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At least 91 records · Page 5Linked to original sources
USGS2022

Balancing model generality and specificity in management-focused habitat selection models for Gunnison sage-grouse

Identifying, protecting, and restoring habitats for declining wildlife populations is foundational to conservation and recovery planning for any species at risk of decline. Resource selection analysis is a key tool to assess habitat and prescribe management actions. Yet, it can be challenging to map suitable resource conditions across a wide range of ecological contexts and use the resulting models to identify effective and universal habitat improvement actions. We developed a management-centric modeling approach that sought to balance the need to evaluate the consistency of key habitat conditions and improvement actions across multiple, distinct populations, while allowing context-specific environmental variables and spatial scales to nuance selection responses that form the basis of location-specific management prescriptions. To demonstrate this approach, we developed a set of habitat selection models for Gunnison sage-grouse ( Centrocercus minimus ), a threatened species under the U.S. Endangered Species Act. Conservation, species recovery, and habitat management efforts are needed in six isolated satellite populations (San Miguel, Crawford, Piñon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass) where environmental conditions differ, and the already small number of birds are declining. We used multi-scale and seasonal resource selection analyses to quantify relationships between environmental conditions and sites used by animals. All models included key habitat variables often altered through management actions to assess their differential influences across models. We found important similarities and differences among satellites, indicating that, although some rules of thumb are generally well-grounded, the consideration of population-specific environmental differences could increase the efficiency of local habitat improvement actions. Sage-grouse also had diverse responses to resource conditions at different scales, indicating that regional spatial (e.g., landscape) and local patch scale can differentially influence expected habitat improvements associated with where such management actions are implemented. Although context variables such as topography cannot be manipulated, sage-grouse associations revealed information that could guide the siting of improvement actions. This approach to balancing management objectives associated with habitat assessment may benefit spatially-structured populations with different environmental contexts and species with complex habitat needs and associations.

Colorado↗
USGS2017

Continued geophysical logging near the GMH Electronics National Priorities List Superfund site near Roxboro, North Carolina

The U.S. Geological Survey South Atlantic Water Science Center collected borehole geophysical logs and images and continuous water-level data near the GMH Electronics National Priorities List Superfund site near Roxboro, North Carolina, during December 2012 through July 2015. Previous work by the U.S. Geological Survey South Atlantic Water Science Center at the site involved the collection of borehole geophysical log data in 15 wells, in addition to surface geologic mapping and passive diffusion bag sampling. In a continued effort to assist the U.S. Environmental Protection Agency in developing a conceptual groundwater model to assess current contaminant distribution and future migration of contaminants, more than 900 subsurface features (primarily fracture orientations) in 10 open borehole wells were delineated and continuous water-level data information from 14 monitoring wells within close proximity of the initially drilled boreholes was collected to observe any induced water-level fluctuations during drilling operations

North Carolina↗
USGS1996

Developing a temporal database of urban development for the Baltimore/Washington region

The U.S. Geological Survey (USGS), the University of Maryland Baltimore County (UMBC), and the U.S. Bureau of the Census are working together as a multiagency, multidisciplinary team in developing a temporal database that documents the growth of the Baltimore-Washington metropolitan region. This database consists of urban development, principal transportation, shoreline, and population density change. The urban development theme, considered a primary data layer in the study of urban land transformation resulting from human impact on the land, is the focus of this paper. The Baltimore-Washington Spatial Dynamics and Human Impacts Study builds on earlier research efforts that mapped urban land use change for the San Francisco Bay area (Acevedo and Bell, 1994; Bell and others, 1995; Kirtland and others, 1994). In developing a temporal database (Acevedo and others, in press), the team participants hope to provide data that can be used to study patterns of urban growth; assess ecological, environmental, and climatic impacts of urban change; and model and predict future urbanization patterns and impacts (Clarke and others, 1996). Both the San Francisco and Baltimore-Washington regions were selected because of the rapid urban growth and resulting impacts on their ecosystems. The Chesapeake Bay region in particular has undergone extensive environmental agitation due to the hydrologic problems that have arisen from the increase in impermeable surfaces and structures, that is buildings and pavement that physically cover the soil. Because of the inability of water to percolate into the ground, little purification occurs by filtration. Water runs over paved surfaces and quickly washes high levels of toxins directly into the water system. Toxins like gasoline, oil, and fertilizer have dramatically affected the local streams, rivers, and the bay. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. This paper describes the techniques used to map the extent of urban areas for Phase I and does not discuss Phase II in detail because the work is still in progress. In this study, urban development is defined as areas of intensive use, with much of the land covered by structures. The built-up areas are characterized by the existence of a systematic street pattern, and the relative concentration of buildings and associated intensive use areas, such as parking lots. Using this definition, urban development does not refer to political boundaries and may include incorporated or unincorporated areas as well as military reservations. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. To build the urban component of the temporal database, a multidisciplinary team was assembled and a phased approach initiated. Expanding on procedures developed for the San Francisco Regional Study (Bell and others, 1995), the team developed data definitions, a classification scheme, compilation criteria, mapping specifications, guidelines for source materials, and metadata specifications to support development of a logically consistent dataset. Extensive documentation procedures were established to ensure consistency in data collection, and for subsequent application to other regions. Phase II was the implementation of the regional mapping effort. ABSTRACT The U.S. Geological Survey, the University of Maryland Baltimore County, and the U.S. Bureau of the Census are developing a temporal database to study urban development in the Baltimore-Washington region. The primary data layer, the extent of urban or built-up areas, was compiled using a geographic information system and historical maps, remotely sensed data, digital land use data, and census information from a variety of sources. Urban land use change has been documented by the Baltimore-Washington Spatial Dynamics & Human Impact Study Team for the last 200 years. The methods, definitions, and collection criteria used to define urban or built-up areas were developed by a multi-disciplinary team that also ensures consistency in collection techniques and documentation methods for subsequent application in other regions. Animation techniques were used to visualize the database and to document the evolution of the region's urban landscape. The database is an important tool to urban and regional planners, ecologists, and global change researchers for measuring trends in urban sprawl, analyzing patterns of water pollution, understanding the impacts of development on ecosystems, and developing predictive modeling techniques to better forecast areas of urban growth. The study area for Phase I consisted of an approximate area of 15- by 15-minute segment centered around the city of Baltimore (fig. 1). Phase I was used as a prototype for the technique development and integration that the multiagency collaborative effort would require. The regional study, Phase II, encompassed a 2-degree square centered on Washington, D.C. With more than 7 million people spread across 39 counties, the Baltimore-Washington region is one the Nation's fastest growing metropolitan areas. The two cities are rapidly merging into one.

Maryland↗
USGS2016

Integrated modeling approach for fate and transport of submerged oil and oil-particle aggregates in a freshwater riverine environment

The Enbridge Line 6B pipeline release of diluted bitumen into the Kalamazoo River downstream of Marshall, Michigan, U.S.A., in July 2010 was one of the largest oil spills into freshwater in North American history. A portion of the oil interacted with river sediment and submerged requiring the development and implementation of new approaches for detection and recovery of oil mixed with river sediment. Hydrodynamic and sediment transport modeling became an integral part of containment and recovery operations for decision support about the potential fate and migration of submerged oil and oiled sediment. Three models were developed for the U.S. Environmental Protection Agency to cover a range of spatial scales of interest to onsite operations. Two-dimensional (2D) hydrodynamic and sediment transport models from the Environmental Fluid Dynamics Code and the sediment bed model SEDZLJ1 were used to simulate potential resuspension, migration, and deposition of submerged oil and oiled sediment along a 38-mile reach of the Kalamazoo River affected by the oil from Marshall to Kalamazoo. An algorithm was added to SEDZLJ to represent three additional particle size classes of oilparticle aggregates (OPAs) with a range of sizes, specific gravities, and settling velocities. Field and laboratory experiments and flume tests were done to support the numerical modeling of OPAs. A three-dimensional hydrodynamic model was developed to simulate hydrodynamics and OPA tracking through Morrow Lake, the most downstream impoundment. This model incorporated wind and dam operations into high and low flow, lake drawdown, and containment simulations. Finally, a 2D unstructured grid model, HydroSed2D, was used to simulate flows and sediment transport along 1- to 2-mile segments of the Kalamazoo River around islands and through side channels and backwater areas that are particularly prone to submerged oil deposition. Integrated models could be developed quickly due to the availability of information and services combined with spill response operations that included: bathymetry and topography data, fieldbased geomorphic mapping of submerged oil, and discharge measured at U.S. Geological Survey streamflow gauges. Modeling results were included in a multiple-lines-of-evidence approach that was used by the Federal On-Scene Coordinator and operations staff for decision-making related to assessment and recovery of submerged oil, as well as net environmental benefit analysis. Similar modeling approaches will likely be useful for future oil spills in riverine environments.

Michigan↗
USGS2012

A climate for speciation: rapid spatial diversification within the Sorex cinereus complex of shrews

The cyclic climate regime of the late Quaternary caused dramatic environmental change at high latitudes. Although these events may have been brief in periodicity from an evolutionary standpoint, multiple episodes of allopatry and divergence have been implicated in rapid radiations of a number of organisms. Shrews of the Sorex cinereus complex have long challenged taxonomists due to similar morphology and parapatric geographic ranges. Here, multi-locus phylogenetic and demographic assessments using a coalescent framework were combined to investigate spatiotemporal evolution of 13 nominal species with a widespread distribution throughout North America and across Beringia into Siberia. For these species, we first test a hypothesis of recent differentiation in response to Pleistocene climate versus more ancient divergence that would coincide with pre-Pleistocene perturbations. We then investigate the processes driving diversification over multiple continents. Our genetic analyses highlight novel diversity within these morphologically conserved mammals and clarify relationships between geographic distribution and evolutionary history. Demography within and among species indicates both regional stability and rapid expansion. Ancestral ecological differentiation coincident with early cladogenesis within the complex enabled alternating and repeated episodes of allopatry and expansion where successive glacial and interglacial phases each promoted divergence. The Sorex cinereus complex constitutes a valuable model for future comparative assessments of evolution in response to cyclic environmental change.

Molecular Phylogenetics and Evolution↗
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↗
USGS2011

Carbonatite and alkaline intrusion-related rare earth element deposits–A deposit model

The rare earth elements are not as rare in nature as their name implies, but economic deposits with these elements are not common and few deposits have been large producers. In the past 25 years, demand for rare earth elements has increased dramatically because of their wide and diverse use in high-technology applications. Yet, presently the global production and supply of rare earth elements come from only a few sources. China produces more than 95 percent of the world's supply of rare earth elements. Because of China's decision to restrict exports of these elements, the price of rare earth elements has increased and industrial countries are concerned about supply shortages. As a result, understanding the distribution and origin of rare earth elements deposits, and identifying and quantifying our nation's rare earth elements resources have become priorities. Carbonatite and alkaline intrusive complexes, as well as their weathering products, are the primary sources of rare earth elements. The general mineral deposit model summarized here is part of an effort by the U.S. Geological Survey's Mineral Resources Program to update existing models and develop new descriptive mineral deposit models to supplement previously published models for use in mineral-resource and mineral-environmental assessments. Carbonatite and alkaline intrusion-related REE deposits are discussed together because of their spatial association, common enrichment in incompatible elements, and similarities in genesis. A wide variety of commodities have been exploited from carbonatites and alkaline igneous rocks, such as rare earth elements, niobium, phosphate, titanium, vermiculite, barite, fluorite, copper, calcite, and zirconium. Other enrichments include manganese, strontium, tantalum, thorium, vanadium, and uranium.

Open-File Report↗
USGS2012

Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States

Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion.

Aquatic Invasions↗
USGS1989

Interaction assessment: Rationale and a test using plants

A non-manipulative method for deriving empirical expressions of population growth parameters from simple field data is presented. The derived expressions can be used to assess the intensity and form of density dependence and interspecies interactions, and have potential for parameterizing more mechanistic models of population dynamics and for use in applied ecology, e.g. land management or environmental risk assessment. The method is based on an assertion of invariant expected fitness across occupied microhabitats. Hence, its success depends upon the degree to which that assertion holds. The assertion, as used here, is broadly applicable. Thus, the method can be expected to yield reliable results even in nonequilibrium communities. Here, we apply the method to data on six desert plant species. Expressions generated from data in one stand, in one year, successfully predict plant cover values in other stands and years. The predicted patterns of plant species interactions are discussed in the light of current knowledge and theorics of desert succession.

Evolutionary Ecology↗
USGS2023

Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20

Loss and degradation of sagebrush ( Artemisia spp.) rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western U.S. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (hereinafter, “Needs”) for informing the actions proposed under the five topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse ( Centrocercus urophasianus ), Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed four Needs identified under the Climate and Weather topic in the Plan. The topic outlined research Needs broadly focused on understanding the potential effects of climate change on vegetative resilience to inform restoration of sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (hereinafter, “Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 92 science products that at least partially addressed a Need identified in the Climate and Weather topic. The Needs that were well and partially addressed included: studies of the complex set of climatic relationships that influence sagebrush rangeland restoration and seeding success; the identification of seed collection areas across the range of environmental variability inhabited by target restoration species; and develop predictive models to assess targeted restoration species’ responses to mid-century climatic conditions. The Need addressed poorly was the identification of native plant species, genotypes and ecotypes, and seed mixes that may be resilient to a changing climate. The information provided in this assessment will assist updating the Plan, and can inform updates of other relevant science planning documents as needed.

Open-File Report↗
USGS2021

How do lizard niches conserve, diverge or converge? Further exploration of saurian evolutionary ecology

Environmental conditions on Earth are repeated in non-random patterns that often coincide with species from different regions and time periods having consistent combinations of morphological, physiological and behavioral traits. Observation of repeated trait combinations among species confronting similar environmental conditions suggest that adaptive trait combinations are constrained by functional tradeoffs within or across niche dimensions. In an earlier study, we assembled a high-resolution database of functional traits for 134 lizard species to explore ecological diversification in relation to five fundamental niche dimensions. Here we expand and further examine multivariate relationships in that dataset to assess the relative influence of niche dimensions on the distribution of species in 6-dimensional niche space and how these may deviate from distributions generated from null models. We then analyzed a dataset with lower functional-trait resolution for 1023 lizard species that was compiled from our dataset and a published database, representing most of the extant families and environmental conditions occupied by lizards globally. Ordinations from multivariate analysis were compared with null models to assess how ecological and historical factors have resulted in the conservation, divergence or convergence of lizard niches.

BMC Ecology and Evolution↗
USGS2007

Proceedings for a workshop on deposit modeling, mineral resource assessment, and their role in sustainable development

The world's use of nonfuel mineral resources continues to increase to support a growing population and increasing standards of living. The ability to meet this increasing demand is affected especially by concerns about possible environmental degradation associated with minerals production and by competing land uses. What information does the world need to support global minerals development in a sustainable way? Informed planning and decisions concerning sustainability and future mineral resource supply require a long–term perspective and an integrated approach to resource, land use, economic, and environmental management worldwide. Such perspective and approach require unbiased information on the global distribution of identified and especially undiscovered resources, the economic and political factors influencing their development, and the potential environmental consequences of their exploitation. The U.S. Geological Survey and the former Deposit Modeling Program of the International Union of Geological Sciences (IUGS) of the United Nations Educational, Scientific and Cultural Organization (UNESCO) sponsored a workshop on "Deposit Modeling, Mineral Resource Assessment, and Their Role in Sustainable Development" at the 31st International Geological Congress (IGC) in Rio de Janeiro, Brazil, on August 18–19, 2000. The purpose of the workshop was to review the state-of-the-art in mineral deposit modeling and resource assessment and to examine the role of global assessments of nonfuel mineral resources in sustainable development. The workshop addressed questions such as the following: Which of the available mineral deposit models and assessment methods are best suited for predicting the locations, deposit types, and amounts of undiscovered nonfuel mineral resources remaining in the world? What is the availability of global geologic, mineral deposit, and mineral exploration information? How can mineral resource assessments be used to address economic and environmental issues? Presentations included overviews of assessment methods applied in previous national and other small-scale assessments of large regions and of the resulting assessment products and their uses. Twenty-seven people from Canada, China, Finland, Germany, Japan, Peru, Slovenia, South Africa, United States, and Venezuela participated in the 2-day post-Congress workshop. The attendees represented academia, government, environmental organizations, and the mining industry.

Circular↗
USGS2008

Simulation of Hydrodynamics and Water Quality in Pueblo Reservoir, Southeastern Colorado, for 1985 through 1987 and 1999 through 2002

Pueblo Reservoir is west of Pueblo, Colorado, and is an important water resource for southeastern Colorado. The reservoir provides irrigation, municipal, and industrial water to various entities throughout the region. In anticipation of increased population growth, the cities of Colorado Springs, Fountain, Security, and Pueblo West have proposed building a pipeline that would be capable of conveying 78 million gallons of raw water per day (240 acre-feet) from Pueblo Reservoir. The U.S. Geological Survey, in cooperation with Colorado Springs Utilities and the Bureau of Reclamation, developed, calibrated, and verified a hydrodynamic and water-quality model of Pueblo Reservoir to describe the hydrologic, chemical, and biological processes in Pueblo Reservoir that can be used to assess environmental effects in the reservoir. Hydrodynamics and water-quality characteristics in Pueblo Reservoir were simulated using a laterally averaged, two-dimensional model that was calibrated using data collected from October 1985 through September 1987. The Pueblo Reservoir model was calibrated based on vertical profiles of water temperature and dissolved-oxygen concentration, and water-quality constituent concentrations collected in the epilimnion and hypolimnion at four sites in the reservoir. The calibrated model was verified with data from October 1999 through September 2002, which included a relatively wet year (water year 2000), an average year (water year 2001), and a dry year (water year 2002). Simulated water temperatures compared well to measured water temperatures in Pueblo Reservoir from October 1985 through September 1987. Spatially, simulated water temperatures compared better to measured water temperatures in the downstream part of the reservoir than in the upstream part of the reservoir. Differences between simulated and measured water temperatures also varied through time. Simulated water temperatures were slightly less than measured water temperatures from March to May 1986 and 1987, and slightly greater than measured data in August and September 1987. Relative to the calibration period, simulated water temperatures during the verification period did not compare as well to measured water temperatures. In general, simulated dissolved-oxygen concentrations for the calibration period compared well to measured concentrations in Pueblo Reservoir. Spatially, simulated concentrations deviated more from the measured values at the downstream part of the reservoir than at other locations in the reservoir. Overall, the absolute mean error ranged from 1.05 (site 1B) to 1.42 milligrams per liter (site 7B), and the root mean square error ranged from 1.12 (site 1B) to 1.67 milligrams per liter (site 7B). Simulated dissolved oxygen in the verification period compared better to the measured concentrations than in the calibration period. The absolute mean error ranged from 0.91 (site 5C) to 1.28 milligrams per liter (site 7B), and the root mean square error ranged from 1.03 (site 5C) to 1.46 milligrams per liter (site 7B). Simulated total dissolved solids generally were less than measured total dissolved-solids concentrations in Pueblo Reservoir from October 1985 through September 1987. The largest differences between simulated and measured total dissolved solids were observed at the most downstream sites in Pueblo Reservoir during the second year of the calibration period. Total dissolved-solids data were not available from reservoir sites during the verification period, so in-reservoir specific-conductance data were compared to simulated total dissolved solids. Simulated total dissolved solids followed the same patterns through time as the measured specific conductance data during the verification period. Simulated total nitrogen concentrations compared relatively well to measured concentrations in the Pueblo Reservoir model. The absolute mean error ranged from 0.21 (site 1B) to 0.27 milligram per liter as nitrogen (sites 3B and 7

Scientific Investigations Report↗
USGS2018

Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study

With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class.

Physical Geography↗
USGS2005

Assessing climate change effects on mountain ecosystems using integrated models: A case study

Mountain systems are characterized by strong environmental gradients, rugged topography and extreme spatial heterogeneity in ecosystem structure and composition. Consequently, most mountainous areas have relatively high rates of endemism and biodiversity, and function as species refugia in many areas of the world. Mountains have long been recognized as critical entities in regional climatic and hydrological dynamics but their importance as terrestrial carbon stores has only been recently underscored (Schimel et al. 2002; this volume). Mountain ecosystems, therefore, are globally important as well as unusually complex. These ecosystems challenge our ability to understand their dynamics and predict their response to climatic variability and global-scale environmental change. To meet this challenge, mountain scientists increasingly are modeling the vast array of relationships that comprise ecosystem dynamics. Dynamic modeling can examine the interactions between land management strategies and climatic change to develop appropriate responses to future human demands on mountain systems. Modeling provides spatially and temporally explicit, quantified results that can be validated in the field, thus providing feedback to our understanding of ecosystem dynamics. Modeling results, particularly maps and other visual tools, also give a concrete dimension to our understanding of the scale and magnitude of potential future changes. Modeling alerts scientists and land managers to apparently counter-intuitive outcomes of ecosystem responses to climate change or management decisions. For instance, in an early modeling exercise for northwest Montana, USA, Running and Nemani (1991) found that streamflow in a warmer future climate decreased by 30% in the Swan Range even when precipitation was increased by 10% in a particular climate change scenario. This unexpected response was due to enhanced forest growth, and increased evapotranspiration, resulting from the earlier snowmelt and extended growing season. There is a rich legacy of models that address climate and weather, hydrology, forest growth (e.g. gap dynamics and succession), forest fires (e.g. fuel loading) and land cover change (cf. Bugmann et al., this volume). Much less common, however, are attempts to fully integrate models from various disciplines to create a robust system that adequately addresses the entire range of ecosystem dynamics. In addition, fine-resolution modeling of entire mountain ranges (i.e. regional ecosystem scale) is not as common as global or continental scale modeling or watershed/catchment scale modeling. However, this is the scale that is germane to policy decisions such as in the western US and Canada, i.e. in those areas that contain most of the mountainous terrain of North America. This paper describes our efforts to implement an integrated regional modeling approach while characterizing potential future responses of a mountain ecosystem to climate change. Our study area was Glacier National Park in northwestern Montana, USA. Glacier Park is a 4082 km” mountain wilderness that straddles the continental divide and contains over 150 summits of up to 3150 m elevation in the Lewis and Livingston mountain ranges.

Book chapter↗
USGS2019

Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification

Visual identification of fish eggs is difficult and unreliable due to a lack of information on the morphological egg characteristics of many species. We used random forests machine learning to predict the identity of genetically identified Bighead Carp Hypophthalmichthys nobilis , Grass Carp Ctenopharyngodon idella , and Silver Carp H. molitrix eggs based on egg morphometric and environmental characteristics. Family, genus, and species taxonomic-level random forests models were explored to assess the performance and accuracy of the predictor variables. The egg characteristics of Bighead Carp, Grass Carp, and Silver Carp were similar, and they were difficult to distinguish from one another. When combined into a single invasive carp class, the random forests models were ≥ 97% accurate at identifying invasive carp eggs, with a ≤5% false positive rate. Egg membrane diameter was the most important predictive variable, but the addition of ten other variables resulted in a 98% success rate for identifying invasive carp eggs from 26 other upper Mississippi River basin species. Our results revealed that a combination of morphometric and environmental measurements can be used to identify invasive carp eggs. Similar machine learning approaches could be used to identify the eggs of other fishes. These results will help managers more easily and quickly assess invasive carp reproduction.

Iowa↗
USGS2025

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington↗