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At least 1,063 records · Page 59Linked to original sources
USGS2017

Reproductive ecology, spawning behavior, and juvenile distribution of Mountain Whitefish in the Madison River, Montana

Mountain Whitefish Prosopium williamsoni were historically common throughout much of the U.S. Intermountain West. However, within the last decade Mountain Whitefish have exhibited population-level declines in some rivers. In the Madison River, Montana, anecdotal evidence indicates Mountain Whitefish abundance has declined and the population is skewed toward larger individuals, which is typically symptomatic of recruitment problems. Describing reproductive development, spawning behavior, and juvenile distribution will form a foundation for investigating mechanisms influencing recruitment. We collected otoliths and gonadal samples from fish of all size-classes to characterize fecundity, age at maturity, and spawning periodicity. We implanted radio tags in mature Mountain Whitefish and relocated tagged fish in autumn 2012–2014. Timing of spawning was determined from spawning status of captured females and from density of eggs collected on egg mats. In spring 2014, we seined backwater and channel sites to describe age-0 whitefish distribution. Mountain Whitefish were highly fecund (18,454 eggs/kg body weight) annual spawners, and age at 50% maturity was 2.0 years for males and 2.6 years for females. In 2013 and 2014, spawning occurred between the third week of October and first week of November. During spawning, spawning adults and collected embryos were concentrated in the downstream 26 km of the study site, a reach characterized by a complex, braided channel. This reach had the highest CPUE of age-0 Mountain Whitefish, and the percentage of spawning adults in the 25 km upstream from a sampling site was positively associated with juvenile CPUE. Within this reach, age-0 Mountain Whitefish were associated with silt-laden backwater and eddy habitats. Future investigations on mechanisms influencing recruitment should be focused on the embryological phase and age-0 fish.

Montana↗
USGS2019

Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks

Conservation of long-distance migratory species poses unique challenges. Migratory connectivity—that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas—is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual-cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration and, in some cases, molt their flight feathers. These additional molt migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess landscape connectivity, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of over 500 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of the breeding, molting, wintering, and migration periods. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual-cycle movement patterns, including the central importance of staging and molting sites in James Bay and the St. Lawrence River to multi-species habitat connectivity. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

Ecological Applications↗
USGS1990

Growth and equilibrium in sea otter populations

(1) Counts through time were compiled for five sea otter ( Enhydra lutris ) populations in the north-east Pacific Ocean that were below equilibrium density: Attu Island, south-east Alaska, British Columbia, Washington State, and central California. Similar data were obtained from the equilibrium density population at Amchitka Island in 1971 and 1986. (2) Shorelines of Attu and Amchitka islands each were divided into forty-five segments, within which lineal (length of shore at mean higher high water) and areal (mean higher high water to the 10-fathom (18.3-m) depth contour) measures were made of the amount of habitat. (3) Rate of increase for the four northern populations was 17-20% year-1. Density- or size-dependent changes in rate of increase could not be demonstrated for any of these populations. The California population, in contrast, has undergone three apparent growth phases: the early 1900s to the mid-1970s when it increased about 5% year-1; the mid-1970s to the mid-1980s when it declined about 5% year-1; and the mid-1980s to 1988 when it increased about 7% year-1. An exponential growth model accounted for 92-98% of the variation in counts through time in all cases. (4) Population increase at Attu Island was achieved largely by range expansion as opposed to increased density. Range expansion in lineal and areal habitat occurred at 11% and 13% year-1, respectively; neither rate was lower (P > 0.25) than the observed rate of increase in numbers of animals counted. (5) Despite similarities in island size and physical environment, the most conservative estimates of population density at Amchitka Island were > 3 X greater than maximum density estimates for Attu Island. (6) Surveys of Amchitka Island from the mid-1930s through the mid-1980s indicate that the population increased to a peak in the 1940s; declined abruptly thereafter; and subsequently increased to a new and higher equilibrium in the 1960s, where it has since remained. (7) These population data, together with information on sea otter foraging and benthic community structure at Attu and Amchitka islands, suggest that multiple population equilibria exist in this system, emanating from complex trophic interactions low in the food web. I hypothesize that the lower population equilibrium is achieved largely or exclusively on an invertebrate diet consisting principally of herbivorous sea urchins. When unregulated by sea otter predation, the rocky benthos is deforested by sea urchin grazing. As growing otter populations compete increasingly for food, grazing intensity declines and the system shifts to one dominated by kelp beds, in turn leading to increased production, a shift in habitat structure, and population increases of kelp bed fishes. Apparently this new food resource elevates the sea otter population to a higher and more stable equilibrium.

Journal of Animal Ecology↗
USGS2003

Phosphorus in a ground-water contaminant plume discharging to Ashumet Pond, Cape Cod, Massachusetts, 1999

The discharge of a plume of sewagecontaminated ground water emanating from the Massachusetts Military Reservation to Ashumet Pond on Cape Cod, Massachusetts, has caused concern about excessive loading of nutrients, particularly phosphorus, to the pond. The U.S. Air Force is considering remedial actions to mitigate potentially adverse effects on the ecological characteristics of the pond from continued phosphorus loading. Concentrations as great as 3 milligrams per liter of dissolved phosphorus (as P) are in ground water near the pond's shoreline; concentrations greater than 5 milligrams per liter of phosphorus are in ground water farther upgradient. Temporary drive-point wells were used to collect water samples from 2 feet below the pond bottom to delineate concentration distributions in the pore waters of the pond-bottom sediments. Measurements in the field of specific conductance and colorimetrically determined orthophosphate concentrations provided real-time data to guide the sampling. The contaminant plume discharges to the Fishermans Cove area of Ashumet Pond as evidenced by elevated levels of specific conductance and boron, which are chemically conservative indicators of the sewage-contaminated ground water. Concentrations of nonconservative species, such as dissolved phosphorus, manganese, nitrate, and ammonium, also were elevated above background levels in ground water discharging to the pond, but in spatially complex distributions that reflect their distributions in ground water upgradient of the pond. Phosphorus concentrations exceeded background levels (greater than 0.10 milligram per liter) in the pond-bottom pore water along 875 feet of shoreline. Greatest concentrations (greater than 2 milligrams per liter) occurred within 30 feet of the shore in an area about 225 feet long. Calculations of phosphorus flux in the aquifer upgradient of Ashumet Pond, as determined from water-flux estimates from a steady-state ground-water-flow model and phosphorus concentrations (in 1999) from multilevel samplers about 75 feet upgradient of the pond, indicate that dissolved phosphorus moves towards the pond and discharges to it with the inflowing ground water at a rate as high as about 316 kilograms per year.

Massachusetts↗
USGS1999

The role of adaptive management as an operational approach for resource management agencies

In making resource management decisions, agencies use a variety of approaches that involve different levels of political concern, historical precedence, data analyses, and evaluation. Traditional decision-making approaches have often failed to achieve objectives for complex problems in large systems, such as the Everglades or the Colorado River. I contend that adaptive management is the best approach available to agencies for addressing this type of complex problem, although its success has been limited thus far. Traditional decision-making approaches have been fairly successful at addressing relatively straightforward problems in small, replicated systems, such as management of trout in small streams or pulp production in forests. However, this success may be jeopardized as more users place increasing demands on these systems. Adaptive management has received little attention from agencies for addressing problems in small-scale systems, but I suggest that it may be a useful approach for creating a holistic view of common problems and developing guidelines that can then be used in simpler, more traditional approaches to management. Although adaptive management may be more expensive to initiate than traditional approaches, it may be less expensive in the long run if it leads to more effective management. The overall goal of adaptive management is not to maintain an optimal condition of the resource, but to develop an optimal management capacity. This is accomplished by maintaining ecological resilience that allows the system to react to inevitable stresses, and generating flexibility in institutions and stakeholders that allows managers to react when conditions change. The result is that, rather than managing for a single, optimal state, we manage within a range of acceptable outcomes while avoiding catastrophes and irreversible negative effects. Copyright ?? 1999 by The Resilience Alliance.

Conservation Ecology↗
USGS2015

Markov decision processes in natural resources management: observability and uncertainty

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

Ecological Modelling↗
USGS2022

A century of drought in Hawai‘i: Geospatial analysis and synthesis across hydrological, ecological, and socioeconomic scales

Drought is a prominent feature of Hawaiʻi’s climate. However, it has been over 30 years since the last comprehensive meteorological drought analysis, and recent drying trends have emphasized the need to better understand drought dynamics and multi-sector effects in Hawaiʻi. Here, we provide a comprehensive synthesis of past drought effects in Hawaiʻi that we integrate with geospatial analysis of drought characteristics using a newly developed 100-year (1920–2019) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: Meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration and magnitude have increased significantly, consistent with trends found in other Pacific Islands. We found that most droughts were associated with El Niño events, and the two worst droughts of the past century were multi-year events occurring in 1998–2002 and 2007–2014. The former event was most severe on the islands of O’ahu and Kaua’i while the latter event was most severe on Hawaiʻi Island. Within islands, we found different spatial patterns depending on leeward versus windward contrasts. Droughts have resulted in over $80 million in agricultural relief since 1996 and have increased wildfire risk, especially during El Niño years. In addition to providing the historical context needed to better understand future drought projections and to develop effective policies and management strategies to protect natural, cultural, hydrological, and agricultural resources, this work provides a framework for conducting drought analyses in other tropical island systems, especially those with a complex topography and strong climatic gradients.

Hawaii↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2023

2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates

Submerged aquatic vegetation (SAV) provides critical structural habitat for valuable nekton and wildlife species across coastal ecosystems and can buffer the negative effects of land loss. Landscape change and restoration efforts across coastal Louisiana can impact the occurrence, coverage, and species assemblages of SAV, and changes to these foundational species can have cascading impacts across food webs. To support the 2023 Coastal Master Plan efforts, a unique SAV model was developed to assess coverage and occurrence of SAV across aquatic waterbodies in response to environmental variables evaluated. This effort created a spatial model describing the probability of presence of SAV across the study area in response to changing conditions over the modeled time period. To develop the initial coverage data layer, we used remotely sensed Normalized Difference Vegetation Index (NDVI) and modified Normalized Difference Water Index (mNDWI) data from 2015-2018 to identify areas containing variable vegetation and water spectral reflectance. Key environmental variables evaluated included total suspended sediments (TSS), salinity, and physical exposure. Seasonal estimates for TSS and salinity were used, as research indicates that seasonal environmental variability is a significant driver for SAV establishment. Seasonal salinity was derived from Coast-wide Reference Monitoring Station (CRMS) data, and seasonal TSS was estimated from hyperspectral imagery. Estimates of physical exposure have previously been provided by calculating fetch (the distance across water over which waves can propagate), but this proved to be too computationally intensive to be feasible, and we found distance to land to be a reasonable proxy for exposure. To represent geographic conditions and historical factors influences on SAV establishment and occurrence (e.g., variables too numerous and complex to model) we developed a basin variable that served as a proxy for complex historical, or prior, conditions, determined by the forested, fresh, intermediate, brackish, or saline (FFIBS) score. The final model included spring TSS, spring salinity, distance to land, and the basin prior. The model performed well for the area evaluated, correctly classifying SAV (as present or absent) 89% of the time (Kappa = 580). SAV probability of presence responded as expected to change in these environmental variables, with likelihood of occurrence decreasing in response to increasing spring TSS, spring salinity, and distance to land. However, the model was more accurate at predicting absence (true negative = 0.940) than predicting presence (true positive = 0.626), suggesting that the scale of the model may limit the ability to predict presence. Moreover, the simplicity of the model limited the accuracy in highly dynamic environments, for example near the outflow of diversions or areas of significant changes in salinity or TSS. Through incorporating underwater communities like SAV, this master plan provides a holistic view of coastal change and restoration. To create healthy ecological structure and function in wetland habitats, the submergent communities must be considered alongside the emergent habitats. As the benefits of SAV are increasingly recognized, both here in Louisiana and beyond, SAV restoration and the use of SAV communities in assessing and improving ecological condition are becoming more common.

Louisiana↗
USGS2025

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials↗
USGS2023

Changes in abiotic drivers of green sea urchin demographics following the loss of a keystone predator

Sea urchin population demographics can respond to changes in keystone species abundances, with the magnitude of these responses varying depending on environmental influences. In this study, sea urchin populations were surveyed across 15 Aleutian archipelago islands over a 30-year period to understand how patterns of sea urchin demography (density, biomass, and size structure) varied through different ecological regimes that were caused by changes in the abundance of sea otters, a keystone species in this system. To examine long-term changes in sea urchin demographics, four time periods across the recent decline of sea otters were examined: during sea otter presence (1987-1994), nearing absence at the end of the decline (1997-2000), 10 years postdecline (2008-2010), and 15-20 years following the loss of sea otters from the ecosystem (2014-2017). Our results show that when sea otters were broadly present, sea urchin demographics were generally similar across the archipelago, with few urchins that had large-sized bodies. During this time, bottom-up environmental controls were muted relative to top-down forces from keystone predation. However, as sea otters declined and remained absent from the system, abiotic factors became more influential on sea urchin biomass, density, and size structure. In particular, differences among island groups during these periods were correlated with variation in ocean temperature, bathymetric complexity, and habitat availability. Sea urchin recruitment also varied among island groups, corresponding to ecoregions delineated by oceanic passes across the archipelago. The functional extinction of sea otters revealed an increasing influence of abiotic forcing in the absence of top-down control. This study further highlights the importance of understanding how keystone predators regulate herbivore demographics.

Alaska↗
USGS2015

A comparison of hydrologic models for ecological flows and water availability

Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.

Ecohydrology↗
USGS2014

The future of nearshore processes research

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability. Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities. The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies. The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

Report↗
USGS2015

Hydrology: The interdisciplinary science of water

We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth’s hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.

Water Resources Research↗
USGS2012

Status and trends of land change in the Western United States--1973 to 2000

Preface U.S. Geological Survey (USGS) Professional Paper 1794–A is the first in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Western United States between 1973 and 2000. Volumes B, C, and D provide similar analyses for the Great Plains, the Midwest–South Central United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Western United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Western United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov .

Professional Paper↗
USGS2016

Status and trends of land change in the Eastern United States—1973 to 2000

Preface U.S. Geological Survey (USGS) Professional Paper 1794–D is the fourth in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Eastern United States between 1973 and 2000. Volumes A, B, and C provide similar analyses for the Western United States, the Great Plains of the United States, and the Midwest–South Central United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Eastern United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Eastern United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov .

Professional Paper↗
USGS2005

Speciation of mercury and mode of transport from placer gold mine tailings

Historic placer gold mining in the Clear Creek tributary to the Sacramento River (Redding, CA) has highly impacted the hydrology and ecology of an important salmonid spawning stream. Restoration of the watershed utilized dredge tailings contaminated with mercury (Hg) introduced during gold mining, posing the possibility of persistent Hg release to the surrounding environment, including the San Francisco Bay Delta. Column experiments have been performed to evaluate the extent of Hg transport under chemical conditions potentially similar to those in river restoration projects utilizing dredge tailings such as at Clear Creek. Physicochemical perturbations, in the form of shifts in column influent ionic strength and the presence of a low molecular weight organic acid, were applied to coarse and fine sand placer tailings containing 109-194 and 69-90 ng of Hg/g, respectively. Significant concentrations of mercury, up to 16 ??g/L, leach from these sediments in dissolved and particle-associated forms. Sequential chemical extractions (SCE) of these tailings indicate that elemental Hg initially introduced during gold mining has been transformed to readily soluble species, such as mercury oxides and chlorides (3-4%), intermediately extractable phases that likely include (in)organic sorption complexes and amalgams (75-87%), and fractions of highly insoluble forms such as mercury sulfides (6-20%; e.g., cinnabar and metacinnabar). Extended X-ray absorption fine structure (EXAFS) spectroscopic analysis of colloids obtained from column effluent identified cinnabar particles as the dominant mobile mercury-bearing phase. The fraction of intermediately extractable Hg phases also likely includes mobile colloids to which Hg is adsorbed. ?? 2005 American Chemical Society.

Environmental Science & Technology↗
USGS2013

Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship

Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.

Land↗