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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 919 records · Page 51Linked to original sources
USGS2017

Fish assemblages

Methods to sample fishes in stream ecosystems and to analyze the raw data, focusing primarily on assemblage-level (all fish species combined) analyses, are presented in this chapter. We begin with guidance on sample site selection, permitting for fish collection, and information-gathering steps to be completed prior to conducting fieldwork. Basic sampling methods (visual surveying, electrofishing, and seining) are presented with specific instructions for estimating population sizes via visual, capture-recapture, and depletion surveys, in addition to new guidance on environmental DNA (eDNA) methods. Steps to process fish specimens in the field including the use of anesthesia and preservation of whole specimens or tissue samples (for genetic or stable isotope analysis) are also presented. Data analysis methods include characterization of size-structure within populations, estimation of species richness and diversity, and application of fish functional traits. We conclude with three advanced topics in assemblage-level analysis: multidimensional scaling (MDS), ecological networks, and loop analysis.

Book chapter↗
USGS2019

The influence of layout on Appalachian Trail soil loss, widening, and muddiness: Implications for sustainable trail design and management

This research investigates the influence of layout and design on the severity of trail degradation. Previous trail studies have been restricted by relatively small study areas which provide a limited range of environmental conditions and therefore produce findings with limited applicability; this research improves on this limitation by analyzing a representative sample of the Appalachian Trail with significant topographical, ecological, use-related, and managerial diversity. Many trail science studies have also focused on a singular form of trail degradation, whereas this study investigates all three core types of trail impact: trail soil loss, widening and muddiness. Relational analyses with all three indicators provide a more cohesive understanding of trail impact and reveal interrelationships between trail degradation processes. ANOVA testing of the mean values for these trail impact indicators across categories of influential independent factors confirms and refines the relevance of core trail design principles, specifically the sustainability advantages of trails with low grades and side-hill alignments. Findings also reveal and clarify the importance of landform grade in determining the susceptibility of trails to degradation and the influence of routing decisions; these relationships have received relatively little attention in the literature. The results also reveal several methodological considerations for trail alignment metrics and trail impact indicators

Connecticut, Georgia, Maine, Massachusetts, Maryla↗
USGS2025

Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation

ulturally, economically, and nutritionally valuable inland fisheries face many new challenges on top of chronic disturbances. In the upper midwestern United States, declines in cool- and coldwater fisheries have been observed, including ogaa/walleye Sander vitreus . In response to population declines, agencies have implemented rehabilitation efforts, and the frequency and intensity of efforts have increased recently given declines. Evaluating intervention outcomes is critical for institutional learning and to understand strategy effectiveness, but is difficult to do when multiple interventions are applied concurrently and in the absence of replication or controls. This review documents walleye rehabilitation efforts in the upper Midwest U.S., where a rehabilitation effort was defined as a coordinated effort with the stated intention to restore a self-sustaining population such that it required limited-to-no further intervention. We discuss: (1) strategies used; (2) similarities and differences in metrics of success; (3) factors leading to success; and (4) recommendations that may increase future successful rehabilitation. Strategies included harvest regulation changes, stocking, fish community manipulations, habitat enhancement, and partner discussions. Overall, evaluations of environmental, habitat, and fish community factors causing walleye population declines were not included in most rehabilitation plans before implementation. This review highlights an increased need for ecosystem-based fisheries management principles and cultivating ecological conditions that favor walleye as a potential path for future rehabilitation plans. Lessons drawn from rehabilitation plans are applicable to global inland fisheries to inform the conservation of declining fish populations.

Michigan, Minnesota, Wisconsin↗
USGS2017

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission. Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [ Cervus Canadensis ] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem. Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts. Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands. Synthesis and applications . Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.

Journal of Applied Ecology↗
USGS2025

Effects of flow on pesticides in water and zooplankton in the northern Sacramento-San Joaquin Delta

Zooplankton are a key food source for juvenile fishes in estuaries worldwide, including California’s Sacramento–San Joaquin Delta (hereafter Delta); both zooplankton quality and quantity are critical to ecosystem health. Zooplankton may be affected by pesticides in water and the food web, and the Delta is known to contain complex pesticide mixtures. In this study, we evaluated pesticide concentrations in water and zooplankton in the northern Delta during (1) the summer–fall of 2017, 2018, and 2019, which included periods of augmented pulse flows from agriculture tailwater, and (2) across a full seasonal cycle from May 2019 to March 2020. We quantified changes in pesticide concentration in response to environmental factors. We found that zooplankton showed more frequent detections of hydrophobic pesticides compared to more frequent detections of hydrophilic compounds in water. Pesticide concentrations were influenced by flow, pesticide application, and season, but the effects of these environmental factors differed by habitat (Sacramento River or Yolo Bypass Toe Drain). Pesticides in water responded similarly to environmental factors in the Sacramento River and Yolo Bypass, whereas pesticides in zooplankton responded differently. In water, we found more detections and higher concentrations at higher flows in the Yolo Bypass and Sacramento River, but responses to pesticide application varied by habitat. Alternatively, pesticide concentrations in zooplankton increased in the Yolo Bypass with increasing flow (correlated with flow pulses) and changed seasonally; whereas, pesticide concentrations in zooplankton in the Sacramento River decreased at higher flows, and decreased with or did not respond to higher pesticide application in the watershed. Our study suggests that augmented flows—particularly those using agricultural tailwater—may have unintended negative ecological effects that could partially offset benefits to the food web and fishes in the northern Delta, underscoring the complex interplay among factors that drive increased pesticide exposure.

California↗
USGS2019

Santa Barbara area coastal ecosystem vulnerability assessment

The Santa Barbara Area Coastal Ecosystem Vulnerability Assessment (SBA CEVA) is a multidisciplinary research project that investigates future changes to southern Santa Barbara County climate, beaches, watersheds, wetland habitats and beach ecosystems. The target audience is local land use planners and decision makers. The main objective is to provide information that assists the Cities of Santa Barbara, Carpinteria, and Goleta, the County of Santa Barbara, and UC Santa Barbara in climate adaptation planning with a clear focus on coastal ecosystems. Led by California Sea Grant, SBA CEVA was developed from the work of three of the state’s leading ecological and climatological research programs: UCSB’s Santa Barbara Coastal Long-Term Ecological Research (LTER) Program, the UCSD Scripps Institution of Oceanography (SIO) and their activities within the California and Nevada Applications Program Regional Integrated Science and Assessment (CNAP RISA), the California 4th Climate Assessment and the Southwest Climate Science Center Program, and USGS Coastal Storm Modeling System (CoSMoS)

California↗
USGS2026

A comprehensive inventory of communication tower infrastructure across the range of greater and Gunnison sage-grouse

We compiled and verified a comprehensive inventory dataset of communication tower infrastructure across the range of the greater sage-grouse ( Centrocercus urophasianus ) and Gunnison sage-grouse ( Centrocercus minimus ), two species of conservation concern that are viewed as ecosystem health indicators for the entire sagebrush biome within the United States. Our dataset includes all known towers with emphasis on validating construction year and month for towers built between 1990–2023. The annual spatial time series format of the data allows users to visualize, assess, and download tower locations and duration (including dates of construction and dismantlement) across the sagebrush biome of the western U.S. Tower data were acquired from publicly available infrastructure databases and records were filtered to include communication tower structures within the area of interest. Data records were validated and checked for accuracy with high resolution aerial and satellite imagery, and a subset were verified during field visits. The final filtered dataset comprises 4,322 tower sites, of which 3,528 tower site locations were verified via satellite imagery or field visits, and 794 were unverified tower sites (tower presence could not be confirmed via satellite imagery). Each tower record includes geographic coordinates, structure height, estimated date of construction, number of towers at each site, and, if applicable, date of dismantlement. The data product closes spatiotemporal gaps and resolves discrepancies present in other public versions of similar data and can be used in ecological research, infrastructure planning/siting/permitting, decision support tools for biological or landscape management, environmental assessments, or general use pertaining to the historic and current locations of communication infrastructure across sagebrush ecosystems.

western united States↗
USGS2026

Quantifying Landsat’s contributions to U.S. agricultural and forestry applications

The Landsat program has provided over 54 years of multispectral imagery, contributing vital information for agricultural and forestry scientific research and operational activities. Freely available Landsat data have enabled scientists to analyze land use patterns, assess ecological impacts, and develop strategies for sustainable management. We explored Landsat’s pivotal role through the lens of the United States Group on Earth Observations 2023 Earth Observation Assessment (EOA). The EOA included comprehensive surveys of more than 2000 federally supported Earth observation data products. We subsequently analyzed how Landsat satellite data and derived products support agricultural and forestry-related priorities compared to other Earth observation inputs. We evaluated both direct and indirect applications of the data, identifying key users across federal agencies and assessing how Landsat data contribute to critical products, services, and objectives. The results indicate that Landsat provides key information to support diverse activities across agriculture and forestry sectors, such as enhancing food supply, improving resilience to disaster and disturbance events, maximizing ecosystem productivity and conservation, and supporting regulatory requirements and decision-making. The Landsat OLI and TIRS sensors ranked 4th and 10th, respectively, out of 1171 Earth observation inputs identified in the study, underscoring their value to agriculture and forestry.

Remote Sensing↗
USGS2024

A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological ( n = 21) and chemical ( n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples ( n = 98) were collected biweekly, and sewage influent samples ( n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides , human Lachnospiraceae ) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.

Wisconsin↗
USGS2011

Monitoring carnivore populations at the landscape scale: occupancy modelling of tigers from sign surveys

1. Assessing spatial distributions of threatened large carnivores at landscape scales poses formidable challenges because of their rarity and elusiveness. As a consequence of logistical constraints, investigators typically rely on sign surveys. Most survey methods, however, do not explicitly address the central problem of imperfect detections of animal signs in the field, leading to underestimates of true habitat occupancy and distribution. 2. We assessed habitat occupancy for a tiger Panthera tigris metapopulation across a c. 38 000-km 2 landscape in India, employing a spatially replicated survey to explicitly address imperfect detections. Ecological predictions about tiger presence were confronted with sign detection data generated from occupancy sampling of 205 sites, each of 188 km 2 . 3. A recent occupancy model that considers Markovian dependency among sign detections on spatial replicates performed better than the standard occupancy model (ΔAIC = 184·9). A formulation of this model that fitted the data best showed that density of ungulate prey and levels of human disturbance were key determinants of local tiger presence. Model averaging resulted in a replicate-level detection probability [inline image] = 0·17 (0·17) for signs and a tiger habitat occupancy estimate of [inline image] = 0·665 (0·0857) or 14 076 (1814) km2 of potential habitat of 21 167 km 2 . In contrast, a traditional presence-versus-absence approach underestimated occupancy by 47%. Maps of probabilities of local site occupancy clearly identified tiger source populations at higher densities and matched observed tiger density variations, suggesting their potential utility for population assessments at landscape scales. 4. Synthesis and applications. Landscape-scale sign surveys can efficiently assess large carnivore spatial distributions and elucidate the factors governing their local presence, provided ecological and observation processes are both explicitly modelled. Occupancy sampling using spatial replicates can be used to reliably and efficiently identify tiger population sources and help monitor metapopulations. Our results reinforce earlier findings that prey depletion and human disturbance are key drivers of local tiger extinctions and tigers can persist even in human-dominated landscapes through effective protection of source populations. Our approach facilitates efficient targeting of tiger conservation interventions and, more generally, provides a basis for the reliable integration of large carnivore monitoring data between local and landscape scales.

Journal of Applied Ecology↗
USGS2016

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications. 2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers. 3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Methods in Ecology and Evolution↗
USGS2010

Supplementing seed banks to rehabilitate disturbed Mojave Desert shrublands: where do all the seeds go?

Revegetation of degraded arid lands often involves supplementing impoverished seed banks and improving the seedbed, yet these approaches frequently fail. To understand these failures, we tracked the fates of seeds for six shrub species that were broadcast across two contrasting surface disturbances common to the Mojave Desert—sites compacted by concentrated vehicle use and trenched sites where topsoil and subsurface soils were mixed. We evaluated seedbed treatments that enhance soil-seed contact (tackifier) and create surface roughness while reducing soil bulk density (harrowing). We also explored whether seed harvesting by granivores and seedling suppression by non-native annuals influence the success of broadcast seeding in revegetating degraded shrublands. Ten weeks after treatments, seeds readily moved off of experimental plots in untreated compacted sites, but seed movements were reduced 32% by tackifier and 55% through harrowing. Harrowing promoted seedling emergence in compacted sites, particularly for the early-colonizing species Encelia farinosa , but tackifier was largely ineffective. The inherent surface roughness of trenched sites retained three times the number of seeds than compacted sites, but soil mixing during trench development likely altered the suitability of the seedbed thus resulting in poor seedling emergence. Non-native annuals had little influence on seed fates during our study. In contrast, the prevalence of harvester ants increased seed removal on compacted sites, whereas rodent activity influenced removal on trenched sites. Future success of broadcast seeding in arid lands depends on evaluating disturbance characteristics prior to seeding and selecting appropriate species and seasons for application.

Mojave Desert↗
USGS2009

Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

Ecology↗
USGS2012

Power analysis and trend detection for water quality monitoring data. An application for the Greater Yellowstone Inventory and Monitoring Network

An important consideration for long term monitoring programs is determining the required sampling effort to detect trends in specific ecological indicators of interest. To enhance the Greater Yellowstone Inventory and Monitoring Network’s water resources protocol(s) (O’Ney 2006 and O’Ney et al. 2009 [under review]), we developed a set of tools to: (1) determine the statistical power for detecting trends of varying magnitude in a specified water quality parameter over different lengths of sampling (years) and different within-year collection frequencies (monthly or seasonal sampling) at particular locations using historical data, and (2) perform periodic trend analyses for water quality parameters while addressing seasonality and flow weighting. A power analysis for trend detection is a statistical procedure used to estimate the probability of rejecting the hypothesis of no trend when in fact there is a trend, within a specific modeling framework. In this report, we base our power estimates on using the seasonal Kendall test (Helsel and Hirsch 2002) for detecting trend in water quality parameters measured at fixed locations over multiple years. We also present procedures (R-scripts) for conducting a periodic trend analysis using the seasonal Kendall test with and without flow adjustment. This report provides the R-scripts developed for power and trend analysis, tutorials, and the associated tables and graphs. The purpose of this report is to provide practical information for monitoring network staff on how to use these statistical tools for water quality monitoring data sets.

Natural Resource Report↗
USGS2021

A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems

Accurately quantifying rates and patterns of biological nitrogen fixation (BNF) in terrestrial ecosystems is essential to characterize ecological and biogeochemical interactions, identify mechanistic controls, improve BNF representation in conceptual and numerical modelling, and forecast nitrogen limitation constraints on future carbon (C) cycling. While many resources address the technical advantages and limitations of different methods for measuring BNF, less systematic consideration has been given to the broader decisions involved in planning studies, interpreting data, and extrapolating results. Here, we present a conceptual and practical road map to study design, study execution, data analysis and scaling, outlining key considerations at each step. We address issues including defining N‐fixing niches of interest, identifying important sources of temporal and spatial heterogeneity, designing a sampling scheme (including method selection, measurement conditions, replication, and consideration of hotspots and hot moments), and approaches to analysing, scaling and reporting BNF. We also review the comparability of estimates derived using different approaches in the literature, and provide sample R code for simulating symbiotic BNF data frames and upscaling. Improving and standardizing study design at each of these stages will improve the accuracy and interpretability of data, define limits of extrapolation, and facilitate broader use of BNF data for downstream applications. We highlight aspects—such as quantifying scales of heterogeneity, statistical approaches for dealing with non‐normality, and consideration of rates versus ecological significance—that are ripe for further development.

Methods in Ecology and Evolution↗
USGS2026

An overview and participatory framework for choosing spatial boundaries in social–ecological systems modeling

A common challenge when modeling social–ecological systems (SESs) is defining the spatial extent of the system. Boundaries that do not adequately capture both social and ecological processes and their interactions can lead to mischaracterization of the system, while expanding boundaries too widely can impact model complexity and required resources. Socially, boundaries can invoke and influence identity, culture, power, and sense of place. Boundary decisions benefit from flexible, iterative approaches and the expertise of local communities. Here, we use a structured database search supplemented with citation searching to identify and review the literature that addresses choosing or defining spatial boundaries in SESs mapping or modeling and, when applicable, how participatory methods were used in the research process. In a review of the resulting 79 studies, we discovered that pre-existing social or ecological boundaries were used most frequently (36 and 18 publications, respectively). Twenty-one publications combined social and ecological boundaries or data to create custom boundaries, and four studies used an alternative approach to conventional boundaries. Informed by the literature review, we present a general framework for defining boundaries at the outset of SES research. We then connect the framework to a specific case study based on a collaborative project with Tribal, university, and federal scientists to develop a social–ecological climate adaptation plan. We present guiding questions alongside candidate boundaries for our study system and explore the tradeoffs of these boundary options, which can function as a useful template for other social–ecological research collaborations.

ISPRS International Journal of Geo-Information↗
USGS2013

Has the time come for big science in wildlife health?

The consequences of wildlife emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy, declines and extinctions of wildlife species, and subsequent loss of ecological integrity. Examples of health threats to wildlife include Batrachochytrium dendrobatidis , which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally; and the recently discovered Pseudogymnoascus (Geomyces) destructans , the etiologic agent of white nose syndrome which has caused precipitous declines of North American bat species. Of particular concern are the novel pathogens that have emerged as they are particularly devastating and challenging to manage. A big science approach to wildlife health research is needed if we are to make significant and enduring progress in managing these diseases. The advent of new analytical models and bench assays will provide us with the mathematical and molecular tools to identify and anticipate threats to wildlife, and understand the ecology and epidemiology of these diseases. Specifically, new molecular diagnostic techniques have opened up avenues for pathogen discovery, and the application of spatially referenced databases allows for risk assessments that can assist in targeting surveillance. Long-term, systematic collection of data for wildlife health and integration with other datasets is also essential. Multidisciplinary research programs should be expanded to increase our understanding of the drivers of emerging diseases and allow for the development of better disease prevention and management tools, such as vaccines. Finally, we need to create a National Fish and Wildlife Health Network that provides the operational framework (governance, policies, procedures, etc.) by which entities with a stake in wildlife health cooperate and collaborate to achieve optimal outcomes for human, animal, and ecosystem health.

EcoHealth↗
USGS2017

Turtles: Freshwater

With their iconic shells, turtles are morphologically distinct in being the only extant or extinct vertebrate animals to have their shoulders and hips inside their rib cages. By the time an asteroid hit the earth 65.5 million years ago, causing the extinction of dinosaurs, turtles were already an ancient lineage that was 70% through their evolutionary history to date. The remarkable evolutionary success of turtles over 220 million years is due to a combination of both conservative and effective life history traits and an essentially unchanging morphology that withstood the test of time. However, the life history traits of many species make them particularly susceptible to overharvest and habitat destruction in the modern world, and a majority of the world’s species face serious conservation challenges with several extinctions documented in modern times. The global plight of turtles is underscored by the fact that the percentage of imperiled species exceeds that of even the critically endangered primates. Freshwater turtles, with over 260 recognized species, have become a focus on a worldwide scale for many conservation issues. This article is a synthesis of a diverse body of information on the general biology of freshwater turtles, with particular emphasis on the extensive research on ecology, life history, and behavior that has been accomplished in the last half century. Much of the research has been applicable to the aforementioned conservation challenges. The studies presented include a combination of laboratory and field experiments and observational studies on this intriguing group of animals.

Book chapter↗