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A guide to environmental DNA extractions for non-molecular trained biologists, ecologists, and conservation scientists

Ecologists, biologists, and conservation scientists are increasingly interested in the use of environmental DNA (eDNA) data for research and potentially decision-making. While commercial DNA extraction kits are typically user-friendly and accessible, they may fail to deliver the desired results with inherently complex eDNA samples, necessitating protocol optimization or educated selection of alternative approaches. To this end, knowledge of the basic steps and principles of DNA extractions is essential, but traditional education tracks in ecology, conservation, and environmental management typically do not include in-depth training in molecular methods. The primary objective of this paper is to enable scientists with an ecological background and limited molecular training to understand the four key steps of eDNA isolations, and to use this expertise to their advantage. We describe the purpose of commonly used reagents and chemicals, point out alternatives for each key step, explain the impact of certain choices regarding isolation approaches on DNA integrity and purity, and highlight the possibility of a tailor-made “mix and match” approach. We anticipate that this paper will enable field ecologists to develop a deeper understanding of the mechanisms and chemistry underlying eDNA extractions, thus allowing them to make informed decisions regarding the best eDNA extraction method for their research goals. Our intention is not to provide comprehensive, step-by-step protocols, but to offer guiding principles while highlighting alternative solutions. Finally, we hope that this paper will act as a useful resource to support knowledge transfer and teaching.

Environmental DNA↗

Landsat data ecosystem case study: Actor perceptions of the use and value of landsat

It is well-known that Earth observation (EO) data plays a critical role in scientific understanding about the global environment. There is also growing support for the use of EO data to provide context-specific insights, with significant implications for their use in decision support systems. Technological development over recent years, including cloud computing infrastructure, machine learning techniques, and rapid expansion of the velocity, volume, and variety of space-borne data sources, offer huge potential to provide solutions to the myriad environmental problems facing society and the planet. The USGS/NASA Landsat Program, the longest continuously gathered source of land surface data, has played a central role in our understanding of environmental change, particularly for its contribution of longitudinal products that offer greater context for present research and decision support activities. The challenge facing the Landsat and EO data community, however, now lies in moving beyond context-specific knowledge generation to translating such knowledge into tangible value for society. Drawing from an open data ecosystem framework and qualitative social science methods, we map the Landsat data ecosystem (LDE) and the relationships linking multiple actors responsible for processing, indexing, analyzing, synthesizing, and translating raw Landsat data into information that is useful, useable, and used by end users in particular social-environmental contexts. Both the role of Big Data and associated technologies are discussed as they relate to the ultimate use of Landsat-derived information products to guide decision-making, and key data ecosystem characteristics that shape the likelihood of these products’ use are highlighted.

Frontiers in Environmental Science↗

GenEst user guide—Software for a generalized estimator of mortality

GenEst (Generalized Estimator) is a software tool for estimating the total number of individuals arriving in an area during a specific time period when their detection probability is unknown but estimable. Its development was motivated by the need to accurately estimate the total number of bird and bat fatalities occurring at wind and solar energy facilities, but it is applicable in a variety of other contexts as well. Simple counts of carcasses are not an accurate measure of the true number of fatalities because some carcasses are inevitably missed in carcass searches. Furthermore, simple carcass counts do not allow comparison among locations or years because carcasses may be detected at different rates. This software uses data collected during carcass searches and estimates of detection rates to accurately estimate the number of fatalities and to provide a measure of precision associated with the estimate. These estimates are fundamental to understanding acute and cumulative effects of renewable energy development on wildlife populations. The software package is available with a user-friendly graphic interface as well as a flexible and powerful command-line implementation. GenEst includes tools for estimating searcher efficiency, carcass persistence, and other detection probability parameters from experimental field trials. Included in the software are example datasets for analyses, standard R package help files, this user guide, and vignettes detailing use at the command-line.

Techniques and Methods↗

A user guide to selecting invasive annual grass spatial products for the western United States

Invasive annual grasses (IAGs)—including Bromus tectorum (cheatgrass), Taeniatherum caput-medusae (medusahead), and Ventenata dubia (ventenata) species—present significant challenges for rangeland management by altering plant communities, impacting ecosystem function, reducing forage for wildlife and livestock, and increasing fire risk. Numerous spatial data products are used to map IAGs, and understanding the similarities, differences, and potential tradeoffs among these products is key to selecting the right maps for specific applications. This short guide outlines considerations for selecting regional- and national-scale spatial data to support the management of IAGs.

western United States↗

Stakeholder engagement to guide decision-relevant water data delivery

Water resources management and policy making require access to reliable scientific data. However, water managers may need to overcome various obstacles to accessing data. For example, insufficient technological infrastructures, low data literacy, and data format complexities often inhibit data user access. Thus, it is imperative to include stakeholders in the design of data delivery systems. The United States Geological Survey's Water Resources Mission Area is currently developing Integrated Water Availability Assessments (IWAAs) — multi-extent, stakeholder driven, near real-time water availability census and prediction for human and ecological uses. To provide appropriate user accessibility to data delivery systems developed for IWAAs, a user-centered design process including stakeholder focus groups was used to determine potential water data user needs and preferences. Focus groups identified five types of potential users: Public sector water resources managers, Public sector water resources manager data analysts, Industry and private companies, Tribal Nations, and Nonprofit organizations. Different water data user types depended on diverse spatial and temporal scale data. Public sector water resources managers benefitted most from data synthesized into user-friendly platforms and Public sector water resources data analysts preferred easy access to raw data. These findings can support the development of a water data delivery platform that meets a variety of user needs.

Journal of the American Water Resources Associatio↗

A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV)

Non-contact, remote sensing approaches to measuring flow velocities in river channels are widely used, but typical workflows involve acquiring images in the field and then processing data later in the office. To reduce latency between acquisition and output, with the ultimate goal of enabling real-time image velocimetry, we developed a Robot Operating System (ROS) package for Particle Image Velocimetry (PIV) that can be deployed on an embedded computer aboard an uncrewed aircraft system (UAS). The ROSPIV package consists of a series of nodes that can be run in parallel and comprise an end-to-end PIV workflow. Software development involved converting MATLAB code to C++, organizing files within a catkin workspace, and building nodes using catkin_make . The codebase is available via a repository that includes a user’s guide and demo script. This paper describes the nodes in the ROSPIV package as well as functions for preparing inputs, facilitating code generation, and visualizing PIV output. To illustrate the application of the software, we present two examples, one based on a simulated image sequence and the other based on data acquired from a UAS. For the simulated data, the velocity field derived via the ROSPIV package closely matched the known flow field used to generate the image sequence. Using real data as input demonstrated the ability of the ROSPIV package to ingest and pre-process raw images. Our initial results suggest that the ROSPIV package could become a viable approach for mapping river surface velocities in real time.

Software X↗

User's Guide for MapIMG 2: Map Image Re-projection Software Package

BACKGROUND Scientists routinely accomplish small-scale geospatial modeling in the raster domain, using high-resolution datasets for large parts of continents and low-resolution to high-resolution datasets for the entire globe. Direct implementation of point-to-point transformation with appropriate functions yields the variety of projections available in commercial software packages, but implementation with data other than points requires specific adaptation of the transformation equations or prior preparation of the data to allow the transformation to succeed. It seems that some of these packages use the U.S. Geological Survey's (USGS) General Cartographic Transformation Package (GCTP) or similar point transformations without adaptation to the specific characteristics of raster data (Usery and others, 2003a). Usery and others (2003b) compiled and tabulated the accuracy of categorical areas in projected raster datasets of global extent. Based on the shortcomings identified in these studies, geographers and applications programmers at the USGS expanded and evolved a USGS software package, MapIMG, for raster map projection transformation (Finn and Trent, 2004). Daniel R. Steinwand of Science Applications International Corporation, National Center for Earth Resources Observation and Science, originally developed MapIMG for the USGS, basing it on GCTP. Through previous and continuing efforts at the USGS' National Geospatial Technical Operations Center, this program has been transformed from an application based on command line input into a software package based on a graphical user interface for Windows, Linux, and other UNIX machines.

Open-File Report↗

Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley

The Land Capacity Potential Index (LCPI) is a coarse-scale index intended to delineate broad land-capability classes in the Lower Missouri River valley bottom from the Gavins Point Dam near Yankton, South Dakota to the mouth of the Missouri River near St. Louis, Missouri (river miles 811–0). The LCPI provides a systematic index of wetness potential and soil moisture-retention potential of the valley-bottom lands by combining the interactions among water-surface elevations, land-surface elevations, and the inherent moisture-retention capability of soils. A nine-class wetness index was generated by intersecting a digital elevation model for the valley bottom with sloping water-surface elevation planes derived from eight modeled discharges. The flow-recurrence index was then intersected with eight soil-drainage classes assigned to soils units in the digital Soil Survey Geographic (SSURGO) Database (Soil Survey Staff, 2010) to create a 72-class index of potential flow-recurrence and moisture-retention capability of Missouri River valley-bottom lands. The LCPI integrates the fundamental abiotic factors that determine long-term suitability of land for various uses, particularly those relating to vegetative communities and their associated values. Therefore, the LCPI provides a mechanism allowing planners, land managers, landowners, and other stakeholders to assess land-use capability based on the physical properties of the land, in order to guide future land-management decisions. This report documents data compilation for the LCPI in a revised and expanded, 72-class version for the Lower Missouri River valley bottom, and inclusion of additional soil attributes to allow users flexibility in exploring land capabilities.

Iowa, Kansas, Missouri, Nebraska, South Dakota↗

Environmental Flows for Riverine EcoSystem Habitats (E-FRESH) decision support tool user guide

The E-FRESH decision support tool is intended to facilitate assessment and comparison of different flow management scenarios on available habitat for various aquatic, riparian, and invertebrate species of interest. This tool also allows users to conduct a variety of analyses ranging from large-scale data processing and export to detailed and complex flow scenario manipulation around water rights and alternative climate futures.

Report↗

User's guide to SSARRMENU

The U.S. Geological Survey, in cooperation with Pierce County Department of Public Works, Washington, has developed an operational tool called the Puyallup Flood-Alert System to alert users of impending floods in the Puyallup River Basin. The system acquires and incorporates meteorological and hydrological data into the Streamflow Synthesis and Reservoir Regulation (SSARR) hydrologic flow-routing model to simulate floods in the Puyallup River Basin. SSARRMENU is the user-interactive graphical interface between the user, the input and output data, and the SSARR model. In a companion cooperative project with Pierce County, the SSARR model for the Puyallup River Basin was calibrated and validated. The calibrated model is accessed through SSARRMENU, which has been specifically programed for the Puyallup River and the needs of Pierce County. SSARRMENU automates the retrieval of data from ADAPS (Automated DAta Processing System, the U.S. Geological Survey?s real-time hydrologic database), formats the data for use with SSARR, initiates SSARR model runs, displays alerts for impending floods, and provides utilities to display the simulated and observed data. An on-screen map of the basin and a series of menu items provide the user wi

Open-File Report↗

FLOwPER user guide—For collection of FLOw PERmanence field observations

The accurate mapping of streams and their streamflow conditions in terms of presence or absence of surface water is important to both understanding physical, chemical, and biological processes in streams and to managing land, water, and ecological resources. This document describes a field form, FLOwPER (FLOw PERmanence), available within a mobile application (app), for standardized data collection of the presence or absence of surface flow in streams. The FLOwPER Database is a publicly available geodataset that can be used for research and management applications. This document provides instructions on how to (1) access and download the FLOwPER field form within the mobile app service, (2) use and complete a FLOwPER field form, and (3) view and download data from the FLOwPER Database.

Open-File Report↗

Ten practical questions to improve data quality

High-quality rangeland data are critical to supporting adaptive management. However, concrete, cost-saving steps to ensure data quality are often poorly defined and understood. Data quality is more than data management. Ensuring data quality requires 1) clear communication among team members; 2) appropriate sample design; 3) training of data collectors, data managers, and data users; 4) observer and sensor calibration; and 5) active data management. Quality assurance and quality control are ongoing processes to help rangeland managers and scientists identify, prevent, and correct errors in past, current, and future monitoring data. We present 10 guiding data quality questions to help managers and scientists identify appropriate workflows to improve data quality by 1) describing the data ecosystem, 2) creating a data quality plan, 3) identifying roles and responsibilities, 4) building data collection and data management workflows, 5) training and calibrating data collectors, 6) detecting and correcting errors, and 7) describing sources of variability. Iteratively improving rangeland data quality is a key part of adaptive monitoring and rangeland data collection. All members of the rangeland community are invited to participate in ensuring rangeland data quality.

Rangelands↗

HydroMet: A new code for automated objective optimization of hydrometeorological thresholds for landslide initiation

Landslide detection and warning systems are important tools for mitigation of potential hazards in landslide prone areas. Traditionally, warning systems for shallow landslides have been informed by rainfall intensity-duration thresholds. More recent advances have introduced the concept of hydrometeorological thresholds that are informed not only by rainfall, but also by subsurface hydrological measurements. Previously, hydrometeorological thresholds have been shown to improve capabilities for forecasting shallow landslides, and they may ultimately be adapted to more generalized landslide forecasting. We present HydroMet, a code developed in Python by the U.S. Geological Survey, which allows users to guide the automated estimation of hydrometeorological thresholds for a site or area of interest, with the flexibility to select preferred threshold variables for the antecedent hydrologic conditions and the triggering meteorological conditions. Users can import hydrologic time-series data, including rainfall, soil-water content, and pore-water pressure, along with the times of known landslide occurrences, and then conduct objective optimization of warning thresholds using receiver operating characteristics. HydroMet presents many additional options, including selecting the threshold formula, the timescale of possible threshold variables, and the skill statistics used for optimization. Users can develop dual-stage thresholds for watch and warning alerts, with a lower, risk-averse threshold to avoid missed alarms and a less conservative threshold to minimize false alarms. Users may also choose to split their inventory data into calibration and evaluation subsets to independently evaluate the performance of optimized thresholds. We present output and applications of HydroMet using monitoring data from landslide-prone areas in the U.S. to demonstrate its utility and ability to produce thresholds with limited missed and false alarms for informing the next generation of reliable landslide warning systems.

Water↗

Introduction

elemetry provides a powerful and flexible tool for studying aquatic animals, making it possible to repeatedly locate and identify individuals in remote or inaccessible settings—a task that would be difficult (if not impossible) to accomplish using other methods. The use of telemetry has increased dramatically in recent years, and its application is limited only by the capabilities of the equipment and the researcher’s imagination. In spite of these advantages, telemetry is equipment-intensive and generally requires more specialized knowledge and training than many other field techniques. The electronic equipment associated with its use can often dazzle, intimidate, and confuse those just starting out. Even experienced users are often hard-pressed to keep up with the technological advances. Answers to such basic questions as “what equipment do I need?” or “how do I get started?” are not always evident or straightforward. These are valid concerns, since the equipment and methods used can affect the success of the study and the quality of information collected. The purpose of this book is to provide a guide for using telemetry to study aquatic animals—call it a user’s manual or Telemetry 101. Our principal intent is to provide the basic information to plan, implement, and conduct telemetry studies under field conditions. Considerations related to data collection and interpretations are also discussed. As with any scientific procedure, collecting usable information and accurately interpreting study results depends on an understanding of the underlying principles of the methods used. A wide range of telemetry equipment and field techniques are available. Clearly defined research objectives and knowledge of the various options, capabilities, and limitations of the equipment and methods is essential for developing projects that effectively address the research or management questions being asked. Telemetry is a tool, and like any tool it will only function effectively when used properly.

Book chapter↗

User's guide to SEAWAT; a computer program for simulation of three-dimensional variable-density ground-water flow

The SEAWAT program was developed to simulate three-dimensional, variable-density, transient ground-water flow in porous media. The source code for SEAWAT was developed by combining MODFLOW and MT3DMS into a single program that solves the coupled flow and solute-transport equations. The SEAWAT code follows a modular structure, and thus, new capabilities can be added with only minor modifications to the main program. SEAWAT reads and writes standard MODFLOW and MT3DMS data sets, although some extra input may be required for some SEAWAT simulations. This means that many of the existing pre- and post-processors can be used to create input data sets and analyze simulation results. Users familiar with MODFLOW and MT3DMS should have little difficulty applying SEAWAT to problems of variable-density ground-water flow. MODFLOW was modified to solve the variable-density flow equation by reformulating the matrix equations in terms of fluid mass rather than fluid volume and by including the appropriate density terms. Fluid density is assumed to be solely a function of the concentration of dissolved constituents; the effects of temperature on fluid density are not considered. Temporally and spatially varying salt concentrations are simulated in SEAWAT using routines from the MT3DMS program. SEAWAT uses either an explicit or implicit procedure to couple the ground-water flow equation with the solute-transport equation. With the explicit procedure, the flow equation is solved first for each timestep, and the resulting advective velocity field is then used in the solution to the solute-transport equation. This procedure for alternately solving the flow and transport equations is repeated until the stress periods and simulation are complete. With the implicit procedure for coupling, the flow and transport equations are solved multiple times for the same timestep until the maximum difference in fluid density between consecutive iterations is less than a user-specified tolerance. The SEAWAT code was tested by simulating five benchmark problems involving variable-density ground-water flow. These problems include two box problems, the Henry problem, Elder problem, and HYDROCOIN problem. The purpose of the box problems is to verify that fluid velocities are properly calculated by SEAWAT. For each of the box problems, SEAWAT calculates the appropriate velocity distribution. SEAWAT also accurately simulates the Henry problem, and SEAWAT results compare well with those of SUTRA. The Elder problem is a complex flow system in which fluid flow is driven solely by density variations. Results from SEAWAT, for six different times, compare well with results from Elder's original solution and results from SUTRA. The HYDROCOIN problem consists of fresh ground water flowing over a salt dome. Simulated contours of salinity compare well for SEAWAT and MOCDENSE.

Techniques of Water-Resources Investigations↗

User's guide for U.S. Geological Survey rainfall-runoff models; revised 1977

Modified versions of the rainfall-runoff model described by Dawdy, Lichty, and Bergmann (1972) (see W72-11754) are used in the U.S. Geological Survey as a means of synthesizing flood discharges for small drainage areas. Synthesized flood discharges derived through use of long-term (60-70 year) rainfall and evaporation data, provide a more representative time base than do short-term (5-15 year) discharge records obtained by conventional stream gaging techniques. The rainfall, discharge, and evaporation data for use with rainfall-runoff models are stored in the Unit and Daily Values Files. Any of these data which were collected during the current or immediately preceding water year are stored on direct access, online disk files. Older data are stored in sequential files on magnetic tapes. Both the disks and tapes contain short-term data collected by the U.S. Geological Survey for calibration of models and long-term data for use in synthesis of long-term flood records. Information in this report provides guidelines for the assembly, storage, and retrieval of data needed to use these models, and also provides description and documentation of computer programs for model calibration and flood-record synthesis. (See also W74-11234) (Woodard-USGS)

Open-File Report↗

An interactive program to display user-generated or file-based maps on a personal computer monitor

PC MAP-MAKER is an ADVANCED BASIC program written to provide users of IBM XT, IBM AT, and compatible computers with a straight-forward, flexible method to display geographical data on a color or monochrome PC (personal computer) monitor. Data can be political boundaries such as State and county boundaries; natural curvilinear features such as rivers, drainage areas, and geological contacts; and points such as well locations and mineral localities. Essentially any point defined by a latitude and longitude and any line defined by a series of latitude and longitude values can be displayed using the program. PC MAP MAKER allows users to view tabular data from U.S. Geological Survey files such as WATSTORE (National Water Data Storage and Retrieval System) in a map format in a time much shorter than required by sending the data to a line plotter. The screen image can be saved to disk for recall at a later date, and hard copies can be printed with a dot matrix printer. The program is user-friendly, using menus or prompts to guide user input. It is fully documented and structured to allow the user to tailor the program to the user 's specific needs. The documentation includes a tutorial designed to introduce users to the capabilities of the program using the State of Colorado as a demonstration map area. (Author 's abstract)

Open-File Report↗

BioData: A national aquatic bioassessment database

BioData is a U.S. Geological Survey (USGS) web-enabled database that for the first time provides for the capture, curation, integration, and delivery of bioassessment data collected by local, regional, and national USGS projects. BioData offers field biologists advanced capabilities for entering, editing, and reviewing the macroinvertebrate, algae, fish, and supporting habitat data from rivers and streams. It offers data archival and curation capabilities that protect and maintain data for the long term. BioData provides the Federal, State, and local governments, as well as the scientific community, resource managers, the private sector, and the public with easy access to tens of thousands of samples collected nationwide from thousands of stream and river sites. BioData also provides the USGS with centralized data storage for delivering data to other systems and applications through automated web services. BioData allows users to combine data sets of known quality from different projects in various locations over time. It provides a nationally aggregated database for users to leverage data from many independent projects that, until now, was not feasible at this scale. For example, from 1991 to 2011, the USGS Idaho Water Science Center collected more than 816 bioassessment samples from 63 sites for the National Water Quality Assessment (NAWQA) Program and more than 477 samples from 39 sites for a cooperative USGS and State of Idaho Statewide Water Quality Network (fig. 1). Using BioData, 20 years of samples collected for both of these projects can be combined for analysis. BioData delivers all of the data using current taxonomic nomenclature, thus relieving users of the difficult and time-consuming task of harmonizing taxonomy among samples collected during different time periods. Fish data are reported using the Integrated Taxonomic Information Service (ITIS) Taxonomic Serial Numbers (TSN's). A simple web-data input interface and self-guided, public data-retrieval web site provides access to bioassessment data. BioData currently accepts data collected using two national protocols: (1) NAWQA and (2) U.S. Environmental Protection Agency (USEPA) National Rivers and Streams Assessment (NRSA). Additional collection protocols are planned for future versions.

Fact Sheet↗