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At least 865 records · Page 48Linked to original sources
USGS2010

Emergency use of groundwater as a backup supply: Quantifying hydraulic impacts and economic benefits

Groundwater can play an important role in water‐supply emergency planning. A framework is presented for assessing the hydraulic impacts and associated costs of using groundwater as a backup supply when imported‐water deliveries are disrupted, and for quantifying the emergency benefits of groundwater management strategies that enable better response to such disruptions. Response functions are derived, which relate additional groundwater pumpage during water‐supply emergencies to impacts such as increased pumping costs, subsidence, and seawater intrusion. Monte Carlo analysis is employed to estimate the incremental costs of using groundwater as a backup supply. The emergency benefits of alternative groundwater management strategies are computed for different expected durations of imported water disruption, percentages of imported water replaced by groundwater, and threshold drawdowns for subsidence impacts. The methodology is applied to the coastal Los Angeles Basin. For this case study, emergency benefits of artificial recharge strategies are dominated by reduction of potential subsidence costs. The variance of the results also is primarily due to subsidence effects. Incorporation of probability distributions reflecting a larger expected use of groundwater during the imported‐water disruption results in higher estimated emergency benefits of artificial recharge strategies. The framework presented for quantifying incremental costs and economic benefits of using groundwater as a backup supply could be applied to a broad range of water emergency planning decisions.

California↗
USGS2025

Evaluating deterrent locations and sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to minimize invasive carp occupancy and abundance

Invasive carps, specifically silver carp ( Hypophthalmichthys molitrix ), bighead carp ( H . nobilis ), grass carp ( Ctenopharyngodon idella ), and black carp ( Mylopharyngodon piceus ), have proliferated in the Mississippi River Basin owing to escapes from aquaculture facilities and intentional releases. In the Water Resources and Development Act (WRDA) of 2020 Sec. 509, Congress directed the U.S. Army Corps of Engineers to work with the Tennessee Valley Authority and other relevant agencies with deterrent projects to implement as many as 10 deterrent projects intended to manage and prevent the spread of invasive carp in the Tennessee and Cumberland River subbasins. The WRDA was amended in 2022 to include that at least one location must be situated on the Tennessee–Tombigbee Waterway. This report documents a structured decision-making process that engaged State and Federal agencies to evaluate alternative deterrent site sequences at specified lock and dam complexes on the Tennessee River, Cumberland River, and the Tennessee–Tombigbee Waterway. State and Federal agencies participated in a series of virtual and face-to-face meetings to structure the problem, expand the models used in previous decision analyses for the Tennessee River, and define management objectives. Potential deterrent sites were restricted to the downstream locations on the Tennessee River ( n =3), Cumberland River ( n =2), and the Tennessee–Tombigbee Waterway ( n =10). Only considering 15 sites allowed all feasible deterrent site combinations and sequences to be evaluated. Invasive carp relative abundance was projected for the Tennessee River, Cumberland River, and Tennessee–Tombigbee Waterway management units for 20 years using a simulation model. The deterrent site sequences were ranked based on the system-level invasive carp relative abundance and distribution in year 20. The unique downstream expansion of invasive carp through the Tennessee–Tombigbee Waterway was important to the interest group, but downstream movement rates were unknown; therefore, several downstream movement rates were evaluated, and the outcomes were used to rank deterrent site sequences. Additionally, the analysis incorporated two scenarios involving the retention and removal of an experimental deterrent at Barkley Lock on the Cumberland River. The results of the deterrent site sequences varied among downstream movement rates, with Tennessee–Tombigbee Waterway deterrent locations installed earlier in highly ranked sequences with increasing downstream movement rates. This analysis was time-limited owing to agency needs and represents Phase 1 of this project. Phase 2 expands Phase 1 to address additional uncertainties and more holistic management objectives and strategies.

Alabama, Georgia, Kentucky, Mississippi, Tennessee↗
USGS1997

U.S. Geological Survey Middle Rio Grande Basin Study; Proceedings of the first annual workshop, Denver, Colorado, November 12-14, 1996

Approximately 40 percent (about 600,000 people) of the total population of New Mexico lives within the Middle Rio Grande Basin, which includes the City of Albuquerque. Ongoing analyses of the central portion of the Middle Rio Grande Basin by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque and other cooperators have shown that ground water in the basin is not as readily accessible as earlier studies indicated. A more complete characterization of the ground-water resources of the entire Middle Rio Grande Basin is hampered by a scarcity of data in the northern and southern areas of the basin. The USGS Middle Rio Grande Basin Study is a 5-year effort by the USGS and other agencies to improve the understanding of the hydrology, geology, and land-surface characteristics of the Middle Rio Grande Basin. The primary objective of this study is to improve the understanding of the water resources of the basin. Of particular interest is to determine the extent of hydrologic connection between the Rio Grande and the Santa Fe Group aquifer. Additionally, ground-water quality affects the availability of water supplies in the basin. Improving the existing USGS- constructed ground-water flow model of the Middle Rio Grande Basin will integrate all the various tasks that improve our knowledge of the various components of the Middle Rio Grande water budget. Part of this improvement will be accompanied by extended knowledge of the aquifer system beyond the Albuquerque area into the northern and southern reaches of the basin. Other improvements will be based on understanding gained through process-oriented research and improved geologic characterization of the deposits. The USGS will study the hydrology, geology, and land-surface characteristics of the basin to provide the scientific information needed for water- resources management and for managers to plan for water supplies needed for a growing population. To facilitate exchange of information among the many USGS scientists working in the Middle Rio Grande Basin, yearly technical meetings are planned for the anticipated 5-year study. These meetings provide an opportunity to present research results and plan new field efforts. This report documents the results of research presented at the first technical workshop held in Denver, Colorado, in November 1996. The report is organized into this introduction, five chapters that focus on USGS investigations in progress in the Middle Rio Grande Basin, and three appendixes with supplemental information. The first chapter provides an overview of the USGS program in the basin. The second chapter describes geographic data and analysis efforts in the basin. The third chapter details work being done on the hydrogeologic framework of the basin. The fourth chapter describes studies on ground-water availability in the basin and is divided into three areas of research: ground-water/surface-water interaction, ground-water flow and aquifer properties, and recharge. The fifth chapter is devoted to an overview of New Mexico District Cooperative Program studies in the basin. Finally, the appendixes list publications and presentations made during the first year of the study and 1996 workshop attendees. The report concludes with a list of selected references relevant to the study. The information in this report presents preliminary results of an evolving study. As the study progresses and individual projects publish their results in more detail, the USGS hopes to expand the scientific basis needed for management decisions regarding the Middle Rio Grande Basin.

Open-File Report↗
USGS2016

Continuous-flow centrifugation to collect suspended sediment for chemical analysis

Recent advances in suspended-sediment monitoring tools and surrogate technologies have greatly improved the ability to quantify suspended-sediment concentrations and to estimate daily, seasonal, and annual suspended-sediment fluxes from rivers to coastal waters. However, little is known about the chemical composition of suspended sediment, and how it may vary spatially between water bodies and temporally within a single system owing to climate, seasonality, land use, and other natural and anthropogenic drivers. Many water-quality contaminants, such as organic and inorganic chemicals, nutrients, and pathogens, preferentially partition in sediment rather than water. Suspended sediment-bound chemical concentrations may be undetected during analysis of unfiltered water samples, owing to small water sample volumes and analytical limitations. Quantification of suspended sediment‑bound chemical concentrations is needed to improve estimates of total chemical concentrations, chemical fluxes, and exposure levels of aquatic organisms and humans in receiving environments. Despite these needs, few studies or monitoring programs measure the chemical composition of suspended sediment, largely owing to the difficulty in consistently obtaining samples of sufficient quality and quantity for laboratory analysis. A field protocol is described here utilizing continuous‑flow centrifugation for the collection of suspended sediment for chemical analysis. The centrifuge used for development of this method is small, lightweight, and portable for the field applications described in this protocol. Project scoping considerations, deployment of equipment and system layout options, and results from various field and laboratory quality control experiments are described. The testing confirmed the applicability of the protocol for the determination of many inorganic and organic chemicals sorbed on suspended sediment, including metals, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls. The particle-size distribution of the captured sediment changes to a more fine-grained sample during centrifugation, and the necessity to account for this change when extrapolating chemical concentrations on the centrifuged sediment sample to the environmental water system is discussed. The data produced using this method will help eliminate a data gap of suspended sediment-bound chemical concentrations, and will support management decisions, such as chemical source-control efforts or in-stream restoration activities. When coupled with streamflow and sediment flux data, it will improve estimates of riverine chemical fluxes, and will aid in assessing the importance and impacts of suspended sediment-bound chemicals to downstream freshwater and coastal marine ecosystems.

Techniques and Methods↗
USGS1994

Problems of stock definition in estimating relative contributions of Atlantic striped bass to the coastal fishery

Stock contribution studies of mixed‐stock fisheries rely on the application of classification algorithms to samples of unknown origin. Although the performance of these algorithms can be assessed, there are no guidelines regarding decisions about including minor stocks, pooling stocks into regional groups, or sampling discrete substocks to adequately characterize a stock. We examined these questions for striped bass Morone saxatilis of the U.S. Atlantic coast by applying linear discriminant functions to meristic and morphometric data from fish collected from spawning areas. Some of our samples were from the Hudson and Roanoke rivers and four tributaries of the Chesapeake Bay. We also collected fish of mixed‐stock origin from the Atlantic Ocean near Montauk, New York. Inclusion of the minor stock from the Roanoke River in the classification algorithm decreased the correct‐classification rate, whereas grouping of the Roanoke River and Chesapeake Bay stock into a regional (“southern”) group increased the overall resolution. The increased resolution was offset by our inability to obtain separate contribution estimates of the groups that were pooled. Although multivariate analysis of variance indicated significant differences among Chesapeake Bay substocks, increasing the number of substocks in the discriminant analysis decreased the overall correct‐classification rate, Although the inclusion of one, two, three, or four substocks in the classification algorithm did not greatly affect the overall correct‐classification rates, the specific combination of substocks significantly affected the relative contribution estimates derived from the mixed‐stock sample, Future studies of this kind must balance the costs and benefits of including minor stocks and would profit from examination of the variation in discriminant characters among all Chesapeake Bay substocks.

Maryland↗
USGS2015

Automated lidar-derived canopy height estimates for the Upper Mississippi River System

Land cover/land use (LCU) classifications serve as important decision support products for researchers and land managers. The LCU classifications produced by the U.S. Geological Survey’s Upper Midwest Environmental Sciences Center (UMESC) include canopy height estimates that are assigned through manual aerial photography interpretation techniques. In an effort to improve upon these techniques, this project investigated the use of high-density lidar data for the Upper Mississippi River System to determine canopy height. An ArcGIS tool was developed to automatically derive height modifier information based on the extent of land cover features for forest classes. The measurement of canopy height included a calculation of the average height from lidar point cloud data as well as the inclusion of a local maximum filter to identify individual tree canopies. Results were compared to original manually interpreted height modifiers and to field survey data from U.S. Forest Service Forest Inventory and Analysis plots. This project demonstrated the effectiveness of utilizing lidar data to more efficiently assign height modifier attributes to LCU classifications produced by the UMESC.

Minnesota, Wisconsin↗
USGS2004

Mortality sensitivity in life-stage simulation analysis: A case study of southern sea otters

Currently, there are no generally recognized approaches for linking detailed mortality and pathology data to population-level analyses of extinction risk. We used a combination of analytical and simulation-based analyses to examine 20 years of age- and sex-specific mortality data for southern sea otters ( Enhydra lutris ), and we applied results to project the efficacy of alternative conservation strategies. Population recovery of the southern sea otter has been slow (rate of population increase λ = 1.05) compared to other recovering populations ( λ = 1.17–1.20 ), and the population declined ( λ = 0.975 ) between 1995 and 1999. Age-based Leslie matrices were developed to explore explanations for the slow recovery and recent decline in the southern sea other population. An elasticity analysis was performed to predict effects of proportional changes in stage-specific reproductive or survival rates on the rate of population increase. A life-stage simulation analysis (LSA) was developed to evaluate the impact of changing age- and cause-specific mortality rates on λ . The information used to develop these models was derived from death assemblage, pathology, and live population census data to examine the sensitivity of sea otter population growth to different sources of mortality (e.g., disease and starvation, direct human take [fisheries, gun shot, boat strike, oil pollution], mating trauma and intraspecific aggression, shark bites, and unknown). We used resampling simulations to generate random combinations of vital rates for a large number of matrix replicates and drew on these to estimate potential effects of mortality sources on population growth ( λ ). Our analyses suggest management actions that are likely and unlikely to promote recovery of the southern sea otter and more broadly indicate a methodology to better utilize cause-of-death data in conservation decision-making.

Ecological Applications↗
USGS2023

Linear regression model documentation for computing water-quality constituent concentrations or densities using continuous real-time water-quality data for the Kansas River above Topeka Weir at Topeka, Kansas, November 2018 through June 2021

The Kansas River and its associated alluvial aquifer provide drinking water to more than 950,000 people in northeastern Kansas. Water suppliers that rely on the Kansas River as a water-supply source use physical and chemical processes to treat and remove contaminants before public distribution. An early-notification system of changing water-quality conditions allows water suppliers to proactively make decisions that affect water treatment. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas Water Plan), the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, WaterOne, and Evergy, began collecting water-quality data at the Kansas River above Topeka Weir at Topeka, Kansas (USGS site 06888990, hereafter referred to as the “Topeka site”), during November 2018 to develop linear regression models that relate continuous in situ water-quality sensor measurements to discretely sampled water-quality constituent concentrations or densities. The addition of the Topeka site expanded an existing water-quality monitoring network, which included the upstream Kansas River at Wamego, Kans., and downstream Kansas River at De Soto, Kans., sites. Linear regression analysis was used to develop models that compute real-time concentrations or densities for total dissolved solids, major ions, hardness as calcium carbonate, nutrients (nitrogen and phosphorus species), chlorophyll a , total suspended solids, suspended sediment, and Escherichia coli at the Topeka site using data collected during November 2018 through June 2021. Water-quality constituent concentrations or densities computed from the models documented in this report are available at the USGS National Real-Time Water-Quality website (https://nrtwq.usgs.gov), are useful to the public for cultural and recreational purposes, and can be used to guide water-treatment processes, compare conditions with Federal and State water-quality criteria, and characterize changes in Kansas River water-quality conditions through time.

Kansas↗
USGS2023

Stress gradients structure spatial variability in coastal tidal marsh plant composition and diversity in a major Pacific coast estuary

Understanding the drivers of variability in plant diversity from local to landscape spatial scales is a challenge in ecological systems. Environmental gradients exist at several spatial scales and can be nested hierarchically, influencing patterns of plant diversity in complex ways. As plant community dynamics influence ecosystem function, understanding the drivers of plant community variability across space is paramount for predicting potential shifts in ecosystem function from global change. Determining the scales at which stress gradients influence vegetation composition is crucial to inform management and restoration of tidal marshes for specific functions. Here, we analyzed vegetation community composition in 51 tidal marshes from the San Francisco Bay Estuary, California, USA. We used model-based compositional analysis and rank abundance curves to quantify environmental (elevation/tidal frame position, distance to channel, and channel salinity) and species trait (species form, wetland indicator status, and native status) influences on plant community variability at the marsh site and estuary scales. While environmental impacts on plant diversity varied by species and their relationships to each other, overall impacts increased in strength from marsh to estuary scales. Relative species abundance was important in structuring these tidal marsh communities even with the limited species pools dominated by a few species. Rank abundance curves revealed different community structures by region with higher species evenness at plots higher in the tidal frame and adjacent to freshwater channels. By identifying interactions (species–species, species–environment, and environment–trait) at multiple scales (local, landscape), we begin to understand how variability measurements could be interpreted for conservation and land management decisions.

California↗
USGS2000

Genetic diversity and epidemiology of infectious hematopoietic necrosis virus in Alaska

Forty-two infectious hematopoietic necrosis virus (IHNV) isolates from Alaska were analyzed using the ribonuclease protection assay (RPA) and nucleotide sequencing. RPA analyses, utilizing 4 probes, N5, N3 (N gene), GF (G gene), and NV (NV gene), determined that the haplotypes of all 3 genes demonstrated a consistent spatial pattern. Virus isolates belonging to the most common haplotype groups were distributed throughout Alaska, whereas isolates in small haplotype groups were obtained from only 1 site (hatchery, lake, etc.). The temporal pattern of the GF haplotypes suggested a 'genetic acclimation' of the G gene, possibly due to positive selection on the glycoprotein. A pairwise comparison of the sequence data determined that the maximum nucleotide diversity of the isolates was 2.75% (10 mismatches) for the NV gene, and 1.99% (6 mismatches) for a 301 base pair region of the G gene, indicating that the genetic diversity of IHNV within Alaska is notably lower than in the more southern portions of the IHNV North American range. Phylogenetic analysis of representative Alaskan sequences and sequences of 12 previously characterized IHNV strains from Washington, Oregon, Idaho, California (USA) and British Columbia (Canada) distinguished the isolates into clusters that correlated with geographic origin and indicated that the Alaskan and British Columbia isolates may have a common viral ancestral lineage. Comparisons of multiple isolates from the same site provided epidemiological insights into viral transmission patterns and indicated that viral evolution, viral introduction, and genetic stasis were the mechanisms involved with IHN virus population dynamics in Alaska. The examples of genetic stasis and the overall low sequence heterogeneity of the Alaskan isolates suggested that they are evolutionarily constrained. This study establishes a baseline of genetic fingerprint patterns and sequence groups representing the genetic diversity of Alaskan IHNV isolates. This information could be used to determine the source of an IHN outbreak and to facilitate decisions in fisheries management of Alaskan salmonid stocks.

Diseases of Aquatic Organisms↗
USGS2023

Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast

Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands. Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area. Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington. Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t. Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.

California, Oregon, Washington↗
USGS2019

Predicting surf zone injuries along the Delaware coast using a Bayesian network

Personnel at Beebe Healthcare in Lewes, Delaware, collected surf zone injury (SZI) data for eight summer seasons from 2010 through 2017. Data include, but are not limited to, time of injury, gender, age, and activity. More than 2000 SZI events, including 196 spinal injuries and 6 fatalities, occurred at the five most populated beaches along the 25 miles of Atlantic-fronting coast. SZI are predominantly wave related incidents associated with wading (50.1%), body surfing (18.4%), and body boarding (13.3%). The episodic nature of SZI indicate the importance of linking the environmental conditions and human behavior in the surf zone to predict days with high injury rates. Higher order statistics are necessary to effectively consider all associated factors related to SZI. Two Bayesian networks (BN) were constructed to model SZI and predict changes in injury rate (proportion of injuries to bathers) and injury likelihood (probability of at least one injury occurrence) on an hourly basis. The models incorporate environmental data collected by weather stations, wave gauges, and researcher personnel on the beach. The models include prior (e.g., historic) information to infer relationships between provided parameters. Sensitivity analysis determined the most influential parameters related to injury rates were significant wave height, foreshore slope, and water temperature. Exposure parameters (e.g., air temperature) influenced the number of people in the water, resulting in strong correlation between injury likelihood and the related meteorological conditions (variance reduction > 0.4%). Log likelihood ratio (LLR) scores indicate the network predicts SZI likelihood during any specified hour with more skill than prior predictions with the best performing model improving prediction 69.1% of the time (LLR = 69.1%). An alternative BN predicting injury rate performed worse with the prior probability model out predicting the injury rate network (positive LLR = 36.7%). Issues persist with predicting SZI that have an LLR ≪ -1 (< 5% of 2017 injuries) and occur in conditions different than when most other SZI occur. Better understanding of SZI will improve awareness techniques to both educate beachgoers and assist beach patrol decision making during high risk conditions.

Delaware↗
USGS2017

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush ( Artemisia tridentata ), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata , we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

Global Change Biology↗
USGS2010

Climate change threatens polar bear populations: A stochastic demographic analysis

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in ?? in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log ??s, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log ??s ' - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act. ?? 2010 by the Ecological Society of America.

Ecology↗
USGS2019

Characterizing 12 years of wildland fire science at the U.S. Geological Survey: Wildland Fire Science Publications, 2006–17

Wildland fire characteristics, such as area burned, number of large fires, burn intensity, and fire season duration, have increased steadily over the past 30 years, resulting in substantial increases in the costs of suppressing fires and managing damages from wildland fire events (National Academies of Sciences, Engineering, and Medicine, 2017). Wildland fire management could benefit from sound decision making based on reliable scientific information. Fire scientists produce data, tools, and information to support fire and land management decision making. With ever-changing land use scenarios, environmental conditions, and emerging technological capabilities, new assessments and studies are continually needed. Established by Congress in 1879, the U.S. Geological Survey (USGS) is the primary science branch of the Department of the Interior (DOI), which manages more than 400 million acres of public lands in the United States. The USGS has more than 100 scientists across seven Mission Areas that help address the wildland fire science needs of DOI bureaus and their stakeholders. The diverse expertise of these scientists allows them to address complex interdisciplinary challenges. In this report, we identify and characterize scientific literature produced by USGS scientists during 2006–17 that addresses topics associated with wildland fire science. Our goals were to (1) make the most complete list possible of product citations readily available in an organized format, and (2) use bibliometric analysis approaches to highlight the productivity of USGS scientists and the impact of contributions that the Bureau has provided to the scientific, land management, and fire management communities.

Open-File Report↗
USGS2014

Placing prairie pothole wetlands along spatial and temporal continua to improve integration of wetland function in ecological investigations

We evaluated the efficacy of using chemical characteristics to rank wetland relation to surface and groundwater along a hydrologic continuum ranging from groundwater recharge to groundwater discharge. We used 27 years (1974–2002) of water chemistry data from 15 prairie pothole wetlands and known hydrologic connections of these wetlands to groundwater to evaluate spatial and temporal patterns in chemical characteristics that correspond to the unique ecosystem functions each wetland performed. Due to the mineral content and the low permeability rate of glacial till and soils, salinity of wetland waters increased along a continuum of wetland relation to groundwater recharge, flow-through or discharge. Mean inter-annual specific conductance (a proxy for salinity) increased along this continuum from wetlands that recharge groundwater being fresh to wetlands that receive groundwater discharge being the most saline, and wetlands that both recharge and discharge to groundwater (i.e., groundwater flow-through wetlands) being of intermediate salinity. The primary axis from a principal component analysis revealed that specific conductance (and major ions affecting conductance) explained 71% of the variation in wetland chemistry over the 27 years of this investigation. We found that long-term averages from this axis were useful to identify a wetland’s long-term relation to surface and groundwater. Yearly or seasonal measurements of specific conductance can be less definitive because of highly dynamic inter- and intra-annual climate cycles that affect water volumes and the interaction of groundwater and geologic materials, and thereby influence the chemical composition of wetland waters. The influence of wetland relation to surface and groundwater on water chemistry has application in many scientific disciplines and is especially needed to improve ecological understanding in wetland investigations. We suggest ways that monitoring in situ wetland conditions could be linked with evolving remote sensing technology to improve our ability to better inform decisions affecting wetland sustainability and provide periodic inventories of wetland ecosystem services to document temporal trends in wetland function and how they respond to contemporary land-use change.

North Dakota↗
USGS2011

Ecoregional-scale monitoring within conservation areas, in a rapidly changing climate

Long-term monitoring of ecological systems can prove invaluable for resource management and conservation. Such monitoring can: (1) detect instances of long-term trend (either improvement or deterioration) in monitored resources, thus providing an early-warning indication of system change to resource managers; (2) inform management decisions and help assess the effects of management actions, as well as anthropogenic and natural disturbances; and (3) provide the grist for supplemental research on mechanisms of system dynamics and cause-effect relationships (Fancy et al., 2009). Such monitoring additionally provides a snapshot of the status of monitored resources during each sampling cycle, and helps assess whether legal standards and regulations are being met. Until the last 1-2 decades, tracking and understanding changes in condition of natural resources across broad spatial extents have been infrequently attempted. Several factors, however, are facilitating the achievement of such broad-scale investigation and monitoring. These include increasing awareness of the importance of landscape context, greater prevalence of regional and global environmental stressors, and the rise of landscape-scale programs designed to manage and monitor biological systems. Such programs include the US Forest Service's Forest Inventory and Analysis (FIA) Program (Moser et al., 2008), Canada's National Forest Inventory, the 3Q Programme for monitoring agricultural landscapes of Norway (Dramstad et al., 2002), and the emerging (US) Landscape Conservation Cooperatives (USDOI Secretarial Order 3289, 2009; Anonymous, 2011). This Special Section explores the underlying design considerations, as well as many pragmatic aspects associated with program implementation and interpretation of results from broad-scale monitoring systems, particularly within the constraints of high-latitude contexts (e.g., low road density, short field season, dramatic fluctuations in temperature). Although Alaska is the focus of most papers in this Special Section, we posit that many of the issues that characterize the remote, relatively undisturbed ecosystems of high northern latitudes are widespread and thus applicable to natural-resource management and conservation across northern portions of the Holarctic ecozone and indeed anywhere broad-scale monitoring is contemplated.

Biological Conservation↗
USGS1993

Preservation of genetic variation in the Green Lake strain lake trout derived from remnant domestic and feral populations

The Green Lake, Wisconsin, strain of lake trout Salvelinus namaycush was discontinued as a hatchery brood stock in 1976 after Lake Michigan was stocked with the 1975 year‐class. In 1982, a decision was made to restore the Green Lake strain as a production brood stock. Five groups were produced by spawning marked fish that were survivors from the 1976 stocking of southern Lake Michigan. A sixth group was produced from a remnant of the Green Lake brood stock held at the Genoa (Wisconsin) National Fish Hatchery. Hatchery accidents reduced both the number of groups and the effective population number of each group. We studied a procedure for reconstructing a composite Green Lake brood stock from individuals of these six groups. Genetic variability was evaluated by allozyme electrophoresis in five of these groups. Twelve of 18 loci were polymorphic. Allelic frequencies were similar in all five groups; however, significant differences occurred in nine systems. Heterozygosity level (mean ± SE) was lowest in the domestic group (0.119 ± 0.043) and ranged from 0.139 ± 0.043 to 0.166 ± 0.052 in the feral groups. Cluster analysis of genetic distances grouped the four feral groups together, but separate from the domestic group. Progeny from fish captured on Black Can Reef, Lake Michigan, in 1986 and 1988 were the most similar. A modified diallel mating design was developed to produce a composite brood stock from remnant feral and domestic fish. Pooled families from 1991 and 1992 diallel matings will be reared to maturity, then reciprocal crosses of the two year‐classes will be made to form the new composite Green Lake brood stock.

Wisconsin↗