SEARCH · Search USGS

Results for “Environmental Advances”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27Linked to original sources

USGS2011

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗

USGS2008

Environmental drivers in mangrove establishment and early development: A review

Mangroves have a global distribution within coastal tropical and subtropical climates, and have even expanded to some temperate locales. Where they do occur, mangroves provide a plethora of goods and services, ranging from coastal protection from storms and erosion to direct income for human societies. The mangrove literature has become rather voluminous, prompting many subdisciplines within a field that earlier in the 20th century received little focus. Much of this research has become diffuse by sheer numbers, requiring detailed syntheses to make research results widely available to resource managers. In this review, we take an inclusive approach in focusing on eco-physiological and growth constraints to the establishment and early development of mangrove seedlings in the intertidal zone. This is a critical life stage for mangroves, i.e., the period between dispersal and recruitment to the sapling stage. We begin with some of the research that has set the precedent for seedling-level eco-physiological research in mangroves, and then we focus on recent advances (circa. 1995 to present) in our understanding of temperature, carbon dioxide, salinity, light, nutrient, flooding, and specific biotic influences on seedling survival and growth. As such, we take a new approach in describing seedling response to global factors (e.g., temperature) along with site-specific factors (e.g., salinity). All variables will strongly influence the future of seedling dynamics in ways perhaps not yet documented in mature forests. Furthermore, understanding how different mangrove species can respond to global factors and regional influences is useful for diagnosing observed mortality within mangrove wetlands, managed or natural. This review provides an updated eco-physiological knowledge base for future research and reforestation activity, and for understanding important links among climate change, local physico-chemical condition, and establishment and early growth of mangrove seedlings.

Aquatic Botany↗

USGS2002

Issues in characterizing phenology from satellite observations

Over the past decade, many investigators have published techniques for deriving phenological parameters, especially the start of the growing season (SOS), from time-series satellite imagery. The principal satellite sensor for these studies is the advanced very high resolution radiometer (AVHRR). This study investigates the characteristics of four of the primary methods for identifying SOS; maximum curvature, delayed moving average, time of greatest NDVI increase and time of half-maximum NDVI. Comparisons between the methods illustrate biases for earlier or later SOS in the various methods and a relatively low statistical relationship among all four methods (r 2 =.10 to .35). Our analysis indicates that each of the methods is detecting fundamentally different stages of the start of season. These stages include snow melt, initial growth of herbaceous plants and understory, and first leaf; each of which is important in determining differences in land/atmosphere interactions. Users of these types of datasets need to be aware of the different environmental conditions being measured by the various approaches and use careful judgment in selecting the proper method.

Conference Paper↗

USGS2018

Phenological mismatch in coastal western Alaska may increase summer season greenhouse gas uptake

High latitude ecosystems are prone to phenological mismatches due to climate change- driven advances in the growing season and changing arrival times of migratory herbivores. These changes have the potential to alter biogeochemical cycling and contribute to feedbacks on climate change by altering greenhouse gas (GHG) emissions of carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) through large regions of the Arctic. Yet the effects of phenological mismatches on gas fluxes are currently unexplored. We used a three-year field experiment that altered the start of the growing season and timing of grazing to investigate how phenological mismatch affects GHG exchange. We found early grazing increased mean GHG emission to the atmosphere despite lower CH 4 emissions due to grazing-induced changes in vegetation structure that increased uptake of CO 2 . In contrast, late grazing reduced GHG emissions because greater plant productivity led to an increase in CO 2 uptake that overcame the increase in CH 4 emission. Timing of grazing was an important control on both CO 2 and CH 4 emissions, and net GHG exchange was the result of opposing fluxes of CO 2 and CH 4 . N 2 O played a negligible role in GHG flux. Advancing the growing season had a smaller effect on GHG emissions than changes to timing of grazing in this study. Our results suggest that a phenological mismatch that delays timing of grazing relative to the growing season, a change which is already developing along in western coastal Alaska, will reduce GHG emissions to the atmosphere through increased CO 2 uptake despite greater CH 4 emissions.

Environmental Research Letters↗

USGS2018

Water-quality conditions with an emphasis on cyanobacteria and associated toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through September 2016

Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds that may cause substantial economic and public health concerns, and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply. Extensive cyanobacterial blooms typically do not develop in the Kansas River; however, reservoirs in the lower Kansas River Basin occasionally develop blooms that may affect downstream water quality. During July 2012 through September 2016, continuous and (or) discrete water-quality data were collected at several sites (Wamego, De Soto, and three main reservoir-fed tributaries) on the Kansas River to characterize the sources, frequency and magnitude of occurrence, and causes of cyanobacteria, cyanobacterial toxins, and taste-and-odor compounds and to develop a real-time notification system of changing water-quality conditions that may affect drinking-water treatment. Algal biomass, as estimated by chlorophyll, was consistently higher at the downstream De Soto site than the upstream Wamego site. Higher algal biomass at the De Soto site likely was caused by algal growth during downstream transport without major losses due to grazing by aquatic organisms or other processes. Algal biomass at the Wamego and De Soto sites was negatively correlated with streamflow and total and bioavailable nutrient concentrations. The negative association between algal biomass and nutrients in the Kansas River likely reflects the relatively strong positive association between nutrient concentrations and streamflows. Cyanobacteria were relatively common in the Kansas River but rarely dominated the algal community. Like overall algal biomass, cyanobacterial abundances typically were higher at the De Soto site than the Wamego site. Cyanobacterial abundances generally peaked in late summer or early fall (July through October), with smaller peaks occasionally observed in spring (April through May). Cyanobacteria in the Kansas River rarely exceeded 20,000 cells per milliliter, the abundance at which cyanobacteria may become a concern for drinking-water treatment. Relations between cyanobacterial abundance and streamflow, turbidity, and nutrients in the Kansas River were similar to those between chlorophyll and total phytoplankton abundance, indicating the same processes that influence overall algal biomass and dynamics also are influencing cyanobacteria. The cyanotoxin microcystin was detected in about 27 percent of the samples collected from Kansas River tributary and main-stem sites. Cylindrospermopsin was detected in one sample from the De Soto site. Microcystin occurrence and concentration were similar between the Wamego and De Soto sites. Concentrations exceeded the U.S. Environmental Protection Agency health advisory guidance values for finished drinking water of 0.3 (for bottle-fed infants and pre-school children) and 1.6 micrograms per liter (μg/L; for school-age children and adults) in 6 percent or less of samples collected. These guidance values are for finished drinking water and are not directly applicable to observed environmental concentrations but do provide a benchmark for comparison. Microcystin was detected most often and had the highest concentrations during summer. Though seasonal patterns in microcystin occurrence were generally consistent, seasonal maxima varied by an order of magnitude across years. The taste-and-odor compounds geosmin and 2-methylisoborneol (MIB) were detected in about 78 and 43 percent of samples, respectively, collected across all sites (main stem and tributaries). Geosmin and MIB occurrence and concentration varied considerably between the Wamego and De Soto sites. Geosmin was detected in about 67 percent of Wamego samples and 81 percent of De Soto samples. The human detection threshold of 5 nanograms per liter (ng/L) was exceeded for geosmin in about 11 and 17 percent of the samples collected at the Wamego and De Soto sites, respectively. Geosmin was detected during all months of the year at both sites, and there were no clear seasonal patterns. MIB was detected less frequently in the Kansas River than geosmin and was observed in about 42 percent of Wamego samples and 33 percent of De Soto samples. Concentrations exceeded 5 ng/L in about 7 and 5 percent of samples from the Wamego and De Soto sites, respectively. As observed for geosmin, there were no clear seasonal patterns in MIB occurrence or concentration. There seems to be a connection between microcystin detections in the Kansas River and occurrence of microcystin in upstream reservoirs (and tributary streams). Microcystin concentrations greater than 0.3 μg/L may be likely during the summer when streamflow is less than 3,000 cubic feet per second (ft 3 /s) and contributions from Milford Lake exceed about 30 percent of total flow in the Kansas River. Observed microcystin concentrations typically were higher at the De Soto site than the Wamego or tributary sites during 2012 through 2016, indicating cyanobacteria may continue to grow and produce microcystin once introduced to the Kansas River. The spatial and temporal patterns in geosmin and MIB occurrence and concentration were more complex than microcystin. There were no clear connections between geosmin and MIB occurrence in the Kansas River and potential upstream reservoir (or tributary stream) sources. Likewise, there was not a clear relation between algal biomass, cyanobacteria, or actinomycetes bacteria and taste-and-odor events in the Kansas River. Geosmin and MIB were not strongly correlated with any measured environmental variable at either Kansas River site. Continuous water-quality data may be used independently or in combination with regression models to provide information on changing water-quality conditions that may affect drinking-water treatment processes or recreational activities on the Kansas River. For example, logistic regression model outputs and continuous water-quality data may both be indicative of the potential for microcystin events. Logistic regression models that are estimating a high probability of microcystin occurrence at concentrations above 0.1 μg/L can be used as one indicator. Streamflows less than 3,000 ft 3 /s during upstream reservoir releases during periods with low turbidity and increased chlorophyll fluorescence, specific conductance, and pH values may also be indicative of microcystin events. Advanced or near-real-time notification may inform proactive, rather than reactive, management strategies when water-quality conditions are changing rapidly or are likely to cause cyanobacteria-related events.

Kansas↗

USGS2023

A hierarchical modelling framework for estimating individual- and population-level reproductive success from movement data

Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free-living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life-history activities, such as reproduction. For many species that are secretive or occupy remote areas, these life-history events are difficult to detect with conventional survey techniques, and consequently, vital rates are difficult to estimate. We present a hierarchical modelling framework, which integrates movement data observed via animal-borne telemetry and optional, infrequent survey data, to estimate individual- and population-level reproductive success. The approach combines a mechanistic movement model and survival model, and allows for assessing the effects of hypothesized individual and environmental covariates on reproductive success. We first tested our approach with simulated data, and then applied it to movement data from migratory golden eagles ( Aquila chrysaetos) breeding in southcentral Alaska across four breeding seasons. We show that results supported our biological hypotheses that changes in movement coincided with the timing of reproductive failures, and that changes in movement could be used to assess breeding success (and failure) at the individual and population levels. The analysis also provided evidence of inter-annual variation in population-level nest success and the timing of nesting failures. This new approach is adaptable to many species that care for young and can be tracked with telemetry devices, and can provide not only individual-level information useful for testing ecological hypotheses, but estimates of demographic parameters that can directly inform conservation and management if tagged animals are representative of the population.

Methods in Ecology and Evolution↗

USGS2021

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.

Wyoming↗

USGS2024

Observing systems, modeling, and forecasting

Predicting harmful algal blooms (HABs) requires integrating physical, chemical, and biological data collected from observing networks and then assimilating these data into models, which are used to generate forecasts. In 2005, the Harmful Algal Research and Response: A National Environmental Science Strategy 2005-2015 (HARRNESS, 2005) made recommendations on how to improve HAB modeling and forecasting over the next decade. Key HARRNESS recommendations related to sensing, networking, and modeling HABs included: ● Support the development and validation of new and improved technologies for remote cell and toxin detection, and for modeling and forecasting, ● Improve coordination of monitoring/ and modeling efforts, both at national and regional levels, ● Improve the use of networking technologies for monitoring and modeling efforts, ● Conduct sustained time series measurements of the biotic, chemical, and physical environments impacted by HABs, ● Develop food web models on the ecosystem fate and effects of toxins, ● Develop and improve species-specific models that link to physical-biological models. Here we review HAB observing, modeling, and forecasting advances and technologies and recommend research and management priorities for the next decade and beyond. Our report encompasses sensing technologies, sensor networking and data management, models and forecasts, and the paths to operationalize forecasts. Continued improvements of deployable sensors are foundational to improving early warning indicators, models, and forecasts, which are only as good as the underlying data. Sensing technology has advanced considerably in the last decade; for example, more capable fluorometric pigment sensors can track changes in bloom biomass in real-time. Additionally, automated imaging/classifying systems to identify and quantify key harmful algal (HA) taxa are being routinely deployed. However, deployable toxin sensors are available for only some HAB toxins and continue to be identified as a critical need by researchers and managers. As more and improved sensors and technologies become available, the data quality associated with each sensor needs to be assessed. Data quality encompasses the reliability, accuracy, and uncertainty associated with sensor-generated data. These data need to be of known quality so that researchers, managers, and end-users can reliably determine if the information is appropriate for their intended applications. Many of the data quality recommendations from HARRNESS (2005) are still relevant and have been reiterated within the management community. Understanding and documenting data quality, and when applicable, standardizing best practices for sensor use, continue to be recommended.

Report↗

USGS2018

Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes

Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.

Arkansas, Missouri, Oklahoma↗

USGS2021

Lake Ontario cisco population dynamics based on long-term surveys

Prior to European settlement, cisco (Coregonus artedi) were likely one of Lake Ontario’s most abundant fishes but currently represent a small portion of the fish community. To understand how the population has changed over the past 70 years we compared trends in annual catch rates from gillnet and bottom trawl surveys and commercial fishery landings. In surveys, cisco were generally rare, and represented 0.2, 0.4, and 0.001% of all fish caught in two gillnet surveys and bottom trawl surveys. Cisco catch rates in gillnets and trawls were positively correlated and correlations increased when gillnet catches two years later were compared to trawls since trawls tended to capture smaller, juvenile-sized cisco relative to gillnets. Survey catch rates suggest recruitment is generally low, but discrete periods of relatively greater recruitment in the 1980s and mid-2010s suggest reproductive conditions for cisco vary temporally. Trawl surveys were the most spatially extensive survey and illustrated catch rates were highest in northeastern Lake Ontario. Greater cisco abundance in this region may be related to more-abundant embayment spawning habitat, greater distance from winter aggregations of nonnative planktivores, or more appropriate environmental conditions during spawing. At the basin scale, Lake Ontario bottom trawl catch per unit effort (CPUE) was positively correlated to Lake Superior trawl CPUE suggesting a regional driver, such as climate, may be similarly impacting both populations. Concurrent patterns across Lake Ontario surveys support the idea that cisco are currently a small portion of the fish community, recruitment remains inconsistent, and habitats in northeastern Lake Ontario appear critical to the remnant populations.

Lake Ontario↗

USGS2026

Optimizing cryo-focused pyrolysis GC/MS for tracing soil organic matter across diverse ecosystems

The cycling of organic matter in terrestrial soils and sediments is central to a range of biogeochemical processes that regulate nutrient cycling, crop productivity, trace gas emissions, and contaminant transport. Pyrolysis-gas chromatography/mass spectrometry (py-GC/MS) is a powerful tool for characterizing bulk soil organic matter (SOM) at the molecular level. In this study, we used a cryo-focused py-GC/MS system to analyze soil samples from seven diverse ecosystems: vernal pool, prairie pothole, temperate forest, tropical forest, tundra, wildfire-affected boreal forest, and grassland. We addressed a key bottleneck in molecular-level SOM characterization by developing an automated data analysis pipeline to optimize py-GC/MS and complementary evolved gas analysis/mass spectrometry (EGA/MS) methods, incorporating advanced tools for data deconvolution, developing a custom compound class library, and implementing fragmentation spectrum-based molecular networking for the first time. This improved workflow was applied to soil samples from all seven ecosystems, including multiple depths and density fractions. Our findings demonstrate that ecosystem type plays a dominant role in shaping compositional differences in SOM. We also identified trends in the source of SOM compounds (e.g., microbial vs. plant-derived) across soil depth and density fractions, which are critical for understanding persistence and turnover of SOM. Our molecular networking analysis indicated that although many compounds are widespread across ecosystems, others are restricted to specific environments, such as wetlands. This underscores the utility of molecular-level data in elucidating the complexity of SOM composition and the environmental drivers that shape it. Such molecular-level insights can deepen our knowledge of biogeochemical SOM cycles.

Environmental Science and Technology↗

USGS2002

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson

The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat . By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data , effective models of habitat preference were created. Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition. Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data . Such relationships, once verified and established, can be used to help indirectly monitor the population. Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat . Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations. The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.

Arizona↗

USGS2017

Widespread legacy brine contamination from oil production reduces survival of chorus frog larvae

Advances in drilling techniques have facilitated a rapid increase in hydrocarbon extraction from energy shales, including the Williston Basin in central North America. This area overlaps with the Prairie Pothole Region, a region densely populated with wetlands that provide numerous ecosystem services. Historical (legacy) disposal practices often released saline co-produced waters (brines) with high chloride concentrations, affecting wetland water quality directly or persisting in sediments. Despite the potential threat of brine contamination to aquatic habitats, there has been little research into its ecological effects. We capitalized on a gradient of legacy brine-contaminated wetlands in northeast Montana to conduct laboratory experiments to assess variation in survival of larval Boreal Chorus Frogs ( Pseudacris maculata ) reared on sediments from 3 local wetlands and a control source. To help provide environmental context for the experiment, we also measured chloride concentrations in 6 brine-contaminated wetlands in our study area, including the 2 contaminated sites used for sediment exposures. Survival of frog larvae during 46- and 55-day experiments differed by up to 88% among sediment sources (Site Model) and was negatively correlated with potential chloride exposure (Chloride Model). Five of the 6 contaminated wetlands exceeded the U.S. EPA acute benchmark for chloride in freshwater (860 mg/L) and all exceeded the chronic benchmark (230 mg/L). However, the Wetland Site model explained more variation in survival than the Chloride Model, suggesting that chloride concentration alone does not fully reflect the threat of contamination to aquatic species. Because the profiles of brine-contaminated sediments are complex, further surveys and experiments are needed across a broad range of conditions, especially where restoration or remediation actions have reduced brine-contamination. Information provided by this study can help quantify potential ecological threats and help land managers prioritize conservation strategies as part of responsible and sustainable energy development.

Montana, North Dakota, South Dakota↗

USGS2017

Signals of impending change

Society has an increasing awareness that there are finite limits to what we can expect the planet to absorb and still provide goods and services at current rates 1 . Both historical reconstructions and contemporary events continue to remind us that ecological regime changes are often abrupt rather than gradual. This reality motivates researchers who seek to discover leading indicators for impending ecosystem change. Berdugo et al . 2 report an important advance in our ability to anticipate the conversion of arid lands from self-organized, self-maintaining and productive ecosystems, to a state characterized by disorganization and low functionality. Such conversions have important implications for our understanding of ‘desertification’ — which is a shift from arid to desert-like conditions. Theoretical studies have suggested that patterns in the patchiness of vegetation might indicate how close a system is to making an abrupt change to desert-like conditions 3 , 4 , 5 . Empirical studies, however, have tended to show instead that simply the total cover of vegetation, rather than its arrangement, often foretells the state of the system 4 , 5 , 6 , 7 , 8 , 9 . Berdugo et al . 2 combine these competing ideas into one integrated perspective. They show how major environmental drivers, such as aridity, influence both vegetation cover and patchiness, as well as where self-organizing, stabilizing forces in the vegetation are likely to be found.

Nature Ecology & Evolution↗

USGS2017

Challenges in recovering resources from acid mine drainage

Metal recovery from mine waters and effluents is not a new approach but one that has occurred largely opportunistically over the last four millennia. Due to the need for low-cost resources and increasingly stringent environmental conditions, mine waters are being considered in a fresh light with a designed, deliberate approach to resource recovery often as part of a larger water treatment evaluation. Mine water chemistry is highly dependent on many factors including geology, ore deposit composition and mineralogy, mining methods, climate, site hydrology, and others. Mine waters are typically Ca-Mg-SO4±Al±Fe with a broad range in pH and metal content. The main issue in recovering components of these waters having potential economic value, such as base metals or rare earth elements, is the separation of these from more reactive metals such as Fe and Al. Broad categories of methods for separating and extracting substances from acidic mine drainage are chemical and biological. Chemical methods include solution, physicochemical, and electrochemical technologies. Advances in membrane techniques such as reverse osmosis have been substantial and the technique is both physical and chemical. Biological methods may be further divided into microbiological and macrobiological, but only the former is considered here as a recovery method, as the latter is typically used as a passive form of water treatment.

Conference Paper↗

USGS1999

Anomalous increases in piezometric levels in advance of longwall mining subsidence

The typical initial piezometric response to longwall undermining is a decline in head due to the opening of fractures and bedding planes during early subsidence. However, in studies over two active longwall mines in southern Illinois, temporary rises in head just before subsidence were observed in piezometers constructed in low-permeability units. Although the initial phase of subsidence is considered dilational, these head increases indicate compressional effects that raise pore-water pressures. Possible mechanisms are shear stresses at the leading edge of subsidence or transmission of stress related to dewatering of underlying permeable units.

Environmental & Engineering Geoscience↗

USGS2018

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Proceedings of the National Academy of Sciences of↗

USGS2014

Hydraulic modeling development and application in water resources engineering

The use of modeling has become widespread in water resources engineering and science to study rivers, lakes, estuaries, and coastal regions. For example, computer models are commonly used to forecast anthropogenic effects on the environment, and to help provide advanced mitigation measures against catastrophic events such as natural and dam-break floods. Linking hydraulic models to vegetation and habitat models has expanded their use in multidisciplinary applications to the riparian corridor. Implementation of these models in software packages on personal desktop computers has made them accessible to the general engineering community, and their use has been popularized by the need of minimal training due to intuitive graphical user interface front ends. Models are, however, complex and nontrivial, to the extent that even common terminology is sometimes ambiguous and often applied incorrectly. In fact, many efforts are currently under way in order to standardize terminology and offer guidelines for good practice, but none has yet reached unanimous acceptance. This chapter provides a view of the elements involved in modeling surface flows for the application in environmental water resources engineering. It presents the concepts and steps necessary for rational model development and use by starting with the exploration of the ideas involved in defining a model. Tangible form of those ideas is provided by the development of a mathematical and corresponding numerical hydraulic model, which is given with a substantial amount of detail. The issues of model deployment in a practical and productive work environment are also addressed. The chapter ends by presenting a few model applications highlighting the need for good quality control in model validation.

Book chapter↗