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At least 775 records · Page 43Linked to original sources
USGS2011

Land use and habitat conditions across the southwestern Wyoming sagebrush steppe: development impacts, management effectiveness and the distribution of invasive plants

For the past several years, USGS has taken a multi-faceted approach to investigating the condition and trends in sagebrush steppe ecosystems. This recent effort builds upon decades of work in semi-arid ecosystems providing a specific, applied focus on the cumulative impacts of expanding human activities across these landscapes. Here, we discuss several on-going projects contributing to these efforts: (1) mapping and monitoring the distribution and condition of shrub steppe communities with local detail at a regional scale, (2) assessing the relationships between specific, land-use features (for example, roads, transmission lines, industrial pads) and invasive plants, including their potential (environmentally defined) distribution across the region, and (3) monitoring the effects of habitat treatments on the ecosystem, including wildlife use and invasive plant abundance. This research is focused on the northern sagebrush steppe, primarily in Wyoming, but also extending into Montana, Colorado, Utah and Idaho. The study area includes a range of sagebrush types (including, Artemisia tridentata ssp. tridentata, Artemisia tridentata ssp. wyomingensis, Artemisia tridentata ssp. vaseyana, Artemisia nova) and other semi-arid shrubland types (for example, Sarcobatus vermiculatus, Atriplex confertifolia, Atriplex gardneri), impacted by extensive interface between steppe ecosystems and industrial energy activities resulting in a revealing multiple-variable analysis. We use a combination of remote sensing (AWiFS (1 Any reference to platforms, data sources, equipment, software, patented or trade-marked methods is for information purposes only. It does not represent endorsement of the U.S.D.I., U.S.G.S. or the authors), Landsat and Quickbird platforms), Geographic Information System (GIS) design and data management, and field-based, replicated sampling to generate multiple scales of data representing the distribution of shrub communities for the habitat inventory. Invasive plant sampling focused on the interaction between human infrastructure and weedy plant distributions in southwestern Wyoming, while also capturing spatial variability associated with growing conditions and management across the region. In a separate but linked study, we also sampled native and invasive composition of recent and historic habitat treatments. Here, we summarize findings of this ongoing work, highlighting patterns and relationships between vegetation (native and invasive), land cover, landform, and land-use patterns in the sagebrush steppe.

Wyoming↗
USGS2005

The Modular Modeling System (MMS): A toolbox for water- and environmental-resources management

The increasing complexity of water- and environmental-resource problems require modeling approaches that incorporate knowledge from a broad range of scientific and software disciplines. To address this need, the U.S. Geological Survey (USGS) has developed the Modular Modeling System (MMS). MMS is an integrated system of computer software for model development, integration, and application. Its modular design allows a high level of flexibility and adaptability to enable modelers to incorporate their own software into a rich array of built-in models and modeling tools. These include individual process models, tightly coupled models, loosely coupled models, and fully- integrated decision support systems. A geographic information system (GIS) interface, the USGS GIS Weasel, has been integrated with MMS to enable spatial delineation and characterization of basin and ecosystem features, and to provide objective parameter-estimation methods for models using available digital data. MMS provides optimization and sensitivity-analysis tools to analyze model parameters and evaluate the extent to which uncertainty in model parameters affects uncertainty in simulation results. MMS has been coupled with the Bureau of Reclamation object-oriented reservoir and river-system modeling framework, RiverWare, to develop models to evaluate and apply optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. This decision support system approach has been developed, tested, and implemented in the Gunnison, Yakima, San Joaquin, Rio Grande, and Truckee River basins of the western United States. MMS is currently being coupled with the U.S. Forest Service model SIMulating Patterns and Processes at Landscape Scales (SIMPPLLE) to assess the effects of alternative vegetation-management strategies on a variety of hydrological and ecological responses. Initial development and testing of the MMS-SIMPPLLE integration is being conducted on the Colorado Plateau region of the western United Sates.

Conference Paper↗
USGS2000

Comparing strengths of geographic and nongeographic classifications of stream benthic macroinvertebrates in the Mid-Atlantic Highlands, USA

The US Environmental Protection Agency’s (USEPA) Environmental Monitoring and Assessment Program (EMAP) sampled ∼500 wadeable streams in the Mid-Atlantic Highlands region of the US during the late spring of 1993 to 1995 for a variety of physical, chemical, and biological indicators of environmental condition. Eighty-eight sites that were minimally affected by human activities were chosen to determine the extent to which geographic and stream-based classifications accounted for variation in the composition of riffle macroinvertebrate assemblages. Bray–Curtis similarities among sites were calculated from the relative abundance of macroinvertebrates to assess the strength of classifications based on geography (ecoregions and catchments), habitat (slope and stream order), and water chemistry (conductivity). For comparison, a taxonomic classification (two-way indicator species analysis, TWINSPAN) and a gradient analysis (correspondence analysis, CA) were performed on the macroinvertebrate data. To assess the effect of taxonomic resolution, all analyses were completed at the family level and to lowest practical taxon. The large overall variation within and among ecoregions resulted in a low average classification strength ( CS ) of ecoregions, although some ecoregions had high CS. Stream order had the highest CS of the habitat and water chemistry classifications. Ecoregion CS increased, however, when stream sites were 1 st stratified by stream order (ecoregions nested within stream order). Nested ecoregion CS did not increase within 1 st -order streams, yet increased within 2 nd - and 3 rd -order streams. CA ordinations and TWINSPAN classification showed a clear gradient of streams along stream size (order), with a clear separation of 1 st - and 3 rd -order streams based on macroinvertebrate composition. The ordinations did not, however, show a distinct clustering of sites on the basis of ecoregions. Overall, the lowest practical taxon level of identification resulted in a clearer pattern of sites in ordination space than did family-level identification, yet only a slight improvement in the different classifications (geographic, habitat, and water chemistry) based on average similarity.

Maryland, New York, Pennsylvania, Virginia, West V↗
USGS1997

Water-quality assessment of the Potomac River Basin: Analysis of available pesticide data, 1972-1990

A study of available data for the period from 1972 to 1990 was conducted to characterize the occurrence and distribution of pesticides in surface water, bottom material, ground water, and fish tissue in the Potomac River Basin. The study was conducted by the Potomac River study unit of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. Existing data coverage was evaluated to guide future data-collection activities. Data from computer data bases and from published and unpublished reports were obtained from local, State, and Federal agencies in the four Potomac River Basin states and the District of Columbia. Data are available for all environmental media, but geographic and temporal coverage are limited. Clusters of data occur in the north-central parts of the basin, with numerous samples at discrete locations in the Shenandoah and Monocacy River Basins, along the mainstem Potomac River, in the Washington, D.C., area, and in streams along the Potomac Estuary. Much of the available surface-water and bottom-material data are from the earlier years of the period of interest, the ground-water data are from the middle years, and the fish-tissue data are distributed over much of the period. Overall, temporal coverage is not sufficient for analysis of trends. Comparisons between different sample media are possible in some areas of the Potomac River Basin, particularly in the northern end of the Great Valley. Residual concentrations of some pesticides have been found in surface water, bottom material, ground water, and fish tissue. Samples have been analyzed for a total of at least 69 pesticides and related compounds in surface water, bottom material, ground water, and fish tissue. Most concentrations of the pesticides analyzed during the period from 1972 to 1990 were less than or equal to reporting limits. For surface-water samples, 13 out of 41 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported in surface water included 2,4-D, atrazine, aldrin, chlordane, DDT and related compounds, dieldrin, endrin, lindane, prometone, prometryne, and simazine. For bottom material samples, 19 of 31 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported in bottom material included aldrin, chlordane, DDT and related compounds, diazinon, dieldrin, endosulfan, endrin, ethion, heptachlor, heptachlor epoxide, lindane, parathion, and toxaphene. In ground-water samples, 14 of 39 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported in ground water included 2,4-D, atrazine, chlordane, cyanazine, DDT and related compounds, diazinon, dieldrin, endosulfan, endrin, heptachlor epoxide, malathion, methyl parathion, simazine. For fish-tissue samples, 30 of the 37 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported included aldrin, chlorpyrifos, dacthal, dieldrin, endrin, HCB, heptachlor, heptachlor epoxide, methoxychlor, mirex, PCA, toxaphene, and those compounds related to chlordane, DDT, and lindane.

Maryland, Pennsylvania, Virginia, West Virginia↗
USGS2024

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter↗
USGS2016

Assessing models of speciation under different biogeographic scenarios; An empirical study using multi-locus and RNA-seq analyses

Evolutionary biology often seeks to decipher the drivers of speciation, and much debate persists over the relative importance of isolation and gene flow in the formation of new species. Genetic studies of closely related species can assess if gene flow was present during speciation, because signatures of past introgression often persist in the genome. We test hypotheses on which mechanisms of speciation drove diversity among three distinct lineages of desert tortoise in the genus Gopherus . These lineages offer a powerful system to study speciation, because different biogeographic patterns (physical vs. ecological segregation) are observed at opposing ends of their distributions. We use 82 samples collected from 38 sites, representing the entire species' distribution and generate sequence data for mtDNA and four nuclear loci. A multilocus phylogenetic analysis in *BEAST estimates the species tree. RNA‐seq data yield 20,126 synonymous variants from 7665 contigs from two individuals of each of the three lineages. Analyses of these data using the demographic inference package ∂a∂i serve to test the null hypothesis of no gene flow during divergence. The best‐fit demographic model for the three taxa is concordant with the *BEAST species tree, and the ∂a∂i analysis does not indicate gene flow among any of the three lineages during their divergence. These analyses suggest that divergence among the lineages occurred in the absence of gene flow and in this scenario the genetic signature of ecological isolation (parapatric model) cannot be differentiated from geographic isolation (allopatric model).

Ecology and Evolution↗
USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗
USGS2009

A habitat assessment for Florida panther population expansion into central Florida

One of the goals of the Florida panther ( Puma concolor coryi ) recovery plan is to expand panther range north of the Caloosahatchee River in central Florida. Our objective was to evaluate the potential of that region to support panthers. We used a geographic information system and the Mahalanobis distance statistic to develop a habitat model based on landscape characteristics associated with panther home ranges. We used cross-validation and an independent telemetry data set to test the habitat model. We also conducted a least-cost path analysis to identify potential habitat linkages and to provide a relative measure of connectivity among habitat patches. Variables in our model were paved road density, major highways, human population density, percentage of the area permanently or semipermanently flooded, and percentage of the area in natural land cover. Our model clearly identified habitat typical of that found within panther home ranges based on model testing with recent telemetry data. We identified 4 potential translocation sites that may support a total of approximately 36 panthers. Although we identified potential habitat linkages, our least-cost path analyses highlighted the extreme isolation of panther habitat in portions of the study area. Human intervention will likely be required if the goal is to establish female panthers north of the Caloosahatchee in the near term.

Florida↗
USGS2008

Chemical and toxicologic assessment of organic contaminants in surface water using passive samplers

Passive sampling methodologies were used to conduct a chemical and toxicologic assessment of organic contaminants in the surface waters of three geographically distinct agricultural watersheds. A selection of current-use agrochemicals and persistent organic pollutants, including polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine pesticides, were targeted using the polar organic chemical integrative sampler (POCIS) and the semipermeable membrane device passive samplers. In addition to the chemical analysis, the Microtox assay for acute toxicity and the yeast estrogen screen (YES) were conducted as potential assessment tools in combination with the passive samplers. During the spring of 2004, the passive samplers were deployed for 29 to 65 d at Leary Weber Ditch, IN; Morgan Creek, MD; and DR2 Drain, WA. Chemical analysis of the sampler extracts identified the agrochemicals predominantly used in those areas, including atrazine, simazine, acetochlor, and metolachlor. Other chemicals identified included deethylatrazine and deisopropylatrazine, trifluralin, fluoranthene, pyrene, cis- and trans-nonachlor, and pentachloroanisole. Screening using Microtox resulted in no acutely toxic samples. POCIS samples screened by the YES assay failed to elicit a positive estrogenic response. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗
USGS2015

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions. Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem. Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular databases, such as the U.S. Department of Agriculture's SCS/S015 ( Soil Survey Staff, 1983 ), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner. During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition. The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available. The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will: Incorporate digital terrain and spectral data into a spatial database for soil surveys. Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process. Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data. Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

Book chapter↗
USGS2018

Developing a framework for evaluating tallgrass prairie reconstruction methods and management

The thousands of hectares of prairie reconstructed each year in the tallgrass prairie biome can provide a valuable resource for evaluation of seed mixes, planting methods, and post-planting management if methods used and resulting characteristics of the prairies are recorded and compiled in a publicly accessible database. The objective of this study was to evaluate the use of such data to understand the outcomes of reconstructions over a 10-year period at two U.S. Fish and Wildlife Service refuges. Variables included number of species planted, seed source (combine-harvest or combine-harvest plus hand-collected), fire history, and planting method and season. In 2015 we surveyed vegetation on 81 reconstructions and calculated proportion of planted species observed; introduced species richness; native species richness, evenness and diversity; and mean coefficient of conservatism. We conducted exploratory analyses to learn how implied communities based on seed mix compared with observed vegetation; which seeding or management variables were influential in the outcome of the reconstructions; and consistency of responses between the two refuges. Insights from this analysis include: 1) proportion of planted species observed in 2015 declined as planted richness increased, but lack of data on seeding rate per species limited conclusions about value of added species; 2) differing responses to seeding and management between the two refuges suggest the importance of geographic variability that could be addressed using a public database; and 3) variables such as fire history are difficult to quantify consistently and should be carefully evaluated in the context of a public data repository.

Ecological Restoration↗
USGS2017

Methods for estimating selected low-flow frequency statistics and harmonic mean flows for streams in Iowa

A statewide study was conducted to develop regression equations for estimating six selected low-flow frequency statistics and harmonic mean flows for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include: the annual 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years, the annual 30-day mean low flow for a recurrence interval of 5 years, and the seasonal (October 1 through December 31) 1- and 7-day mean low flows for a recurrence interval of 10 years. Estimation equations also were developed for the harmonic-mean-flow statistic. Estimates of these seven selected statistics are provided for 208 U.S. Geological Survey continuous-record streamgages using data through September 30, 2006. The study area comprises streamgages located within Iowa and 50 miles beyond the State's borders. Because trend analyses indicated statistically significant positive trends when considering the entire period of record for the majority of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. The median number of years of record used to compute each of these seven selected statistics was 35. Geographic information system software was used to measure 54 selected basin characteristics for each streamgage. Following the removal of two streamgages from the initial data set, data collected for 206 streamgages were compiled to investigate three approaches for regionalization of the seven selected statistics. Regionalization, a process using statistical regression analysis, provides a relation for efficiently transferring information from a group of streamgages in a region to ungaged sites in the region. The three regionalization approaches tested included statewide, regional, and region-of-influence regressions. For the regional regression, the study area was divided into three low-flow regions on the basis of hydrologic characteristics, landform regions, and soil regions. A comparison of root mean square errors and average standard errors of prediction for the statewide, regional, and region-of-influence regressions determined that the regional regression provided the best estimates of the seven selected statistics at ungaged sites in Iowa. Because a significant number of streams in Iowa reach zero flow as their minimum flow during low-flow years, four different types of regression analyses were used: left-censored, logistic, generalized-least-squares, and weighted-least-squares regression. A total of 192 streamgages were included in the development of 27 regression equations for the three low-flow regions. For the northeast and northwest regions, a censoring threshold was used to develop 12 left-censored regression equations to estimate the 6 low-flow frequency statistics for each region. For the southern region a total of 12 regression equations were developed; 6 logistic regression equations were developed to estimate the probability of zero flow for the 6 low-flow frequency statistics and 6 generalized least-squares regression equations were developed to estimate the 6 low-flow frequency statistics, if nonzero flow is estimated first by use of the logistic equations. A weighted-least-squares regression equation was developed for each region to estimate the harmonic-mean-flow statistic. Average standard errors of estimate for the left-censored equations for the northeast region range from 64.7 to 88.1 percent and for the northwest region range from 85.8 to 111.8 percent. Misclassification percentages for the logistic equations for the southern region range from 5.6 to 14.0 percent. Average standard errors of prediction for generalized least-squares equations for the southern region range from 71.7 to 98.9 percent and pseudo coefficients of determination for the generalized-least-squares equations range from 87.7 to 91.8 percent. Average standard errors of prediction for weighted-least-squares equations developed for estimating the harmonic-mean-flow statistic for each of the three regions range from 66.4 to 80.4 percent. The regression equations are applicable only to stream sites in Iowa with low flows not significantly affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. If the equations are used at ungaged sites on regulated streams, or on streams affected by water-supply and agricultural withdrawals, then the estimates will need to be adjusted by the amount of regulation or withdrawal to estimate the actual flow conditions if that is of interest. Caution is advised when applying the equations for basins with characteristics near the applicable limits of the equations and for basins located in karst topography. A test of two drainage-area ratio methods using 31 pairs of streamgages, for the annual 7-day mean low-flow statistic for a recurrence interval of 10 years, indicates a weighted drainage-area ratio method provides better estimates than regional regression equations for an ungaged site on a gaged stream in Iowa when the drainage-area ratio is between 0.5 and 1.4. These regression equations will be implemented within the U.S. Geological Survey StreamStats web-based geographic-information-system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the seven selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these seven selected statistics are provided for the streamgage.

Iowa↗
USGS2011

Factors influencing riverine fish assemblages in Massachusetts

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, Massachusetts Department of Environmental Protection, and the Massachusetts Department of Fish and Game, conducted an investigation of fish assemblages in small- to medium-sized Massachusetts streams. The objective of this study was to determine relations between fish-assemblage characteristics and anthropogenic factors, including impervious cover and estimated flow alteration, relative to the effects of environmental factors, including physical-basin characteristics and land use. The results of this investigation supersede those of a preliminary analysis published in 2010. Fish data were obtained for 669 fish-sampling sites from the Massachusetts Division of Fisheries and Wildlife fish-community database. A review of the literature was used to select fish metrics - species richness, abundance of individual species, and abundances of species grouped on life history traits - responsive to flow alteration. The contributing areas to the fish-sampling sites were delineated and used with a geographic information system to determine a set of environmental and anthropogenic factors that were tested for use as explanatory variables in regression models. Reported and estimated withdrawals and return flows were used together with simulated unaltered streamflows to estimate altered streamflows and indicators of flow alteration for each fish-sampling site. Altered streamflows and indicators of flow alteration were calculated on the basis of methods developed in a previous U.S. Geological Survey study in which unaltered daily streamflows were simulated for a 44-year period (water years 1961-2004), and streamflow alterations were estimated by use of water-withdrawal and wastewater-return data previously reported to the State for the 2000-04 period and estimated domestic-well withdrawals and septic-system discharges. A variable selection process, conducted using principal components analysis and Spearman rank correlation, was used to select a set of 15 non-redundant environmental and anthropogenic factors to test for use as explanatory variables in the regression analyses. Twenty-one fish species were used in a multivariate analysis of fish-assemblage patterns. Results of nonmetric multidimensional scaling and hierarchical cluster analysis were used to group fish species into fluvial and macrohabitat generalist habitat-use classes. Two analytical techniques, quantile regression and generalized linear modeling, were applied to characterize the association between fish-response variables and environmental and anthropogenic explanatory variables. Quantile regression demonstrated that as percent impervious cover and an indicator of percent alteration of August median flow from groundwater withdrawals increase, the relative abundance and species richness of fluvial fish decrease. The quantile regression plots indicate that (1) as many as seven fluvial fish species are expected in streams with little flow alteration or impervious cover, (2) no more than four fluvial fish species are expected in streams where flow alterations from groundwater withdrawals exceed 50 percent of the August median flow or the percent area of impervious cover exceeds 15 percent, and (3) few fluvial fish remain at high rates of withdrawal (approaching 100 percent) or high rates of impervious cover (between 25 and 30 percent). Three generalized linear models (GLMs) were developed to quantify the response of fluvial fish to multiple environmental and anthropogenic variables. All variables in the GLM equations were demonstrated to be significant (p less than 0.05, with most less than 0.01). Variables in the fluvial-fish relative-abundance model were channel slope, estimated percent alteration of August median flow from groundwater withdrawals, percent wetland in a 240-meter buffer strip, and percent impervious cover. Variables in the fluvial-fish species-richness model were drainage area, channel slope, total undammed reach length, percent wetland in a 240-meter buffer strip, and percent impervious cover. Variables in the brook trout relativeabundance model were drainage area, percent open water, and percent impervious cover. The variability explained by the GLM models, as measured by the pseudo R2, ranged from 18.2 to 34.6, and correlations between observed and predicted values ranged from 0.50 to 0.60. Results of GLM models indicated that, keeping all other variables the same, a one-unit (1 percent) increase in the percent depletion of August median flow would result in a 0.9-percent decrease in the relative abundance (in counts per hour) of fluvial fish. The results of GLM models also indicated that a unit increase in impervious cover (1 percent) resulted in a 3.7-percent decrease in the relative abundance of fluvial fish, a 5.4-percent decrease in fluvial-fish species richness, and an 8.7-percent decrease in brook trout relative abundance.

Massachusetts↗
USGS2015

Methods for estimating flow-duration curve and low-flow frequency statistics for ungaged locations on small streams in Minnesota

Knowledge of the magnitude and frequency of low flows in streams, which are flows in a stream during prolonged dry weather, is fundamental for water-supply planning and design; waste-load allocation; reservoir storage design; and maintenance of water quality and quantity for irrigation, recreation, and wildlife conservation. This report presents the results of a statewide study for which regional regression equations were developed for estimating 13 flow-duration curve statistics and 10 low-flow frequency statistics at ungaged stream locations in Minnesota. The 13 flow-duration curve statistics estimated by regression equations include the 0.0001, 0.001, 0.02, 0.05, 0.1, 0.25, 0.50, 0.75, 0.9, 0.95, 0.99, 0.999, and 0.9999 exceedance-probability quantiles. The low-flow frequency statistics include annual and seasonal (spring, summer, fall, winter) 7-day mean low flows, seasonal 30-day mean low flows, and summer 122-day mean low flows for a recurrence interval of 10 years. Estimates of the 13 flow-duration curve statistics and the 10 low-flow frequency statistics are provided for 196 U.S. Geological Survey continuous-record streamgages using streamflow data collected through September 30, 2012. The study area includes 196 streamgages located within Minnesota and 50 miles beyond the State’s borders in North Dakota, South Dakota, Iowa, and Wisconsin. The study area was divided into five regions that were developed in a previous study using the concept of hydrologic landscape units. Geographic information system software was used to calculate 18 characteristics investigated as potential explanatory variables in regression analyses for each streamgage drainage basin. Trend analyses indicated statistically significant trends in summer 7-day low flows that were not related to precipitation patterns for 19 streamgages. For 16 of these streamgages, the streamflow record was subset using structural change analysis to identify the most recent period of record without a significant trend. The three remaining streamgages with significant trends were excluded from the final analysis because the effective period of record without a significant trend was less than 10 years. Because several streams in this study have zero flow as their minimum reported flow, weighted left-censored regression was used to analyze the flow data in an unbiased manner, with weights based on the number of years of record. A total of 115 regression equations were developed in this study to calculate flow-duration curve and low-flow frequency statistics for ungaged locations in the study area. In addition, data from 25 pairs of streamgages were used to develop drainage-area ratio equations that can be used to estimate streamflow statistics at ungaged locations on streams that have a streamgage in another location. Streamflow statistics estimated using regional regression and drainage-area ratio equations were compared among regions. For regions A, D, and E, drainagearea ratio equations were more accurate than regional regression equations for flows, but regional regression equations were more accurate for high flows. For region F, regional regression equations were consistently more accurate than drainage-area ratio equations. For region BC, the pattern in accuracies of regional regression and drainage-area ratio equations between low flows and high flows was not consistent. Equations developed in this study apply only to stream locations where flows are not substantially affected by regulation, diversion, or urbanization. All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.

Iowa, Minnesota, North Dakota, South Dakota, Wisco↗
USGS2019

Patterning emergent marsh vegetation assemblages in coastal Louisiana, USA, with unsupervised artificial neural networks

Question Are self‐organizing maps (SOMs) useful for patterning coastal wetland vegetation communities? Do SOMs provide robust alternatives to traditional classification methods, particularly when underlying species response functions are unknown or difficult to approximate, or when a need exists to continuously classify new samples obtained under ongoing long‐term ecosystem monitoring programs as they become available?. Location Coastal Louisiana, USA. Methods A SOM was trained from in situ observations of 559 vegetation species relative cover data from 2526 samples collected over eight years at 343 locations across coastal Louisiana. Hierarchical cluster analysis was applied to the SOM output to delineate vegetation community types, and indicator species analysis was conducted. Salinity and flood duration were compared across the delineated community types. Results The SOM patterned the 2526 training samples into 260 output neurons, which were further clustered into eleven community types. Clear gradients in salinity and flood duration existed among the community types, and geographic zonation of the communities was evident across the landscape. At some locations assemblages were temporally stable; at other locations they varied considerably. Samples not used in training the network were effectively projected onto the SOM and assigned to one of the delineated community types. Conclusions The SOM was effective in delineating plant communities in the region that were qualitatively similar to those obtained in previous investigations. Being robust to skewed distributions and the presence of outliers, SOMs provide an alternative to traditional distribution‐based statistical approaches. Their ability to efficiently classify new data into existing community types makes their use an ideal approach to classifying samples obtained from ongoing, long‐term ecological monitoring programs.

Louisiana↗
USGS2018

Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se , based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

Montana↗
USGS2009

Modern benthic ostracodes from Lutzow-Holm Bay, East Antarctica: paleoceanographic, paleobiogeographic, and evolutionary significance

Seventy-three ostracode species from 38 genera were recovered from the 55 surface sediment samples in Lützow-Holm Bay, northeastern Antarctica. We investigated bathymetric and geographic distributions of modern benthic ostracode species in the bay and compared this fauna with published modern and fossil ostracode data of Antarctic and southern South American regions. The results show: (1) Four biotopes and three sub-biotopes are recognized based on Q-mode cluster analysis, which suggest distributions of modern ostracodes are mainly controlled by water-mass structure, ice scouring, and light availability. (2) Comparison between the Lützow-Holm Bay fauna and other ostracode faunas from Antarctica and southern South America shows high endemism and homogeneity of Antarctic ostracode fauna, suggesting in situ evolution of most extant Antarctic species. (3) Most species are endemic to the Antarctica, a few species also inhabit South American waters.

Micropaleontology↗
USGS2013

Wildfire and aspect effects on hydrologic states after the 2010 Fourmile Canyon Fire

Wildfire can change how soils take in, store, and release water. This study examined differences in how burned and unburned plots on north versus south-facing slope aspects respond to rainfall. The largest wildfire impacts were litter/duff combustion on burned north-facing slopes versus soil-water retention reduction on burned south-facing slopes. Wildfire is one of the most significant disturbances in mountainous landscapes, affecting water supply and ecologic function and setting the stage for natural hazards such as flash floods. The impacts of wildfire can affect the entire hydrologic cycle. Measurements of soil-water content and matric potential in the near surface (top 30 cm) captured the hydrologic state in both burned and unburned hillslopes during the first spring through fall period (1 June–1 Oct. 2011) after the 2010 Fourmile Canyon Fire near Boulder, CO. This time span included different hydrologic periods characterized by cyclonic frontal storms (low-intensity, long duration), convective storms (high-intensity, short duration), and dry periods. In mountainous environments, aspect can also control hydrologic states, so north- vs. south-facing slopes were compared. Wildfire tended to homogenize soil-water contents across aspects and with depth in the soil, yet it also may have introduced an aspect control on matric potential that was not observed in unburned soils. Post-wildfire changes in hydrologic state were observed in south-facing soils, probably reflecting decreased soil-water retention after wildfire. North-facing soils were impacted the most, in terms of hydrologic state, by the loss of water storage in the combusted litter–duff layer and forest canopy, which had provided a large “hydrologic buffering” capacity when unburned. Unsaturated zone measurements showed increased variability in hydrologic states and more rapid state transitions in wildfire-impacted soils. A simple, qualitative analysis suggested that the range of unsaturated-zone processes along the gravity–capillarity–adsorption continuum was expanded by wildfire for a given soil. The small number of experimental plots in this study suggests that further work is needed before these conclusions can be generalized to other geographic areas.

Vadose Zone Journal↗