is considerably larger than the disturbed-area footprint in the New York region (13,687.9 hectares [ha] in Pennsylvania; 3,840.5 ha in New York). Disturbance per site is similar, with 1.2 disturbed ha per site in New York and 1.6 disturbed ha per site in Pennsylvania. In the New York-Pennsylvania 10-county region, hydrocarbon-development and extraction disturbance strongly correlate with a reduction in the percentage of forest for the entire region. This observation also appears to be true in the New York five-county region for forest area. This form of disturbance in the New York five-county region shows significantly correlated changes in forest metrics (–0.4 percent total forest area), particularly in the percentage of interior forest (–1.2 percent total area) and forest edge (+0.7 percent total area). On the other hand, gas and hydrocarbon-development and extraction disturbance (1.0 percent total area) in the Pennsylvania five-county region strongly correlates with a total decline in forest area and agricultural land area (–0.8 percent combined total area) but not with either land-cover class separately.

New York, Pennsylvania↗

User guide for the farm process (FMP1) for the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model, MODFLOW-2000

There is a need to estimate dynamically integrated supply-and-demand components of irrigated agriculture as part of the simulation of surface-water and ground-water flow. To meet this need, a computer program called the Farm Process (FMP1) was developed for the U.S. Geological Survey three-dimensional finite-difference modular ground-water flow model, MODFLOW- 2000 (MF2K). The FMP1 allows MF2K users to simulate conjunctive use of surface- and ground water for irrigated agriculture for historical and future simulations, water-rights issues and operational decisions, nondrought and drought scenarios. By dynamically integrating farm delivery requirement, surface- and ground-water delivery, as well as irrigation-return flow, the FMP1 allows for the estimation of supplemental well pumpage. While farm delivery requirement and irrigation return flow are simulated by the FMP1, the surface-water delivery to the farm can be simulated optionally by coupling the FMP1 with the Streamflow Routing Package (SFR1) and the farm well pumping can be simulated optionally by coupling the FMP1 to the Multi-Node Well (MNW) Package. In addition, semi-routed deliveries can be specified that are associated with points of diversion in the SFR1 stream network. Nonrouted surface-water deliveries can be specified independently of any stream network. The FMP1 maintains a dual mass balance of a farm budget and as part of the ground-water budget. Irrigation demand, supply, and return flow are in part subject to head-dependent sources and sinks such as evapotranspiration from ground water and leakage between the conveyance system and the aquifer. Farm well discharge and farm net recharge are source/sink terms in the FMP1, which depend on transpiration uptake from ground water and other head dependent consumptive use components. For heads rising above the bottom of the root zone, the actual transpiration is taken to vary proportionally with the depth of the active root zone, which can be restricted by anoxia or wilting. Depths corresponding to anoxia- or wilting-related pressure heads within the root zone are found using analytical solutions of a vertical pseudo steady-state pressure- head distribution over the depth of the total root zone (Consumptive Use Concept 1). Alternatively, a simpler, conceptual model is available, which defines how consumptive use (CU) components vary with changing head (CU Concept 2). Subtracting the ground water and precipitation transpiration components from the total transpiration yields a transpiratory irrigation requirement for each cell. The total farm delivery requirement (TFDR) then is determined as cumulative transpiratory and evaporative irrigation requirements of all farm cells and increased sufficiently to compensate for inefficient use from irrigation with respect to plant consumption. The TFDR subsequently is satisfied with surface- and ground-water delivery, respectively constrained by allotments, water rights, or maximum capacities. Five economic and noneconomic drought response policies can be applied optionally, if the potential supply of surface water and ground water is insufficient to meet the crop demand: acreage-optimization with or without a water conservation pool, deficit irrigation with or without water-stacking, and zero policy.

Techniques and Methods↗

The Amphibian Research and Monitoring Initiative (ARMI): 5-year report

The Amphibian Research and Monitoring Initiative (ARMI) is an innovative, multidisciplinary program that began in 2000 in response to a congressional directive for the Department of the Interior to address the issue of amphibian declines in the United States. ARMI&rsquo;s formulation was cross-disciplinary, integrating U.S. Geological Survey scientists from Biology, Water, and Geography to develop a course of action (Corn and others, 2005a). The result has been an effective program with diverse, yet complementary, expertise. ARMI&rsquo;s approach to research and monitoring is multiscale. Detailed investigations focus on a few species at selected local sites throughout the country; monitoring addresses a larger number of species over broader areas (typically, National Parks and National Wildlife Refuges); and inventories to document species occurrence are conducted more extensively across the landscape. Where monitoring is conducted, the emphasis is on an ability to draw statistically defensible conclusions about the status of amphibians. To achieve this objective, ARMI has instituted a monitoring response variable that has nationwide applicability. At research sites, ARMI focuses on studying species/environment interactions, determining causes of observed declines, and developing new techniques to sample populations and analyze data. Results from activities at all scales are provided to scientists, land managers, and policymakers, as appropriate. The ARMI program and the scientists involved contribute significantly to understanding amphibian declines at local, regional, national, and international levels. Within National Parks and National Wildlife Refuges, findings help land managers make decisions applicable to amphibian conservation. For example, the National Park Service (NPS) selected amphibians as a vital sign for several of their monitoring networks, and ARMI scientists provide information and assistance in developing monitoring methods for this NPS effort. At the national level, ARMI has had major exposure at a variety of meetings, including a dedicated symposium at the 2004 joint meetings of the Herpetologists&rsquo; League, the American Society of Ichthyologists and Herpetologists, and the Society for the Study of Amphibians and Reptiles. Several principal investigators have brought international exposure to ARMI through venues such as the World Congress of Herpetology in South Africa in 2005 (invited presentation by Dr. Gary Fellers), the Global Amphibian Summit, sponsored by the International Union for Conservation of Nature (IUCN) and Wildlife Conservation International, in Washington, D.C., 2005 (invited participation by Dr. P.S. Corn), and a special issue of the international herpetological journal Alytes focused on ARMI in 2004 (edited by Dr. C.K. Dodd, Jr.). ARMI research and monitoring efforts have addressed at least 7 of the 21 Threatened and Endangered Species listed by the U.S. Fish and Wildlife Service (California red-legged frog [Rana draytonii], Chiricahua leopard frog [R. chiricahuensis], arroyo toad [Bufo californicus], dusky gopher frog [Rana sevosa], mountain yellow-legged frog [R. muscosa], flatwoods salamander [Ambystoma cingulatum], and the golden coqui [Eleutherodactylus jasperi]), and 9 additional species of concern recognized by the IUCN. ARMI investigations have addressed time-sensitive research, such as emerging infectious diseases and effects on amphibians related to natural disasters like wildfire, hurricanes, and debris flows, and the effects of more constant, environmental change, like urban expansion, road development, and the use of pesticides. Over the last 5 years, ARMI has partnered with an extensive list of government, academic, and private entities. These partnerships have been fruitful and have assisted ARMI in developing new field protocols and analytic tools, in using and refining emerging technologies to improve accuracy and efficiency of data handling, in conducting amphibian disease, malformation, and environmental effects research, and in implementing a network of monitoring and research sites. Accomplishments from these endeavors include more than 40 publications on amphibian status and trends, nearly 100 publications on amphibian ecology and causes of declines, and over 30 methodological publications. Several databases have emerged as a result of ARMI and its partnerships; one, a digital atlas of ranges for all U.S. amphibian species, was used by the IUCN to display amphibian distribution maps in the Global Amphibian Assessment Project. Given the scope of ARMI and the panoply of projects, findings have had implications for policy. Investigations that demonstrate amphibian declines or illuminate causes of declines provide valuable information about habitat management, environmental effects, mechanisms for the spread of disease, and human/amphibian interfaces. This information has been made available to land managers, scientists, educators, Congress and other policymakers, and the public. The support afforded ARMI by Congress has been influential in the program&rsquo;s development and success. The value of ARMI&rsquo;s efforts will continue to increase as we are able to extend our studies spatially and temporally to answer critical questions with more confidence. We are using ARMI&rsquo;s resources efficiently and continuing to develop innovative mechanisms for leveraging resources for maximum effectiveness during challenging financial times. This report is a 5-year retrospective of the structure, methodology, progress, and contributions to the broader scientific community that have resulted from this national USGS program. We evaluate ARMI&rsquo;s success to date, with regard to the challenges faced by the program and the strengths that have emerged. We chart objectives for the next 5 years that build on current accomplishments, highlight areas meriting further research, and direct efforts to overcome existing weaknesses.

Scientific Investigations Report↗