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At least 577 records · Page 32Linked to original sources
USGS2016

Statistical analysis and mapping of water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, Miami-Dade County, Florida, 2000–2009

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000–2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000–2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990–1999 and 2000–2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974–2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990–1999 and 2000–2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990–1999 and 2000–2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000–2009 than during 1990–1999; and that inland water levels were generally lower during 2000–2009 than during 1990–1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990–1999. Mean October water levels during 2000–2009 were generally higher than during 1990–1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

Florida↗
USGS2015

A case study demonstrating analysis of stormflows, concentrations, and loads of nutrients in highway runoff and swale discharge with the Stochastic Empirical Loading and Dilution Model (SELDM)

Decisionmakers need information about the quality and quantity of stormwater runoff, the risk for adverse effects of runoff on receiving waters, and the potential effectiveness of mitigation measures to reduce these risks. The Stochastic Empirical Loading and Dilution Model (SELDM) uses Monte Carlo methods to generate stormflows, concentrations, and loads from a highway site and an upstream basin to provide needed risk-based information. SELDM was designed to help inform water-management decisions for streams and lakes receiving runoff from a highway or other land-use site. The purpose of this paper is to provide a brief description of SELDM and a hypothetical case study demonstrating the type of risk-based information that SELDM can provide. Total nitrogen (TN) and total phosphorus (TP) were selected as example constituents because nutrients are a common concern throughout the Nation and data for receiving waters, highway runoff, and the performance of best management practices (BMPs) are readily available for these constituents. The case study is hypothetical, but was formulated by using actual data from selected monitoring sites in New England. Data representing streamflow and water-quality were collected at U.S. Geological Survey (USGS) streamgage 01208950 Sasco Brook near Southport, CT, which has a drainage area of 7.38 square miles. In this hypothetical case study a 4-lane highway would replace the current 2-lane road and would have a contributing area of 2.2 acres between the topographic basin divides. Concentrations of TN and TP in highway runoff were simulated with data from USGS highway-runoff monitoring station 423027071291301 along State Route 2 in Littleton Massachusetts. Results of a highway-runoff analysis are shown in relation to three hypothetical discharge criteria for TN and two hypothetical discharge criteria for TP. The risks for exceeding TN discharge criteria of 3, 5, and 8 mg/L for highway runoff are 7.4, 0.83, and 0.13 percent of 1,721 runoff events that may occur during a stochastic 30-year simulation. If a grassy swale is used to treat the runoff, the risks for TN exceedances are reduced to 3.2, 0.33 and 0.03 percent, respectively. The risks for exceeding TP discharge criteria of 0.1 and 0.5 mg/L for highway runoff are 49 and 1.2 percent, respectively. If a grassy swale is used to treat the runoff, the risks for TP exceedances are 57 and 0.8 percent, respectively. The risks for the 0.1 mg/L criterion increase because swales can be a source of TP if pavement concentrations are low. The risks for the 0.5 mg/L criterion decrease because the swale is effective for reducing high TP concentrations. Although the results are mixed for storm-event concentrations, the grassy swale effectively reduces annual loads. Annual loads from the swale are, on average, about 49 percent of highway loads for TN and 62 percent of highway loads of TP because the swale reduces high runoff concentrations and stormflow volumes. Analysis of upstream and downstream concentrations indicates that runoff from the site of interest does not have a substantial effect on instream stormflow concentrations in this example simulation.

Conference Paper↗
USGS2017

Assessing the potential of translocating vulnerable forest birds by searching for novel and enduring climatic ranges

Hawaiian forest birds are imperiled, with fewer than half the original >40 species remaining extant. Recent studies document ongoing rapid population decline and pro- ject complete climate-based range losses for the critically endangered Kaua’i endemics ‘akeke’e (Loxops caeruleirostris) and ‘akikiki (Oreomystis bairdi) by end-of-century due to projected warming. Climate change facilitates the upward expansion of avian malaria into native high elevation forests where disease was historically absent. While intensi- fied conservation efforts attempt to safeguard these species and their habitats, the magnitude of potential loss and the urgency of this situation require all conservation options to be seriously considered. One option for Kaua’i endemics is translocation to islands with higher elevation habitats. We explored the feasibility of interisland translocation by projecting baseline and future climate-based ranges of ‘akeke’e and ‘akikiki across the Hawaiian archipelago. For islands where compatible climates for these spe- cies were projected to endure through end-of-century, an additional climatic niche overlap analysis compares the spatial overlap between Kaua’i endemics and current native species on prospective destination islands. Suitable climate-based ranges exist on Maui and Hawai’i for these Kaua’i endemics that offer climatically distinct areas compared to niche distributions of destination island endemics. While we recognize that any decision to translocate birds will include assessing numerous additional social, political, and biological factors, our focus on locations of enduring and ecologically compatible climate-based ranges represents the first step to evaluate this potential conservation option. Our approach considering baseline and future distributions of species with climatic niche overlap metrics to identify undesirable range overlap provides a method that can be utilized for other climate-vulnerable species with disjointed compatible environments beyond their native range.

Hawaii↗
USGS2009

The scientific assessment and strategy team contributions assessing the 1993 flood on the Mississippi and Missouri River basins

The Scientific Assessment and Strategy Team was formed to provide scientific advice and assistance to federal officials responsible for making decisions with respect to flood recovery in the Upper Mississippi River Basin (above Cairo, Illinois) as a result of the 1993 flooding. The team assembled data from a wide variety of sources within federal, state, and local governments, and the private sector. The huge volume of data (over 250 gigabytes) made analysis of all the data difficult. The locating, obtaining, and conversion of the data were extremely difficult leading to a recommendation for an on-line source or at least an on-line listing of available data. Parts of the data were analyzed and scientific bases were establishedfor discussions concerning levee effects on flood stages, effects of wetlands on flooding , effects of man 's increased intervention in the floodplains and uplands, and proposals regarding floodways on the nations rivers. The data collected indicated that the 1993 flooding could not be attributed to man's intervention on the floodplain but to the excessive amount of rainfall in the basin. The stormpatterns thatproduced the rainfall also moved south at about the same speed as the flood waters resulting in storms later in the summer reinforcing early floods. This resulted in a very long duration flood that overwhelmed existing flood reduction measures in the portions of the basin that were flooded.

Mississppi River basin, Missouri River basin↗
USGS2021

Testing a generalizable machine learning workflow for aquatic invasive species on Rainbow Trout (Oncorhynchus mykiss) in northwest Montana

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Alberta, British Columbia, Montana↗
USGS2014

Land cover mapping of Greater Mesoamerica using MODIS data

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: ( i ) qualitative assessment provided good insight in identifying and correcting gross errors; ( ii ) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest ( r 2  = 0.88), shrubland ( r 2  = 0.75), and cropland ( r 2  = 0.97) but weak positive association for grassland ( r 2  = 0.26); and ( iii ) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

Canadian Journal of Remote Sensing↗
USGS2012

Design and implementation of a structural health monitoring and alerting system for hospital buildings in the United States

This paper describes the current progress in the development of a structural health monitoring and alerting system to meet the needs of the U.S. Department of Veterans Affairs to monitor hospital buildings instrumented in high and very high seismic hazard regions in the U.S. The system, using the measured vibration data, is primarily designed for post-earthquake condition assessment of the buildings. It has two essential components – sensing and analysis. The sensing component includes all necessary firmware and sensors to measure the response of the building; while the analysis component consists of several data processing modules integrated into an open source software package which compresses a large amount of measured data into useful information to assess the building’s condition before and after an event. The information can be used for a rapid building safety assessment, and to support decisions for necessary repairs, replacements, and other maintenance and rehabilitation measures.

Conference Paper↗
USGS2019

Rapid station and network quality analysis for temporary deployments

Seismic station data quality is commonly defined by metrics such as data completeness or background seismic noise levels in specific frequency bands. However, for temporary networks such as aftershock deployments or induced seismicity monitoring, the most critical metric is often how well the station performs when recording events of interest. A timely measure of station performance can be used for real-time network maintenance and to help make decisions about which stations may need to be moved or are redundant. We develop new event-based methods to assess station and network performance, including estimating network magnitude of completeness, determining station signal-to-noise ratios as a function of earthquake magnitude, and computing relative station amplitudes. At times, a complete catalog of local seismic events may not exist, such as in an aftershock deployment where hundreds to thousands of small earthquakes may be happening and catalog generation efforts cannot keep up. To overcome this, we use an envelope of the average energy recorded by the network to identify events of interest. We find that the log amplitude of events identified using this technique scales linearly with local earthquake magnitudes. This suggests that this approach can be used to determine seismicity rates and detection thresholds.

Seismological Research Letters↗
USGS2016

A python framework for environmental model uncertainty analysis

We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

Environmental Modelling and Software↗
USGS2003

Preliminary analysis of cores from north San Francisco Bay, California

During the mid-to late-1800's, large quantities of tailings from hydraulic gold mining in the Sierra Nevada were deposited in San Francisco Bay (Gilbert, 1917; Jaffe et al., 1998; Capiella et al., 1999). This rapid deposition also choked river systems and deposited mercury-contaminated sediments in the rivers and Bay. Hydraulic mining was stopped in 1884 by a California Supreme Court decision. Deposition in the Bay slowed in the late 1800's and early 1900's as a result of this decrease in sediment supply (Jaffe et al., 1998; Capiella et al., 1999). During the mid-1900's, sediment supply was further reduced by water works projects (dams, diversions, etc.), creating an erosional system in the study area by the late 1900's. The re-working of these sediments poses environmental and biological concerns regarding mercury in the bay. The location of these deposits is important for understanding the health of the bay waters. In March 2000, the U.S. Geological Survey collected sediment cores in the study area to determine the location of mercury-contaminated hydraulic mining debris. The study area (Figure 1) comprises 400 km2 and consists of San Pablo Bay and Suisun Bay, both of which are part of the San Francisco Bay estuary. Grizzly Bay, a subembayment of Suisun Bay, is also part of the study area. For the purpose of this report the term Suisun Bay will be used collectively for both areas. The present channel system in Suisun Bay is composed of three channels that flow through the bay. The primary channel runs in the southern section of Suisun Bay. A smaller channel flows between Roe Island and Ryer Island. The deepest channel flows through Suisun Cutoff, north of Ryer Island, and past Grizzly Bay. All three channels join at Carquinez Strait where they continue through the southern section of San Pablo Bay, and into San Francisco Bay. The average depths in San Pablo and Suisun Bays at mean sea level are 3.7 m and 5.8 m, respectively (Smith et al., 2002).

California↗
USGS2026

Exploring trip preference heterogeneity in away-from-home birdwatchers using a discrete choice experiment

Birdwatching has grown in popularity worldwide and birdwatchers have emerged as an important constituency for wildlife and habitat conservation. To help promote wetland conservation, agencies and managers need to understand birdwatchers' desired trip experiences. We conducted national web-based surveys of American and Canadian birdwatchers by employing a discrete choice experiment to explore birdwatching trip preferences. We also collected information about participation in birdwatching and recreation specialization. We used latent class analysis to identify groups of birdwatchers with similar preferences. Our analysis indicated that birdwatchers were not homogeneous in their preferences. The seven attributes and associated attribute levels that were presented to participants (travel distance, site naturalness, bird rarity, the presence of waterfowl and wetlands, ease of access, species diversity and the number of birds seen) were all relevant, to varying degrees, in decisions about whether to take a birdwatching trip. We identified five latent classes of birdwatchers in the United States and Canada. ‘Nature seekers’ prioritised setting naturalness; ‘local birdwatchers’ strongly preferred shorter travel distances; ‘list-focused birdwatchers’ prioritised bird rarity and diversity; whereas ‘site-focused birdwatchers’ prioritised on-site characteristics above bird-related characteristics; and ‘casual birdwatchers’ were most likely to opt out of taking a trip. We found variation in recreation specialization and avidity levels across all the classes. Some classes ( e.g. list-focused birdwatchers) tend to be more specialised and more avid than others ( e.g. casual and local birdwatchers). Recognising the diversity of birdwatcher trip preferences can help outdoor recreation and wildlife managers provide a variety of suitable settings, services, and experiences.

Journal of Outdoor Recreation and Tourism↗
USGS2017

Forecast first: An argument for groundwater modeling in reverse

Numerical groundwater models are important compo-nents of groundwater analyses that are used for makingcritical decisions related to the management of ground-water resources. In this support role, models are oftenconstructed to serve a specific purpose that is to provideinsights, through simulation, related to a specific func-tion of a complex aquifer system that cannot be observeddirectly (Anderson et al. 2015). For any given modeling analysis, several modelinput datasets must be prepared. Herein, the datasetsrequired to simulate the historical conditions are referredto as the calibration model, and the datasets requiredto simulate the model’s purpose are referred to as theforecast model. Future groundwater conditions or otherunobserved aspects of the groundwater system may besimulated by the forecast model—the outputs of interestfrom the forecast model represent the purpose of themodeling analysis. Unfortunately, the forecast model,needed to simulate the purpose of the modeling analysis,is seemingly an afterthought—calibration is where themajority of time and effort are expended and calibrationis usually completed before the forecast model is evenconstructed. Herein, I am proposing a new groundwatermodeling workflow, referred to as the “forecast first”workflow, where the forecast model is constructed at anearlier stage in the modeling analysis and the outputsof interest from the forecast model are evaluated duringsubsequent tasks in the workflow.

Groundwater↗
USGS2014

Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem

Common Raven ( Corvus corax ) numbers and distribution are increasing throughout the sagebrush steppe, influencing avian communities in complex ways. Anthropogenic structures are thought to increase raven populations by providing food and nesting subsidies, which is cause for concern because ravens are important nest predators of sensitive species, including Greater Sage-Grouse ( Centrocercus urophasianus ). During 2007–2009, we located raven nests in southeastern Idaho and conducted a resource selection analysis. We measured variables at multiple spatial scales for 72 unique nest locations, including landscape-level vegetation characteristics and anthropogenic structures. Using generalized linear mixed models and an information-theoretic approach, we found a 31% decrease in the odds of nesting by ravens for every 1 km increase in distance away from a transmission line. Furthermore, a 100-m increase in distance away from the edge of two different land cover types decreased the odds of nesting by 20%, and an increase in the amount of edge by 1 km within an area of 102.1 ha centered on the nest increased the odds of nesting by 49%. A post hoc analysis revealed that ravens were most likely to nest near edges of adjoining big sagebrush ( Artemisia tridentata ) and land cover types that were associated with direct human disturbance or fire. These findings contribute to our understanding of raven expansion into rural environments and could be used to make better-informed conservation decisions, especially in the face of increasing renewable energy development.

Idaho↗
USGS2021

Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA

Background Humans are primary drivers of environmental contamination worldwide, including in drinking-water resources. In the United States (US), federal and state agencies regulate and monitor public-supply drinking water while private-supply monitoring is rare; the current lack of directly comparable information on contaminant-mixture exposures and risks between private- and public-supplies undermines tapwater (TW) consumer decision-making. Methods We compared private- and public-supply residential point-of-use TW at Cape Cod, Massachusetts, where both supplies share the same groundwater source. TW from 10 private- and 10 public-supply homes was analyzed for 487 organic, 38 inorganic, 8 microbial indicators, and 3 in vitro bioactivities. Concentrations were compared to existing protective health-based benchmarks, and aggregated Hazard Indices (HI) of regulated and unregulated TW contaminants were calculated along with ratios of in vitro exposure-activity cutoffs. Results Seventy organic and 28 inorganic constituents were detected in TW. Median detections were comparable, but median cumulative concentrations were substantially higher in public supply due to 6 chlorine–disinfected samples characterized by disinfection byproducts and corresponding lower heterotrophic plate counts. Public-supply applicable maximum contaminant (nitrate) and treatment action (lead and copper) levels were exceeded in private-supply TW samples only. Exceedances of health-based HI screening levels of concern were common to both TW supplies. Discussion These Cape Cod results indicate comparable cumulative human-health concerns from contaminant exposures in private- and public-supply TW in a shared source-water setting. Importantly, although this study’s analytical coverage exceeds that currently feasible for water purveyors or homeowners, it nevertheless is a substantial underestimation of the full breadth of contaminant mixtures documented in the environment and potentially present in drinking water. Conclusion Regardless of the supply, increased public engagement in source-water protection and drinking-water treatment, including consumer point-of-use treatment, is warranted to reduce risks associated with long-term TW contaminant exposures, especially in vulnerable populations.

Massachusetts↗
USGS2023

Recognizing political influences in participatory social-ecological systems modeling

Stakeholder participation in social-ecological systems (SES) modeling is increasingly considered a desirable way to elicit diverse sources of knowledge about SES behavior and to promote inclusive decision-making in SES. Understanding how participatory modeling processes function in the context of long-term adaptive management of SES may allow for better design of participatory processes to achieve the intended outcomes of inclusionary knowledge, representativeness, and social learning, while avoiding unintended outcomes. Long-term adaptive management contexts often include political influences -- attempts to shift or preserve power structures and authority, and efforts to represent the political and economic interests of stakeholders -- in the computer models that are used to shape policy making and implementation. In this research, we examine a period that included a major transition in the watershed model used for management of the Chesapeake Bay in the United States. The Chesapeake Bay watershed model has been in development since the 1980s, and is considered by many to be an exemplary case of participatory modeling. We use documentary analysis and interviews with participants involved in the model application and development transition to reveal a variety of ways in which participatory modeling may be subject to different kinds of political influences, some of which resulted in unintended outcomes, including: perceptions of difficulty updating the model in substantive ways, “gaming” of the model/participatory process by stakeholders, and increasing resistance against considering uncertainty in the system not captured by the model. This research suggests unintended or negative outcomes may be associated with both participatory decision-making and stakeholder learning even though they are so often touted as the benefits of participatory modeling. We end with a hypothesis that further development of a theory of computer model governance to bridge model impact and broader theories of environmental governance at the science-policy interface may result in improved SES modeling outcomes.

Maryland, Virginia↗
USGS2012

Developing a quality assurance plan for telemetry studies: A necessary management tool for an effective study

Telemetry has been used to answer various questions associated with research, management, and monitoring programs and to monitor animal behavior and population dynamics throughout the world. Many telemetry projects have been developed to study the passage, behavior, and survival of migrating adult and juvenile salmonids at hydroelectric projects on the mainstem Columbia and Snake rivers (Skalski et al. 2001a, 2001b; Skalski et al. 2002; Keefer et al. 2004; Goniea et al. 2006; Plumb et al. 2006). Telemetry based field evaluations of the survival of salmon through hydroelectric projects are costly because of the technology (tags, telemetry systems, infrastructure, etc.) and personnel required to conduct the evaluations. Given the cost of implementing these projects, and the financial and conservation implications of the decisions made from the research results (e.g., forgone electricity production and conservation of threatened and endangered animals), ensuring quality data are collected by documenting all procedures, training, data checks, and that sound protocols and quality assurance and control procedures are in place is paramount. Telemetry studies can pose unique data collection, processing, and analysis challenges. For instance, inferences about entire populations of animals are made from study animals that are captured, held, and tagged at disparate locations. Consequently great care must be taken to ensure that any potential biases that could arise from field procedures must be minimized (Peven et al. 2005). Interrogations of released study animals are remotely conducted by telemetry systems throughout the study area. The continuous recording of telemetry systems can result in large numbers of detections over a short time frame and the potential for false positive detections from records that are weak or erroneous. Thus, there is the potential to generate large data sets (many thousands of lines) that require significant postprocessing. Data reduction can be done using software or programming code within a software package or manually to discern noise from valid data and pull out the pertinent information for analysis. In either case, consistent well-documented procedures need to be in place to ensure quality results and allow for repeatability of study methods.

Book chapter↗
USGS2011

Incorporating parametric uncertainty into population viability analysis models

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Biological Conservation↗
USGS2012

Water monitoring to support the State of Illinois Governor's Drought Response Task Force -August 7, 2012

The U.S. Geological Survey (USGS) collects streamflow, groundwater level, and water-quality data for the State of Illinois and the Nation. Much of these data are collected every 15 minutes (real-time) as a part of the national network, so that water-resource managers can make decisions in a timely and reliable manner. Coupled with modeling and other water-resource investigations, the USGS provides data to the State during droughts and other hydrologic events. The types of data, capabilities, and presentation of these materials are described in this document as USGS Real-Time Data, Supplementary Data Collection and Analysis, and National Resources Available.

Illinois↗