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John J. Kosovich

Publications and source records attributed to John J. Kosovich.

10 recordsLinked to original sources

Can data from disparate long-term fish monitoring programs be used to increase our understanding of regional and continental trends in large river assemblages?

Understanding trends in the diverse resources provided by large rivers will help balance tradeoffs among stakeholders and inform strategies to mitigate the effects of landscape scale stressors such as climate change and invasive species. Absent a cohesive coordinated effort to assess trends in important large river resources, a logical starting point is to assess our ability to draw inferences from existing efforts. In this paper, we use a common analytical framework to analyze data from five disparate fish monitoring programs to better understand the nature of spatial and temporal trends in large river fish assemblages. We evaluated data from programs that monitor fishes in the Colorado, Columbia, Illinois, Mississippi, and Tallapoosa rivers using non-metric dimensional scaling ordinations and associated tests to evaluate trends in fish assemblage structure and native fish biodiversity. Our results indicate that fish assemblages exhibited significant spatial and temporal trends in all five of the rivers. We also document native species diversity trends that were variable within and between rivers and generally more evident in rivers with higher species richness and programs of longer duration. We discuss shared and basin-specific landscape level stressors. Having a basic understanding of the nature and extent of trends in fish assemblages is a necessary first step towards understanding factors affecting biodiversity and fisheries in large rivers.

PLoS ONE

Long-term fish monitoring in large rivers: Utility of “benchmarking” across basins

In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to learn from those conducting fish monitoring in other rivers. We briefly examine five long-term fish monitoring programs in large rivers in the United States (Colorado, Columbia, Mississippi, Illinois, and Tallapoosa rivers) and identify opportunities for learning across programs by detailing best monitoring practices and why these practices were chosen. Although monitoring objectives, methods, and program maturity differ between each river system, examples from these five case studies illustrate the important role that long-term monitoring programs play in interpreting temporal and spatial shifts in fish populations for both established objectives and newly emerging questions. We suggest that deliberate efforts to develop a broader collaborative network through benchmarking will facilitate sharing of ideas and development of more effective monitoring programs.

Colorado River, Columbia River, Illinois River, Mi

U.S. Geological Survey Science Strategy for the Wyoming Landscape Conservation Initiative

Southwest Wyoming's wildlife and habitat resources are increasingly affected by energy and urban/exurban development, climate change, and other key drivers of ecosystem change. To ensure that southwest Wyoming's wildlife populations and habitats persist in the face of development and other changes, a consortium of public resource-management agencies proposed the Wyoming Landscape Conservation Initiative (WLCI), the overall goal of which is to implement conservation actions. As the principal agency charged with conducting WLCI science, the U.S. Geological Survey (USGS) has developed a Science Strategy for the WLCI. Workshops were held for all interested parties to identify and refine the most pressing management needs for achieving WLCI goals. Research approaches for addressing those needs include developing conceptual models for understanding ecosystem function, identifying key drivers of change affecting WLCI ecosystems, and conducting scientific monitoring and experimental studies to better understand ecosystems processes, cumulative effects of change, and effectiveness of habitat treatments. The management needs drive an iterative, three-phase framework developed for structuring and growing WLCI science efforts: Phase I entails synthesizing existing information to assess current conditions, determining what is already known about WLCI ecosystems, and providing a foundation for future work; Phase II entails conducting targeted research and monitoring to address gaps in data and knowledge during Phase I; and Phase III entails integrating new knowledge into WLCI activities and coordinating WLCI partners and collaborators. Throughout all three phases, information is managed and made accessible to interested parties and used to guide and improve management and conservation actions, future habitat treatments, best management practices, and other conservation activities.

Scientific Investigations Report

Rainfall-Runoff and Erosion Data from the Mancos Shale Formation in the Gunnison Gorge National Conservation Area, Southwestern Colorado, 2003-2006

Data were collected and experiments were conducted from 2003 to 2006 by the U.S. Geological Survey, in cooperation with the Bureau of Land Management, to support research into understanding processes that liberate, disperse, and concentrate erosion byproducts in Mancos Shale landscapes. The study area was the Gunnison Gorge National Conservation Area near Montrose and Delta, Colorado. This report includes data collected from 24, small-plot, rainfall-runoff simulations, 6 hillslope-erosion monitoring plots, 20 hillslope-creep monitoring sites, and 3 precipitation gages. Small-plot rainfall-runoff simulations were performed on paired (undisturbed and disturbed) plots to examine the effect of off-highway vehicle use on runoff and erosion. These data were collected in conjunction with several other studies done by the U.S. Geological Survey in the Gunnison Gorge National Conservation Area. Data collected in companion studies are published in separate open-file reports.

Open-File Report

State of Florida 1:24,000- and 1:100,000-scale quadrangle index map - Highlighting low-lying areas derived from USGS Digital Elevation Models

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts 1:24,000- and 1:100,000-scale quadrangle footprints over a color shaded relief representation of the State of Florida. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Figure 1 shows a similar representation for the entire U.S. Gulf Coast, using coarsened 30-meter NED data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. Quadrangle names, dated April, 2006, were obtained from the Federal Geographic Names Information System. The NED data were downloaded in 2004.

Scientific Investigations Map

Gulf of Mexico region — Highlighting low-lying areas derived from USGS Digital Elevation Data

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation of the area surrounding the Gulf of Mexico. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s data) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of 10-meter contour-derived DEM data or higher-resolution LIDAR data. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2005.

Alabama, Florida, Louisiana, Mississippi, Texas

State of Louisiana - Highlighting low-lying areas derived from USGS Digital Elevation Data

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation highlighting the State of Louisiana and depicts the surrounding areas using muted elevation colors. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data are a mixture of data and were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. Approximately one-half of the area shown on this map has DEM source data at a 30-meter resolution, with the remaining half consisting of mostly 10-meter contour-derived DEM data and some small areas of higher-resolution LIght Detection And Ranging (LIDAR) data along parts of the coastline. Areas below sea level typically are surrounded by levees or some other type of flood-control structures. State and parish boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2007.

Scientific Investigations Map

State of Texas - Highlighting low-lying areas derived from USGS Digital Elevation Data

In support of U.S. Geological Survey (USGS) disaster preparedness efforts, this map depicts a color shaded relief representation of Texas and a grayscale relief of the surrounding areas. The first 30 feet of relief above mean sea level are displayed as brightly colored 5-foot elevation bands, which highlight low-elevation areas at a coarse spatial resolution. Standard USGS National Elevation Dataset (NED) 1 arc-second (nominally 30-meter) digital elevation model (DEM) data are the basis for the map, which is designed to be used at a broad scale and for informational purposes only. The NED data were derived from the original 1:24,000-scale USGS topographic map bare-earth contours, which were converted into gridded quadrangle-based DEM tiles at a constant post spacing (grid cell size) of either 30 meters (data before the mid-1990s) or 10 meters (mid-1990s and later data). These individual-quadrangle DEMs were then converted to spherical coordinates (latitude/longitude decimal degrees) and edge-matched to ensure seamlessness. The NED source data for this map consists of a mixture of 30-meter- and 10-meter-resolution DEMs. State and county boundary, hydrography, city, and road layers were modified from USGS National Atlas data downloaded in 2003. The NED data were downloaded in 2002. Shaded relief over Mexico was obtained from the USGS National Atlas.

Scientific Investigations Map

Results of chemical analyses of soil, shale, and soil/shale extract from the Mancos Shale formation in the Gunnison Gorge National Conservation Area, southwestern Colorado, and at Hanksville, Utah

Results of chemical and some isotopic analyses of soil, shale, and water extracts collected from the surface, trenches, and pits in the Mancos Shale are presented in this report. Most data are for sites on the Gunnison Gorge National Conservation Area (GGNCA) in southwestern Colorado. For comparison, data from a few sites from the Mancos landscape near Hanksville, Utah, are included. Twelve trenches were dug on the GGNCA from which 258 samples for whole-rock (total) analyses and 187 samples for saturation paste extracts were collected. Sixteen of the extract samples were duplicated and subjected to a 1:5 water extraction for comparison. A regional soil survey across the Mancos landscape on the GGNCA generated 253 samples for whole-rock analyses and saturation paste extractions. Seventeen gypsum samples were collected on the GGNCA for sulfur and oxygen isotopic analysis. Sixteen samples were collected from shallow pits in the Mancos Shale near Hanksville, Utah.

Colorado, Utah

Recent U.S. Geological Survey applications of Lidar

As lidar (light detection and ranging) technology matures, more applications are being explored by U.S. Geological Survey (USGS) scientists throughout the Nation, both in collaboration with other Federal agencies and alone in support of USGS natural-hazards research (Crane et al., 2004). As the technology continues to improve and evolve, USGS scientists are finding new and unique methods to use and represent high-resolution lidar data, and new ways to make these data and derived information publicly available. Different lidar sensors and configurations have offered opportunities to use high-resolution elevation data for a variety of projects across all disciplines of the USGS. The following examples are just a few of the diverse projects in the USGS where lidar data is being used.

Photogrammetric Engineering and Remote Sensing