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At least 55 records · Page 3Linked to original sources
USGS2019

Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration

This chapter discusses an interdisciplinary and transdisciplinary project to understand the interactions of agriculture, climate, and water resources in the Central Great Plains as a coupled natural-human system. We focus on the Smoky Hills Watershed in Kansas, where we gathered socioeconomic, hydrological, and climatic data, along with ecological data on fish species. The project involved substantial stakeholder engagement, which was complicated by post-truth attitudes about climate science and environmental regulation by some groups. We discuss the challenges of team management, stakeholder engagement, and data integration for modeling, notably the incorporation of stakeholder support for environmental policy in the context of extreme climatic events. We conclude by offering a framework for good collaborative practice to manage the complications of crossing boundaries in transdisciplinary research and outreach.

Kansas↗
USGS1997

Pesticides in surface waters: distribution, trends, and governing factors

Pesticde use in agriculture and non-agriculture settings has increased dramatically over the last several decades. Concern about adverse effects on the environment and human health has spurred an enormous amount of research into their environmental behavior and fate. Pesticides in Surface Waters presents a comprehensive summary of this research. This book evaluates published studies that focus on measuring pesticide concentration. The studies chosen include peer reviewed scientific literature, government reports, laboratory studies, and those using microcosms and artificial streams and ponds. The authors used this information to develop their overview of pesticide contamination of surface waters. The exhaustive compilation of data along with the fundamental science make this book essential for those involved in pesticide use, environmental protection, water quality, and human or ecological risk assessment. Pesticides in Surface Waters covers the results of actual studies, sources of pesticides to surface water, fate and transport, and environmental significance. Hundreds of data-packed tables, maps, charts, and drawings illustrate the key points, making research and application easy and cost effective.

Book↗
USGS2014

Decision support system development at the Upper Midwest Environmental Sciences Center

A Decision Support System (DSS) can be defined in many ways. The working definition used by the U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) is, “A spatially based computer application or data that assists a researcher or manager in making decisions.” This is quite a broad definition—and it needs to be, because the possibilities for types of DSSs are limited only by the user group and the developer’s imagination. There is no one DSS; the types of DSSs are as diverse as the problems they help solve. This diversity requires that DSSs be built in a variety of ways, using the most appropriate methods and tools for the individual application. The skills of potential DSS users vary widely as well, further necessitating multiple approaches to DSS development. Some small, highly trained user groups may want a powerful modeling tool with extensive functionality at the expense of ease of use. Other user groups less familiar with geographic information system (GIS) and spatial data may want an easy-to-use application for a nontechnical audience. UMESC has been developing DSSs for almost 20 years. Our DSS developers offer our partners a wide variety of technical skills and development options, ranging from the most simple Web page or small application to complex modeling application development.

Upper Midwest↗
USGS2020

Statistical methods in water resources

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report. The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.

Techniques and Methods↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2012

Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools

Ecological indicators are science-based tools used to assess how human activities have impacted environmental resources. For monitoring and environmental assessment, existing species assemblage data can be used to make these comparisons through time or across sites. An impediment to using assemblage data, however, is that these data are complex and need to be simplified in an ecologically meaningful way. Because multivariate statistics are mathematical relationships, statistical groupings may not make ecological sense and will not have utility as indicators. Our goal was to define a process to select defensible and ecologically interpretable statistical simplifications of assemblage data in which researchers and managers can have confidence. For this, we chose a suite of statistical methods, compared the groupings that resulted from these analyses, identified convergence among groupings, then we interpreted the groupings using species and ecological guilds. When we tested this approach using a statewide stream fish dataset, not all statistical methods worked equally well. For our dataset, logistic regression (Log), detrended correspondence analysis (DCA), cluster analysis (CL), and non-metric multidimensional scaling (NMDS) provided consistent, simplified output. Specifically, the Log, DCA, CL-1, and NMDS-1 groupings were ≥60% similar to each other, overlapped with the fluvial-specialist ecological guild, and contained a common subset of species. Groupings based on number of species (e.g., Log, DCA, CL and NMDS) outperformed groupings based on abundance [e.g., principal components analysis (PCA) and Poisson regression]. Although the specific methods that worked on our test dataset have generality, here we are advocating a process (e.g., identifying convergent groupings with redundant species composition that are ecologically interpretable) rather than the automatic use of any single statistical tool. We summarize this process in step-by-step guidance for the future use of these commonly available ecological and statistical methods in preparing assemblage data for use in ecological indicators.

Ecological Indicators↗
USGS2008

Cliff swallows Petrochelidon pyrrhonota as bioindicators of environmental mercury, Cache Creek Watershed, California

To evaluate mercury (Hg) and other element exposure in cliff swallows (Petrochelidon pyrrhonota), eggs were collected from 16 sites within the mining-impacted Cache Creek watershed, Colusa, Lake, and Yolo counties, California, USA, in 1997-1998. Nestlings were collected from seven sites in 1998. Geometric mean total Hg (THg) concentrations ranged from 0.013 to 0.208 ??g/g wet weight (ww) in cliff swallow eggs and from 0.047 to 0.347 ??g/g ww in nestlings. Mercury detected in eggs generally followed the spatial distribution of Hg in the watershed based on proximity to both anthropogenic and natural sources. Mean Hg concentrations in samples of eggs and nestlings collected from sites near Hg sources were up to five and seven times higher, respectively, than in samples from reference sites within the watershed. Concentrations of other detected elements, including aluminum, beryllium, boron, calcium, manganese, strontium, and vanadium, were more frequently elevated at sites near Hg sources. Overall, Hg concentrations in eggs from Cache Creek were lower than those reported in eggs of tree swallows (Tachycineta bicolor) from highly contaminated locations in North America. Total Hg concentrations were lower in all Cache Creek egg samples than adverse effects levels established for other species. Total Hg concentrations in bullfrogs (Rana catesbeiana) and foothill yellow-legged frogs (Rana boylii) collected from 10 of the study sites were both positively correlated with THg concentrations in cliff swallow eggs. Our data suggest that cliff swallows are reliable bioindicators of environmental Hg. ?? Springer Science+Business Media, LLC 2007.

Archives of Environmental Contamination and Toxico↗
USGS2025

Quantifying the substantive influence of public comment on United States federal environmental decisions under NEPA

A citizen’s right to comment on, and criticize, government decisions makes a difference. The U.S. National Environmental Policy Act of 1969 (NEPA) institutionalized public engagement in environmental review in the belief it would lead to better decisions and more sustainable outcomes. But, 50 years later, NEPA’s public comment process has been criticized as costly and slow, while doing little to change outcomes. Data science now makes it possible to track progress and evaluate the influence of public participation. We examined 108 environmental impact statement (EIS) processes spanning 22 years. Our analysis revealed that public comments resulted in substantive decision alterations in 62% of cases, with 64% showing modifications to alternatives, 42% showing modifications to mitigation plans and 11% leading to the selection of an entirely new preferred alternative. When federal agencies changed project alternatives (78 EISs), 88% of the time (69 of the 78 EISs) they credited public comments as the reason. In 45 of the 108 EISs, agencies modified mitigation plans and credited public comments as the reason 100% of the time. Agencies only occasionally selected a new preferred alternative (21 out of 104 EISs), but when they did, they credited public comments as the reason 100% of the time. As the United States and the 190+ states and countries that have adopted NEPA’s example consider how to address environmental change, it is important to assess the role of public participation in environmental decision making. Our data say public comments matter.

Environmental Research Letters↗
USGS2023

Prioritizing science efforts to inform decision making on public lands

Public land management agencies in the US are committed to using science-informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

Frontiers in Ecology and the Environment↗
USGS2008

Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics

The main classes of statistical treatment of below-detection limit (left-censored) environmental data for the determination of basic statistics that have been used in the literature are substitution methods, maximum likelihood, regression on order statistics (ROS), and nonparametric techniques. These treatments, along with using all instrument-generated data (even those below detection), were evaluated by examining data sets in which the true values of the censored data were known. It was found that for data sets with less than 70% censored data, the best technique overall for determination of summary statistics was the nonparametric Kaplan-Meier technique. ROS and the two substitution methods of assigning one-half the detection limit value to censored data or assigning a random number between zero and the detection limit to censored data were adequate alternatives. The use of these two substitution methods, however, requires a thorough understanding of how the laboratory censored the data. The technique of employing all instrument-generated data - including numbers below the detection limit - was found to be less adequate than the above techniques. At high degrees of censoring (greater than 70% censored data), no technique provided good estimates of summary statistics. Maximum likelihood techniques were found to be far inferior to all other treatments except substituting zero or the detection limit value to censored data.

Environmental Science & Technology↗
USGS2002

Spatial data available on the web at http://mrdata.usgs.gov/

Earth science information is important to decisionmakers who formulate public policy related to mineral resource sustainability, land stewardship, environmental hazards, the economy, and public health. To meet the growing demand for easily accessible data, the Mineral Resources Program has developed, in cooperation with other Federal and State agencies, an Internet-based, data-delivery system that allows interested customers worldwide to download accurate, up-to-date mineral resource-related data at any time. All data in the system are spatially located and customers with Internet access and a modern Web browser can easily produce maps having user-defined overlays for any region of interest.

Fact Sheet↗
USGS2013

Spatial Relation Predicates in Topographic Feature Semantics

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Book chapter↗
USGS2023

The future of ecosystem assessments is automation, collaboration, and artificial intelligence

Robust and routine ecosystem assessments will be fundamental to track progress towards achieving this decade’s global environmental and sustainability goals. Here we examine four needs that address common failure points of ecosystem assessments. These are (1) developing rapid, reproducible, and repeatable ecological data workflows, (2) harmonizing in situ and remotely sensed data, (3) integrating socioeconomic and biophysical data, and (4) increasing access to the digital resources and cyberinfrastructure needed to perform assessments. These four needs have profound potential to help us achieve our environmental objectives through cross-sector collaborations that leverage advancements in digital resources, remote data streams, and data science.

Environmental Research Letters↗
USGS2019

Simultaneous autoregressive (SAR) model

Simultaneous autoregressive (SAR) models are useful for accommodating various forms of dependence among data that have discrete support in a space of interest. These models are often specified hierarchically as mixed-effects regression models with first-moment structure controlled by a conventional linear regression term and second-moment structure induced by correlated random effects. In their general form, SAR models resemble conditional autoregressive (CAR) models, and can be made equivalent but are often parameterized differently. Importantly, SAR models can be specified by simultaneously regressing a discrete spatial process on itself. Thus, they allow one to construct statistical models for processes with directional graphical properties that pertain to data generating mechanisms. Most commonly SAR models have been used to account for structure among data with areal spatial support in applications involving ecology, epidemiology, sociology, and environmental science.

Book chapter↗
USGS2009

Methodology for an integrative assessment of China's ecological restoration programs

While research projects have been conducted to examine the impacts and effectiveness of China's ecological restoration programs, few of them represent integrated, systematic efforts. The objective of this chapter is thus to articulate and outline a methodology for an integrative assessment, which, we believe, should embrace both the environmental and socioeconomic changes and engage investigations at multiple scales. Further, these investigations should be pursued through interdisciplinary collaboration with expertise from ecology, economics, hydrology, and geospatial, climate, and land change sciences. We argue that the deployment of geospatial capability, the use of longitudinal data, and the connection between science and policy should be the hallmarks of an integrative assessment. We also describe our general approach and specific models to quantify the environmental and socioeconomic impacts induced by implementing the restoration programs, and address the issue of how to overcome the challenges in generating the data needed for executing various empirical tasks. We hope that the adoption and application of this methodology will make a valuable contribution to a more robust and timely assessment as well as implementation of the ecological restoration programs in and outside of China.

Book chapter↗
USGS2002

Continental shelf GIS for the Monterey Bay National Marine Sanctuary

A marine sanctuary is an environment where the interests of science and society meet. Land and marine managers need access to the best scientific data available that describe the environment and environmental processes in sanctuaries. The sidescan sonar imagery, bathymetry, sample analyses and other data discussed in the papers in this volume have been made available as a U.S. Geological Survey CDROM publication. ?? 2002 Elsevier Science B.V. All rights reserved.

Marine Geology↗
USGS2021

Opportunities and challenges of macrogenetic studies

The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.

Nature Reviews Genetics↗
USGS2014

Reflections on a vision for integrated research and monitoring after 15 years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Aquatic Geochemistry↗