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At least 55 records · Page 3Linked to original sources
USGS2015

Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas

In 2010, the U.S. Geological Survey, in cooperation with the San Antonio Water System, began a study to assess the brackish-water movement within the Edwards aquifer (more specifically the potential for brackish-water encroachment into wells near the interface between the freshwater and brackish-water transition zones, referred to in this report as the transition-zone interface) and effects on spring discharge at Comal and San Marcos Springs under drought conditions using a numerical model. The quantitative targets of this study are to predict the effects of higher-than-average groundwater withdrawals from wells and drought-of-record rainfall conditions of 1950–56 on (1) dissolved-solids concentration changes at production wells near the transition-zone interface, (2) total spring discharge at Comal and San Marcos Springs, and (3) the groundwater head (head) at Bexar County index well J-17. The predictions of interest, and the parameters implemented into the model, were evaluated to quantify their uncertainty so the results of the predictions could be presented in terms of a 95-percent credible interval. The model area covers the San Antonio and Barton Springs segments of the Edwards aquifer; the history-matching effort was focused on the San Antonio segment. A previously developed diffuse-flow model of the Edwards aquifer, which forms the basis for the model in this assessment, is primarily based on a conceptualization in which flow in the aquifer is predominately through a network of numerous small fractures and openings. Primary updates to this model include an extension of the active area downdip, a conversion to an 8-layer SEAWAT variable-density flow and transport model to simulate dissolved-solids concentration effects on water density, history matching to 1999–2009 conditions, and parameter estimation in a highly parameterized context using automated methods in PEST (a model-independent Parameter ESTimation code). In addition to the best-fit parameter values derived from history matching, the uncertainty of model parameters was also estimated by using linear uncertainty analysis. Comparison of “prior” (before history matching) and “posterior” (after history matching) variances of parameters indicate that the information within the observation dataset used for history matching informs many parameters. The concentration threshold parameters were well-informed by the observation dataset as their posterior distributions were much narrower than their prior distributions. The transition-zone scaling parameters of hydraulic conductivity, effective porosity, and specific storage were all informed by the observation dataset, as evidenced by the difference between the prior and posterior variances. Saline-zone scaling parameters, alternatively, were not informed by the observation dataset for effective porosity and specific storage. Resulting posterior drier-month, wetter-month, and annual recharge multiplier parameter variances are important to understanding how well recharge is estimated and implemented within the model. The shifts of the posterior distributions left and right indicate that there were zones where less or more water was needed in the model. The widths of the distributions were not decreased substantially, indicating that many of the best-fit recharge parameters are not statistically different from the initial values specified in the history-matching effort. Recharge from rainfall is the driving force behind groundwater flow and heads in the aquifer; therefore, an increase in understanding of this process would benefit model development by potentially decreasing the uncertainty of this parameter. The history-matching effort was most helpful in informing the parameters in the model that control discharge at springs, namely, the spring orifice (drain) altitude and drain conductance parameters for each spring. The uncertainty assessment of the predictive model (a hypothetical recurrence of 1950–56 drought conditions and higher-than-average groundwater withdrawals from wells) provided insights into the potential effects of these conditions on dissolved-solids concentration changes at production wells near the transition-zone interface, discharges at Comal and San Marcos Springs, and heads at Bexar County index well J-17. Results at the 25 production wells near the transition-zone interface indicate that the uncertainty of model input parameters based on expert knowledge yielded an upper bound of the 95-percent credible interval of dissolved-solids concentrations that exceeds the secondary drinking water standards of 1,000 milligrams per liter (mg/L) of the Texas Commission on Environmental Quality (TCEQ) for many wells. However, the history-matching process provided key information to inform prediction-sensitive model parameters and therefore, contributed to a substantial decrease of the upper bound of the 95-percent credible interval to below the secondary drinking water standards. Reductions in dissolved-solids concentration changes were on the order of 400 mg/L to 1,300 mg/L. The reduction in uncertainty in regards to this prediction implies that this prediction of dissolved-solids concentration change can be made with some certainty using this current model and that those parameters that control this prediction are informed by the observation dataset. Even though predictive uncertainty was reduced for this prediction, dissolved-solids concentration changes were still greater than zero, indicating a minimal increase in concentration at these 25 production wells during the 7-year simulation period is likely. However, this minimal concentration increase indicates a small potential for movement of the brackish-water transition zone near these wells during the 7-year simulation period of drought-ofrecord (1950–56) rainfall conditions with higher-than-average groundwater withdrawals by wells. Predictive results of total spring discharge during the 7-year period, as well as head predictions at Bexar County index well J-17, were much different than the dissolved-solids concentration change results at the production wells. These upper bounds are an order of magnitude larger than the actual prediction which implies that (1) the predictions of total spring discharge at Comal and San Marcos Springs and head at Bexar County index well J-17 made with this model are not reliable, and (2) parameters that control these predictions are not informed well by the observation dataset during historymatching, even though the history-matching process yielded parameters to reproduce spring discharges and heads at these locations during the history-matching period. Furthermore, because spring discharges at these two springs and heads at Bexar County index well J-17 represent more of a cumulative effect of upstream conditions over a larger distance (and longer time), many more parameters (with their own uncertainties) are potentially controlling these predictions than the prediction of dissolved-solids concentration change at the prediction wells, and therefore contributing to a large posterior uncertainty.

Texas↗
USGS2022

Modeling functional flows in California rivers

Environmental flows are critical to the recovery and conservation of freshwater ecosystems worldwide. However, estimating desired ranges of environmental flows across large, diverse landscapes is challenging. To advance protections of environmental flows for streams in California, USA, we developed a statewide modeling approach focused on functional components of the natural flow regime. Functional flow components in California streams—fall pulse flows, wet season peak flows and base flows, the spring flow recession, and dry season baseflows—support essential physical and ecological processes in riverine ecosystems. These functional flow components can be represented by functional flow metrics (FFMs) and quantified by their magnitude, timing, frequency, duration, and rate-of-change from daily streamflow records. After quantifying FFMs at reference-quality streamflow gages in California, we used machine-learning methods to estimate their natural range of values for all stream reaches in the state based on physical watershed characteristics and climatic factors. We found that the models performed well in predicting FFMs in streams across a diversity of landscape and climate contexts, according to several model performance criteria. Using the predicted FFM values, we established initial estimates of ecological flows that are expected to support critical functions and are broadly protective of ecosystem health. Modeling functional flows statewide offers a pathway for increasing the pace and scale of environmental flow protections in California and beyond.

California↗
USGS2019

The area under the precision‐recall curve as a performance metric for rare binary events

Species distribution models are used to study biogeographic patterns and guide decision‐making. The variable quality of these models makes it critical to assess whether a model's outputs are suitable for the intended use, but commonly used evaluation approaches are inappropriate for many ecological contexts. In particular, unrealistically high performance assessments have been associated with models for rare species and predictions over large geographic extents. We evaluated the area under the precision‐recall curve (AUC‐PR) as a performance metric for rare binary events, focusing on the assessment of species distribution models. Precision is the probability that a species is present given a predicted presence, while recall (more commonly called sensitivity) is the probability the model predicts presence in locations where the species has been observed. We simulated species at three levels of prevalence, compared AUC‐PR and the area under the receiver operating characteristic curve (AUC‐ROC) when the geographic extent of predictions was increased and assessed how well each metric reflected a model's utility to guide surveys for new populations. AUC‐PR was robust to species rarity and, unlike AUC‐ROC, not affected by an increasing geographic extent. The major advantages of AUC‐PR arise because it does not incorporate correctly predicted absences and is therefore less prone to exaggerate model performance for unbalanced datasets. AUC‐PR and precision were useful indicators of a model's utility for guiding surveys. We show that AUC‐PR has important advantages for evaluating models of rare species, and its benefits in the context of unbalanced binary responses will make it applicable for other ecological studies. By not considering the true negative quadrant of the confusion matrix, AUC‐PR ameliorates issues that arise when the geographic extent is increased beyond the species’ range or when a large number of background points are used when absence information is unavailable. However, no single metric captures all aspects of performance nor provides an absolute index that can be compared across datasets. Our results indicate AUC‐PR and precision can provide useful and intuitive metrics for evaluating a model's utility for guiding sampling, and can complement other metrics to help delineate a model's appropriate use.

Methods in Ecology and Evolution↗
USGS2013

Resilience to stress and disturbance, and resistance to Bromus tectorum L. invasion in cold desert shrublands of western North America

Alien grass invasions in arid and semi-arid ecosystems are resulting in grass–fire cycles and ecosystem-level transformations that severely diminish ecosystem services. Our capacity to address the rapid and complex changes occurring in these ecosystems can be enhanced by developing an understanding of the environmental factors and ecosystem attributes that determine resilience of native ecosystems to stress and disturbance, and resistance to invasion. Cold desert shrublands occur over strong environmental gradients and exhibit significant differences in resilience and resistance. They provide an excellent opportunity to increase our understanding of these concepts. Herein, we examine a series of linked questions about (a) ecosystem attributes that determine resilience and resistance along environmental gradients, (b) effects of disturbances like livestock grazing and altered fire regimes and of stressors like rapid climate change, rising CO 2 , and N deposition on resilience and resistance, and (c) interacting effects of resilience and resistance on ecosystems with different environmental conditions. We conclude by providing strategies for the use of resilience and resistance concepts in a management context. At ecological site scales, state and transition models are used to illustrate how differences in resilience and resistance influence potential alternative vegetation states, transitions among states, and thresholds. At landscape scales management strategies based on resilience and resistance—protection, prevention, restoration, and monitoring and adaptive management—are used to determine priority management areas and appropriate actions.

Ecosystems↗
USGS2026

Ecosystem metabolism as an early warning indicator of lake algal blooms

Algal blooms represent ecosystem state shifts that degrade drinking water, restrict recreation, threaten public health, and lower property values. Detecting blooms in advance on management relevant timescales of days to weeks can support proactive intervention. Early warning statistics derived from indicator time series offer a framework for detecting state shifts, but the use of lake metabolic estimates (gross primary production, ecosystem respiration, and net ecosystem production) in this context has been limited. Here, we modeled lake metabolism using water-quality monitoring data from eight U.S. lakes spanning a trophic gradient to test the hypothesis that metabolic estimates serve as effective early warning indicators of algal blooms. Time series of early warning statistics were analyzed using the conventional Kendall’s tau approach and a complementary threshold-based approach. The threshold-based approach yielded higher bloom detection rates, longer early warning lead times, and fewer false alarms than the Kendall’s tau approach. Across lakes, metabolic metrics detected 86% of blooms, with the strongest early warning signals in oligotrophic, eutrophic, and hypereutrophic systems. However, directly measured water-quality parameters, particularly water temperature and chlorophyll concentration, were the primary early warning indicators of blooms. Overall, these results demonstrate that metabolic estimates can provide early warning signals of bloom development but are secondary to directly measured water-quality parameters, indicating a complementary rather than primary role in early bloom detection.

EarthArXiv↗
USGS2015

Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line

A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps. The availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗
USGS2015

Flood-inundation Maps for the Deerfield River, Franklin County, Massachusetts, from the Confluence with the Cold River Tributary to the Connecticut River

The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 30-mile reach of the Deerfield River from the confluence of the Cold River tributary to the Connecticut River in the towns of Charlemont, Buckland, Shelburne, Conway, Deerfield, and Greenfield in Franklin County, Massachusetts to assist land owners, and emergency management workers prepare for and recover from floods. Peak flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using current [2015] stage-discharge relations at two U.S. Geological Survey streamgages in the study reach—Deerfield River at Charlemont, MA (01168500) and Deerfield River near West Deerfield, MA (01170000)—and from documented high-water marks from the tropical storm Irene flood, which had between a 1- and 0.2-percent AEP. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the two streamgages. Two sets of flood-inundation map libraries were created from the modeled profiles. The library for the upstream, western portion of the modeled reach is 9.1 miles long, extends from just downstream of the confluence of the Deerfield River with the Cold River to just upstream of the confluence with Clesson Brook, and is calibrated to the Deerfield River at Charlemont, MA streamgage. The library for the downstream, eastern portion of the modeled reach is 8.9 miles long, extends from just downstream of the confluence of the Deerfield River with the South River to just upstream of the confluence with the Green River, and is calibrated to the Deerfield River near West Deerfield streamgage. Stages for mapped profiles of the upstream reach range from 8.7 feet (ft) at the local datum (525.6 ft when converted to the North American Vertical Datum of 1988 [NAVD 88]) to 25.7 ft (542.6 ft at NAVD 88) at the Charlemont streamgage, and stages for mapped profiles of the downstream reach range from 8.5 ft (165.2 ft at NAVD 88) to 29.0 ft (185.7 ft at NAVD 88) at the West Deerfield streamgage. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from 0.5-ft vertical accuracy light detection and ranging (lidar) data to create the two sets of flood-inundation maps. The availability of the flood-inundation maps at http://water.usgs.gov/osw/flood_inundation/, combined with information regarding current (near real-time) stage from the two U.S. Geological Survey streamgages in the study reach, can provide emergency management personnel and residents with information to aid in flood response activities, such as evacuations and road closures, and with postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗
USGS2015

Flood-Inundation Maps for the North River in Colrain, Charlemont, and Shelburne, Massachusetts, From the Confluence of the East and West Branch North Rivers to the Deerfield River

A series of 10 digital flood-inundation maps were developed for a 3.3-mile reach of the North River in Colrain, Charlemont, and Shelburne, Massachusetts, by the U.S. Geological Survey in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence of the East and West Branch North Rivers to the Deerfield River. Peak-flow estimates at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011, into historical context. The hydraulic model was calibrated by using the current [2015] stage-discharge relation at the U.S. Geological Survey streamgage North River at Shattuckville, MA (station number 01169000), and from documented high-water marks from the tropical storm Irene flood, which had a peak flow with approximately a 0.2-percent annual exceedance probability. A hydraulic model was used to compute water-surface profiles for 10 flood stages referenced to the streamgage and ranging from 6.6 feet (ft; 464.5 ft North American Vertical Datum of 1988 [which is approximately bankfull]) to 18.3 ft (476.2 ft North American Vertical Datum of 1988 [which is the stage of the 0.2-percent annual exceedance probability peak flow and exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft]. The mapped stages of 6.6 to 18.3 ft were selected to match the stages of flows for bankfull; the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities; and an incremental stage of 17.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 0.5-ft vertical accuracy to create a set of flood-inundation maps. The availability of the flood-inundation maps, combined with information regarding near-real-time stage from the U.S. Geological Survey North River at Shattuckville, MA streamgage can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events. Introduction

Massachusetts↗
USGS2016

Flood-inundation maps for the Green River in Colrain, Leyden, and Greenfield, Massachusetts, from U.S. Geological Survey streamgage 01170100 Green River near Colrain to the confluence with the Deerfield River

The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 14.3-mile reach of the Green River in Colrain, Leyden, and Greenfield, Massachusetts, to assist landowners and emergency management workers to prepare for and recover from floods. The river reach extends from the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage downstream to the confluence with the Deerfield River. A series of seven digital flood inundation maps were developed for the upper 4.4 miles of the river reach downstream from the stream. Flood discharges corresponding to the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows and the flood flows associated with the stages of 10.2, 12.4, and 14.4 feet (ft) at the Green River streamgage were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the Tropical Storm Irene flood of August 28, 2011 (stage 13.97 ft), into historical context. The hydraulic model was calibrated by using the current (2015) stage-discharge relation at the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage and from documented high-water marks from the Tropical Storm Irene flood, which had a flow higher than a 0.2-percent annual exceedance probability flood discharge. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from the 50-percent annual exceedance probability (bankfull flow) at 7.6 ft (439.8 ft above the North American Vertical Datum of 1988 [NAVD 88]) to 14.4 ft (446.7 ft NAVD 88), which exceeds the maximum recorded water level of 13.97 ft (Tropical Storm Irene) at the streamgage. The mapped stages of 7.6 to 14.4 ft were selected to match the stages for bankfull; the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities; incremental stages of 10.2 and 12.4 ft; and the maximum stage of the stage-discharge rating curve. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps. The availability of the flood-inundation maps, combined with information regarding near real-time stage from U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage, can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗
USGS2024

Monarch butterfly (Danaus plexippus) roost site-selection criteria and locations east of the Appalachian Mountains, U.S.A.

The monarch butterfly is a flagship species and pollinator whose populations have declined by 85% in the recent two decades. Their largest population overwinters in Mexico, then disperses across eastern North America during March to August. During September-December, they return south using two flyways, one that spans the central United States and another that follows the Atlantic coast. Migrating monarchs fly diurnally and roost in groups nocturnally. We sought to determine the criteria this species uses to select roost sites, and the landscape context where those sites are found. We developed species distribution models of the landscape context of Atlantic flyway roost sites via citizen scientist observations and environmental variables that affect monarchs in the adult stage prior to migration, using two algorithms (Maximum Entropy and Genetic Algorithm for Ruleset Prediction). We developed two model validation methods: a citizen scientist smartphone application and peer-informed comparisons with aerial imagery. Proximity to surface water, elevation, and vegetative cover were the most important criteria for monarch roost site selection. Our model predicted 2.6 million ha (2.9% of the study area) of suitable roosting habitat in the Atlantic flyway, with the greatest availability along the Atlantic coastal plain and Appalachian Mountain ridges. Conservation of this species is difficult, as monarchs range over both large areas and various habitat types, and most current monarch research and conservation efforts are focused on the breeding and overwintering periods. These models can serve to help prioritize surveys of roosting sites and conservation efforts during the monarchs’ fall migration.

Journal of Insect Behavior↗
USGS1995

Simulation models for conservative and nonconservative solute transport in streams

Solute transport in streams is governed by a suite of hydrologic and chemical processes. Interactions between hydrologic processes and chemical reactions may be quantified through a combination of field-scale experimentation and simulation modeling. Two mathematical models that simulate conservative and nonconservative solute transport in streams are presented. A model for conservative solutes that considers One Dimensional Transport with Inflow and Storage (OTIS) may be used in conjunction with tracer-dilution methods to quantify hydrologic transport processes (advection, dispersion, lateral inflow and transient storage). For nonconservative solutes, a model known as OTEQ may be used to quantify chemical processes within the context of hydrologic transport. OTEQ combines the transport mechanisms in OTIS with a chemical equilibrium sub-model that considers complexation, precipitation/dissolution and sorption. OTEQ has been used to quantify processes affecting trace metals in two streams in the Rocky Mountains of Colorado, USA.

Effects of scale on interpretation and management ↗
USGS2013

Exposure and effects of perfluoroalkyl substances in tree swallows nesting in Minnesota and Wisconsin, USA

The exposure and effects of perfluoroalkyl substances (PFASs) were studied at eight locations in Minnesota and Wisconsin between 2007 and 2011 using tree swallows (Tachycineta bicolor). Concentrations of PFASs were quantified as were reproductive success end points. The sample egg method was used wherein an egg sample is collected, and the hatching success of the remaining eggs in the nest is assessed. The association between PFAS exposure and reproductive success was assessed by site comparisons, logistic regression analysis, and multistate modeling, a technique not previously used in this context. There was a negative association between concentrations of perfluorooctane sulfonate (PFOS) in eggs and hatching success. The concentration at which effects became evident (150–200 ng/g wet weight) was far lower than effect levels found in laboratory feeding trials or egg-injection studies of other avian species. This discrepancy was likely because behavioral effects and other extrinsic factors are not accounted for in these laboratory studies and the possibility that tree swallows are unusually sensitive to PFASs. The results from multistate modeling and simple logistic regression analyses were nearly identical. Multistate modeling provides a better method to examine possible effects of additional covariates and assessment of models using Akaike information criteria analyses. There was a credible association between PFOS concentrations in plasma and eggs, so extrapolation between these two commonly sampled tissues can be performed.

Minnesota;Wisconsin↗
USGS1998

Overview of a workshop on screening methods for detecting potential (anti-) estrogenic/androgenic chemicals in wildlife

The U.S. Congress has passed legislation requiring the U.S. Environmental Protection Agency (U.S. EPA) to develop, validate, and implement screening tests for identifying potential endocrine-disrupting chemicals within 3 years. To aid in the identification of methods suitable for this purpose, the U.S. EPA, the Chemical Manufacturers Association, and the World Wildlife Fund sponsored several workshops, including the present one, which dealt with wildlife species. This workshop was convened with 30 international scientists representing multiple disciplines in March 1997 in Kansas City, Missouri, USA. Participants at the meeting identified methods in terms of their ability to indicate (anti-) estrogenic/androgenic effects, particularly in the context of developmental and reproductive processes. Data derived from structure-activity relationship models and in vitro test systems, although useful in certain contexts, cannot at present replace in vivo tests as the sole basis for screening. A consensus was reached that existing mammalian test methods (e.g., with rats or mice) generally are suitable as screens for assessing potential (anti-) estrogenic/ androgenic effects in mammalian wildlife. However, due to factors such as among-class variation in receptor structure and endocrine function, it is uncertain if these mammalian assays would be of broad utility as screens for other classes of vertebrate wildlife. Existing full and partial life-cycle tests with some avian and fish species could successfully identify chemicals causing endocrine disruption; however, these long-term tests are not suitable for routine screening. However, a number of short-term tests with species from these two classes exist that could serve as effective screening tools for chemicals inducing (anti-) estrogenic/androgenic effects. Existing methods suitable for identifying chemicals with these mechanisms of action in reptiles and amphibians are limited, but in the future, tests with species from these classes may prove highly effective as screens. In the case of invertebrate species, too little is known at present about the biological role of estrogens and androgens in reproduction and development to recommend specific assays.

Environmental Toxicology and Chemistry↗
USGS2013

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

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

Annals of Applied Statistics↗
USGS2018

GenEst statistical models—A generalized estimator of mortality

Introduction GenEst (a generalized estimator of mortality) is a suite of statistical models and software tools for generalized mortality estimation. It was specifically designed for estimating the number of bird and bat fatalities at solar and wind power facilities, but both the software (Dalthorp and others, 2018) and the underlying statistical models are general enough to be useful in various situations to estimate the size of open populations when detection probabilities and search coverages are less than 1. In this report, we outline the statistical models and data structures underlying the estimator. The models are numerous, complex, and intricately interwoven. Discussion begins with broad, high-level overviews of the general models. The lower-level technical details are then gradually added. Broader and less technical discussions on the general context and applications of the models and the use of the software are available in the software user guide (Simonis and others, 2018), vignettes bundled with the software, and the help files within the software itself.

Techniques and Methods↗
USGS2021

Space-for-time is not necessarily a substitution when monitoring the distribution of pelagic fishes in the San Francisco Bay-Delta

Occupancy models are often used to analyze long-term monitoring data to better understand how and why species redistribute across dynamic landscapes while accounting for incomplete capture. However, this approach requires replicate detection/non-detection data at a sample unit and many long-term monitoring programs lack temporal replicate surveys. In such cases, it has been suggested that surveying subunits within a larger sample unit may be an efficient substitution (i.e., space-for-time substitution). Still, the efficacy of fitting occupancy models using a space-for-time substitution has not been fully explored and is likely context dependent. Herein, we fit occupancy models to Delta Smelt ( Hypomesus transpacificus ) and Longfin Smelt ( Spirinchus thaleichthys ) catch data collected by two different monitoring programs that use the same sampling gear in the San Francisco Bay-Delta, USA. We demonstrate how our inferences concerning the distribution of these species changes when using a space-for-time substitution. Specifically, we found the probability that a sample unit was occupied was much greater when using a space-for-time substitution, presumably due to the change in the spatial scale of our inferences. Furthermore, we observed that as the spatial scale of our inferences increased, our ability to detect environmental effects on system dynamics was obscured, which we suspect is related to the tradeoffs associated with spatial grain and extent. Overall, our findings highlight the importance of considering how the unique characteristics of monitoring programs influences inferences, which has broad implications for how to appropriately leverage existing long-term monitoring data to understand the distribution of species.

Calfornia↗
USGS2002

Hierarchical modeling of population stability and species group attributes from survey data

Many ecological studies require analysis of collections of estimates. For example, population change is routinely estimated for many species from surveys such as the North American Breeding Bird Survey (BBS), and the species are grouped and used in comparative analyses. We developed a hierarchical model for estimation of group attributes from a collection of estimates of population trend. The model uses information from predefined groups of species to provide a context and to supplement data for individual species; summaries of group attributes are improved by statistical methods that simultaneously analyze collections of trend estimates. The model is Bayesian; trends are treated as random variables rather than fixed parameters. We use Markov Chain Monte Carlo (MCMC) methods to fit the model. Standard assessments of population stability cannot distinguish magnitude of trend and statistical significance of trend estimates, but the hierarchical model allows us to legitimately describe the probability that a trend is within given bounds. Thus we define population stability in terms of the probability that the magnitude of population change for a species is less than or equal to a predefined threshold. We applied the model to estimates of trend for 399 species from the BBS to estimate the proportion of species with increasing populations and to identify species with unstable populations. Analyses are presented for the collection of all species and for 12 species groups commonly used in BBS summaries. Overall, we estimated that 49% of species in the BBS have positive trends and 33 species have unstable populations. However, the proportion of species with increasing trends differs among habitat groups, with grassland birds having only 19% of species with positive trend estimates and wetland birds having 68% of species with positive trend estimates.

Ecology↗
USGS2020

A pheromone antagonist liberates female sea lamprey from a sensory trap to enable reliable communication

The evolution of male signals and female preferences remains a central question in the study of animal communication. The sensory trap model suggests males evolve signals that mimic cues used in nonsexual contexts and thus manipulate female behavior to generate mating opportunities. Much evidence supports the sensory trap model, but how females glean reliable information from both mimetic signals and their model cues remains unknown. We discovered a mechanism whereby a manipulative male signal guides reliable communication in sea lamprey ( Petromyzon marinus ). Migratory sea lamprey follow a larval cue into spawning streams; once sexually mature, males release a pheromone that mimics the larval cue and attracts females. Females conceivably benefit from the mimetic pheromone during mate search but must discriminate against the model cue to avoid orienting toward larvae in nearby nursery habitats. We tested the hypothesis that spawning females respond to petromyzonol sulfate (PZS) as a behavioral antagonist to avoid attraction to the larval cue while tracking the male pheromone despite each containing attractive 3-keto petromyzonol sulfate (3kPZS). We found 1) PZS inhibited electrophysiological responses to 3kPZS and abated preferences for 3kPZS when mixed at the same or greater concentrations, 2) larvae released more PZS than 3kPZS whereas males released more 3kPZS than PZS, and 3) mixtures of 3kPZS and PZS applied at ratios measured in larval and male odorants resulted in the discrimination observed between the natural odors. Our study elucidates how communication systems that arise via deception can facilitate reliable communication.

Proceedings of the National Academy of Sciences of↗