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At least 577 records · Page 32Linked to original sources
USGS2017

Pathogenic lineage of Perkinsea associated with mass mortality of frogs across the United States

Emerging infectious diseases such as chytridiomycosis and ranavirus infections are important contributors to the worldwide decline of amphibian populations. We reviewed data on 247 anuran mortality events in 43 States of the United States from 1999–2015. Our findings suggest that a severe infectious disease of tadpoles caused by a protist belonging to the phylum Perkinsea might represent the third most common infectious disease of anurans after ranavirus infections and chytridiomycosis. Severe Perkinsea infections (SPI) were systemic and led to multiorganic failure and death. The SPI mortality events affected numerous anuran species and occurred over a broad geographic area, from boreal to subtropical habitats. Livers from all PCR-tested SPI-tadpoles (n = 19) were positive for the Novel Alveolate Group 01 (NAG01) of Perkinsea, while only 2.5% histologically normal tadpole livers tested positive (2/81), suggesting that subclinical infections are uncommon. Phylogenetic analysis demonstrated that SPI is associated with a phylogenetically distinct clade of NAG01 Perkinsea. These data suggest that this virulent Perkinsea clade is an important pathogen of frogs in the United States. Given its association with mortality events and tendency to be overlooked, the potential role of this emerging pathogen in amphibian declines on a broad geographic scale warrants further investigation.

Scientific Reports↗
USGS2013

Wildlife connectivity approaches and best practices in U.S. state wildlife action plans

As habitat loss and fragmentation threaten biodiversity on large geographic scales, creating and maintaining connectivity of wildlife populations is an increasingly common conservation objective. To assess the progress and success of large-scale connectivity planning, conservation researchers need a set of plans that cover large geographic areas and can be analyzed as a single data set. The state wildlife action plans (SWAPs) fulfill these requirements. We examined 50 SWAPs to determine the extent to which wildlife connectivity planning, via linkages, is emphasized nationally. We defined linkage as connective land that enables wildlife movement. For our content analysis, we identified and quantified 6 keywords and 7 content criteria that ranged in specificity and were related to linkages for wide-ranging terrestrial vertebrates and examined relations between content criteria and statewide data on focal wide-ranging species, spending, revenue, and conserved land. Our results reflect nationwide disparities in linkage conservation priorities and highlight the continued need for wildlife linkage planning. Only 30% or less of the 50 SWAPs fulfilled highly specific content criteria (e.g., identifying geographic areas for linkage placement or management). We found positive correlations between our content criteria and statewide data on percent conserved land, total focal species, and spending on parks and recreation. We supplemented our content analysis with interviews with 17 conservation professionals to gain specific information about state-specific context and future directions of linkage conservation. Based on our results, relevant literature, and interview responses, we suggest the following best practices for wildlife linkage conservation plans: collect ecologically meaningful background data; be specific; establish community-wide partnerships; and incorporate sociopolitical and socioeconomic information.

Conservation Biology↗
USGS1998

Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore

Prior research developed a cellular automaton model, that was calibrated by using historical digital maps of urban areas and can be used to predict the future extent of an urban area. The model has now been applied to two rapidly growing, but remarkably different urban areas: the San Francisco Bay region in California and the Washington/Baltimore corridor in the Eastern United States. This paper presents the calibration and prediction results for both regions, reviews their data requirements, compares the differences in the initial configurations and control parameters for the model in the two settings, and discusses the role of GIS in the applications. The model has generated some long term predictions that appear useful for urban planning and are consistent with results from other models and observations of growth. Although the GIS was only loosely coupled with the model, the model's provision of future urban patterns as data layers for GIS description and analysis is an important outcome of this type of calculation.

California, Maryland↗
USGS2008

Using logistic regression to predict a probability of debris flows in areas burned by wildfires, southern California, 2003-2006

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

California↗
USGS2003

A geographic information system tool to solve regression equations and estimate flow-frequency characteristics of Vermont Streams

Estimates of the magnitude and frequency of streamflow are needed to safely and economically design bridges, culverts, and other structures in or near streams. These estimates also are used for managing floodplains, identifying flood-hazard areas, and establishing flood-insurance rates, but may be required at ungaged sites where no observed flood data are available for streamflow-frequency analysis. This report describes equations for estimating flow-frequency characteristics at ungaged, unregulated streams in Vermont. In the past, regression equations developed to estimate streamflow statistics required users to spend hours manually measuring basin characteristics for the stream site of interest. This report also describes the accompanying customized geographic information system (GIS) tool that automates the measurement of basin characteristics and calculation of corresponding flow statistics. The tool includes software that computes the accuracy of the results and adjustments for expected probability and for streamflow data of a nearby stream-gaging station that is either upstream or downstream and within 50 percent of the drainage area of the site where the flow-frequency characteristics are being estimated. The custom GIS can be linked to the National Flood Frequency program, adding the ability to plot peak-flow-frequency curves and synthetic hydrographs and to compute adjustments for urbanization.

Vermont↗
USGS2003

A temporal study of urban development for the municipality of Anchorage, Alaska

A land use/land cover database was produced for a portion of the Municipality of Anchorage, Alaska to document the temporal and spatial extent of urbanization to assist in the analysis of changes in impervious cover and water quality. Data were derived from black and white and color infrared aerial photography, and satellite imagery from the early 1970's to 2000 in roughly ten‐year increments. Aerial photographs and satellite data were manually interpreted to identify and map land use/land cover classes which were then entered into a geographic information system, attributed, and georeferenced to a U.S. Geological Survey topographic map base. The spatial extent of the study was 31,117 hectares. In the early 1970's, approximately 7,356 hectares (24%) of the study area were mapped as urban developed. During the 30‐year analysis period, the largest increase in urban development occurred between the late 1970's and early 1980's when urban area increased to 12,263 hectares (39%). Between 1980 and 1990, and 1990 and 2000, urban area increased to 12,762 hectares (41%), and 13,980 hectares (45%) respectively. Most development occurred in forested or tall shrub areas, although some also occurred in wetlands. Between 1970 and 2000, close to 1,300 hectares of wetlands were lost due to development. Contrary to this, the amount of lake and pond area increased slightly from 261 hectares in 1973 to 334 hectares in 1980, and reduced to 310 hectares by 2000. The increase was primarily due to the filling in of gravel pits with spring melt water.

Alasak↗
USGS2019

The past and future roles of competition and habitat in the range‐wide occupancy dynamics of Northern Spotted Owls

Slow ecological processes challenge conservation. Short‐term variability can obscure the importance of slower processes that may ultimately determine the state of a system. Furthermore, management actions with slow responses can be hard to justify. One response to slow processes is to explicitly concentrate analysis on state dynamics. Here, we focus on identifying drivers of Northern Spotted Owl ( Strix occidentalis caurina ) territorial occupancy dynamics across 11 study areas spanning their geographic range and forecasting response to potential management actions. Competition with Barred Owls ( Strix varia ) has increased Spotted Owl territory extinction probabilities across all study areas and driven recent declines in Spotted Owl populations. Without management intervention, the Northern Spotted Owl subspecies will be extirpated from parts of its current range within decades. In the short term, Barred Owl removal can be effective. Over longer time spans, however, maintaining or improving habitat conditions can help promote the persistence of northern spotted owl populations. In most study areas, habitat effects on expected Northern Spotted Owl territorial occupancy are actually greater than the effects of competition from Barred Owls. This study suggests how intensive management actions (removal of a competitor) with rapid results can complement a slower management action (i.e., promoting forest succession).

Ecological Applications↗
USGS2002

Assessing state-wide biodiversity in the Florida Gap analysis project

The Florida Gap (FI-Gap) project provides an assessment of the degree to which native animal species and natural communities are or are not represented in existing conservation lands. Those species and communities not adequately represented in areas being managed for native species constitute 'gaps' in the existing network of conservation lands. The United States Geological Survey Gap Analysis Program is a national effort and so, eventually, all 50 states will have completed it. The objective of FI-Gap was to provide broad geographic information on the status of terrestrial vertebrates, butterflies, skippers and ants and their respective habitats to address the loss of biological diversity. To model the distributions and potential habitat of all terrestrial species of mammals, breeding birds, reptiles, amphibians, butterflies, skippers and ants in Florida, natural land cover was mapped to the level of dominant or co-dominant plant species. Land cover was classified from Landsat Thematic Mapper (TM) satellite imagery and auxiliary data such as the national wetlands inventory (NWI), soils maps, aerial imagery, existing land use/land cover maps, and on-the-ground surveys, Wildlife distribution models were produced by identifying suitable habitat for each species within that species' range, Mammalian models also assessed a minimum critical area required for sustainability of the species' population. Wildlife species richness was summarized against land stewardship ranked by an area's mandates for conservation protection. ?? 2002 Elsevier Science Ltd. All rights reserved.

Journal of Environmental Management↗
USGS2013

Genetic population structure of muskellunge in the Great Lakes

We quantified genetic relationships among Muskellunge Esox masquinongy from 15 locations in the Great Lakes to determine the extent and distribution of measurable population structure and to identify appropriate spatial scales for fishery management and genetic conservation. We hypothesized that Muskellunge from each area represented genetically distinct populations, which would be evident from analyses of genotype data. A total of 691 Muskellunge were sampled ( n = 10–127/site) and genetic data were collected at 13 microsatellite loci. Results from a suite of analyses (including pairwise genetic differentiation, Bayesian admixture prediction, analysis of molecular variance, and tests of isolation by distance) indicated the presence of nine distinct genetic groups, including two that were approximately 50 km apart. Geographic proximity and low habitat complexity seemed to facilitate genetic similarity among areas, whereas Muskellunge from areas of greater habitat heterogeneity exhibited high differentiation. Muskellunge from most areas contained private alleles, and mean within-area genetic variation was similar to that reported for other freshwater fishes. Management programs aimed at conserving the broader diversity and long-term sustainability of Muskellunge could benefit by considering the genetically distinct groups as independent fisheries, and individual spawning and nursery habitats could subsequently be protected to conserve the evolutionary potential of Muskellunge.

Great Lakes↗
USGS2007

Application of GPS and GIS to map channel features in Walnut Creek, Iowa

A 12-km reach of Walnut Creek was mapped at the Neal Smith National Wildlife Refuge in Jasper County, Iowa to identify and prioritize areas of the stream channel in need of further investigation or restoration. Channel features, including streambank conditions, bottom sediment materials and thickness, channel cross-sections, debris dams, tile lines, tributary creeks, and cattle access points, were located to one-meter accuracy with global positioning system (GPS) equipment and described while traversing the stream. The GPS data were exported into a Geographic Information System (GIS) format, and field descriptions were added to create a series of coverages. Channel features were coupled with existing land cover data for analysis. Left and right streambank erosion rates varied from slight in many areas to severe at outside meander bends, debris dams or cattle access points. Erosion estimates from this study suggest that stream banks contribute about 50 percent of the annual suspended sediment load in the channel. Substrate materials varied from bare or thinly mantled pre-Illinoian till to thick silty muck (> 0.3 m) behind some debris dams and cattle access points. Occurrences of sand and gravel areas were generally restricted to cattle access areas and bridge crossings. A total of 81 debris dams were identified in the stream channel, ranging from fallen trees and beaver dams to several large debris dams. Numerous tile lines (52 total) and tributary creeks (45 total) were mapped as contributing flow to the main channel. Cross-sections measured at 34 locations indicated Walnut Creek averages 10.64 m wide and 2.77 m deep, with the width and depth increasing downstream. Channelization and tile discharge in row crop land use areas have contributed to increased bed degradation and channel widening throughout the watershed. The results of this study indicate the effectiveness of a one-time detailed mapping program to characterize stream system variability and identify spatial relationships among many stream characteristics. Stream survey data are being used to model watershed conditions, identify water sampling points and evaluate and select appropriate channel rehabilitation measures.

Iowa↗
USGS2015

NLEAP/GIS approach for identifying and mitigating regional nitrate-nitrogen leaching

Improved simulation-based methodology is needed to help identify broad geographical areas where potential NO 3 -N leaching may be occurring from agriculture and suggest management alternatives that minimize the problem. The Nitrate Leaching and Economic Analysis Package (NLEAP) model was applied to estimate regional NO 3 -N leaching in eastern Colorado. Results show that a combined NLEAP/GIS technology can be used to identify potential NO 3 -N hot spots in shallow alluvial aquifers under irrigated agriculture. The NLEAP NO 3 -N Leached (NL) index provided the most promising single index followed by NO 3 -N Available for Leaching (NAL). The same combined technology also shows promise in identifying Best Management Practice (BMP) methods that help minimize NO 3 -N leaching in vulnerable areas. Future plans call for linkage of the NLEAP/GIS procedures with groundwater modeling to establish a mechanistic analysis of agriculture-aquifer interactions at a regional scale.

Book chapter↗
USGS2005

A spatial model of potential jaguar habitat in Arizona

The jaguar (Panthera onca) is an endangered species that occasionally visits the southwestern United States from Mexico. The number of jaguar sightings per decade has declined over the last 100 years in Arizona, USA, raising conservation concerns for the species at a local and national level. In 1997, state, federal, and local governments with land-management responsibilities agreed to characterize and identify potential jaguar habitat in Arizona and New Mexico. Specifically, the objectives of our analysis were 2-fold: (1) characterize potential jaguar habitat in Arizona from historic sighting records and (2) create a statewide habitat suitability map. We used a Geographic Information System (GIS) to characterize potential jaguar habitat by overlaying historic jaguar sightings (25) on landscape and habitat features believed important (e.g., vegetation biomes and series, elevation, terrain ruggedness, proximity to perennial or intermittent water sources, human density). The amount of Arizona (%) identified as potential jaguar habitat ranged from 21% to 30% depending on the input variables. Most jaguar sightings were in scrub grasslands between 1,220 and 1,829-m elevation in southeastern Arizona, in intermediately to extremely rugged terrain, and within 10 km of a water source. Conservation efforts should focus on protecting the most suitable jaguar habitat in southeastern Arizona (i.e., Santa Cruz, Pima, Cochise, Pinal, Graham counties), travel corridors within and outside Arizona, and jaguar habitat in the Sierra Madres of Sonora, Mexico.

Journal of Wildlife Management↗
USGS1997

AVHRR imagery used to identify hurricane damage in a forested wetland of Louisiana

Certain events provide a unique opportunity to test the monitoring capability of AVHBR imagery. On 26 August 1992, Hurricane Andrew passed through Louisiana, impacting a large area of forested wetlands. One response to the widespread defoliation resulting from the hurricane impact was an abnormal bloom of new leaves and new growth in the underlying vegetation between September and October. To capture this atypical phenology, a time sequence of AVHRR images was transformed into a normalized difference vegetation index, NDVI, as an indicator of vegetation changes in the forest impacted by the passage of a hurricane. Using geographic information system functions, three sites in the impacted forest were vectorized as polygons, and the inclusive pixels were extracted for subsequent graphical and univariate statistical analysis. Temporal curves of mean NDVIs for the three sites for before, during, and after the hurricane passage, and aggregate curves of the impacted forest to an undisturbed forest, were compared. These comparisons corroborated the atypical phenology of the impacted forested wetland and directly related the cause to the hurricane passage.

Louisiana↗
USGS2010

Summary and statistical analysis of precipitation and groundwater data for Brunswick County, North Carolina, Water Year 2008

Groundwater conditions in Brunswick County, North Carolina, have been monitored continuously since 2000 through the operation and maintenance of groundwater-level observation wells in the surficial, Castle Hayne, and Peedee aquifers of the North Atlantic Coastal Plain aquifer system. Groundwater-resource conditions for the Brunswick County area were evaluated by relating the normal range (25th to 75th percentile) monthly mean groundwater-level and precipitation data for water years 2001 to 2008 to median monthly mean groundwater levels and monthly sum of daily precipitation for water year 2008. Summaries of precipitation and groundwater conditions for the Brunswick County area and hydrographs and statistics of continuous groundwater levels collected during the 2008 water year are presented in this report. Groundwater levels varied by aquifer and geographic location within Brunswick County, but were influenced by drought conditions and groundwater withdrawals. Water levels were normal in two of the eight observation wells and below normal in the remaining six wells. Seasonal Kendall trend analysis performed on more than 9 years of monthly mean groundwater-level data collected in an observation well located within the Brunswick County well field indicated there is a strong downward trend, with water levels declining at a rate of about 2.2 feet per year.

North Carolina↗
USGS2008

Characteristics and Classification of Least Altered Streamflows in Massachusetts

Streamflow records from 85 streamflow-gaging stations at which streamflows were considered to be least altered were used to characterize natural streamflows within southern New England. Period-of-record streamflow data were used to determine annual hydrographs of median monthly flows. The shapes and magnitudes of annual hydrographs of median monthly flows, normalized by drainage area, differed among stations in different geographic areas of southern New England. These differences were gradational across southern New England and were attributed to differences in basin and climate characteristics. Period-of-record streamflow data were also used to analyze the statistical properties of daily streamflows at 61 stations across southern New England by using L-moment ratios. An L-moment ratio diagram of L-skewness and L-kurtosis showed a continuous gradation in these properties between stations and indicated differences between base-flow dominated and runoff-dominated rivers. Streamflow records from a concurrent period (1960-2004) for 61 stations were used in a multivariate statistical analysis to develop a hydrologic classification of rivers in southern New England. Missing records from 46 of these stations were extended by using a Maintenance of Variation Extension technique. The concurrent-period streamflows were used in the Indicators of Hydrologic Alteration and Hydrologic Index Tool programs to determine 224 hydrologic indices for the 61 stations. Principal-components analysis (PCA) was used to reduce the number of hydrologic indices to 20 that provided nonredundant information. The PCA also indicated that the major patterns of variability in the dataset are related to differences in flow variability and low-flow magnitude among the stations. Hierarchical cluster analysis was used to classify stations into groups with similar hydrologic properties. The cluster analysis classified rivers in southern New England into two broad groups: (1) base-flow dominated rivers, whose statistical properties indicated less flow variability and high magnitudes of low flow, and (2) runoff-dominated rivers, whose statistical properties indicated greater flow variability and lower magnitudes of low flow. A four-cluster classification further classified the runoff-dominated streams into three groups that varied in gradient, elevation, and differences in winter streamflow conditions: high-gradient runoff-dominated rivers, northern runoff-dominated rivers, and southern runoff-dominated rivers. A nine-cluster division indicated that basin size also becomes a distinguishing factor among basins at finer levels of classification. Smaller basins (less than 10 square miles) were classified into different groups than larger basins. A comparison of station classifications indicated that a classification based on multiple hydrologic indices that represent different aspects of the flow regime did not result in the same classification of stations as a classification based on a single type of statistic such as a monthly median. River basins identified by the cluster analysis as having similar hydrologic properties tended to have similar basin and climate characteristics and to be in close proximity to one another. Stations were not classified in the same cluster on the basis of geographic location alone; as a result, boundaries cannot be drawn between geographic regions with similar streamflow characteristics. Rivers with different basin and climate characteristics were classified in different clusters, even if they were in adjacent basins or upstream and downstream within the same basin.

Scientific Investigations Report↗
USGS2017

Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

The distribution and abundance of pinyon ( Pinus monophylla ) and juniper ( Juniperus osteosperma, J. occidentalis ) trees (hereinafter, "pinyon-juniper") in sagebrush ( Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes . Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst ™ . This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC , including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

California, Nevada↗
USGS2024

Quantitative risk of earthquake disruption to global copper and rhenium supply

Earthquakes have the potential to substantially affect mining operations, potentially leading to supply chain disruptions and adversely affecting the global economy. This study explores the quantification of earthquake risk to copper and rhenium commodity supply by examining the spatial concentration of high earthquake hazard areas and the commodity-specific mining, smelting, and refining operations across the globe. Because many of the largest facilities are concentrated geographically near the highly seismic regions of South America, East Asia, and the Pacific, there is a potential for cascading effects on the entire supply chain. The analysis indicates that the expected annual disruption of global production is 0.3–1.1 percent for copper mines, 1.8–4.0 percent for smelters, and 1.5–3.3 percent for refineries. Expected annual disruption of global rhenium production capacity is 0.32–1.32 percent. The research highlights that the potential lost revenue from earthquake disruptions is from $315 million to $1.29 billion for copper mining, $1.92 billion to $4.33 billion for copper smelting, $2.06 billion to $4.52 billion for copper refining, and $337,000 to $1.40 million for rhenium production capacity.

Open-File Report↗
USGS1998

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate (NO2+NO3-N) in ground water in the Idaho part of the upper Snake River basin

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, cyanazine, metolachlor, and simazine. This study developed maps that the Idaho State Department of Agriculture might use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in the Idaho part of the upper Snake River Basin. These maps can be incorporated in the State Pesticide Management Plan and help provide a sound hydrogeologic basis for atrazine management in the study area. Maps showing the probability of detecting atrazine/desethyl-atrazine in ground water were developed as follows: (1) Ground-water monitoring data were overlaid with hydrogeologic and anthropogenic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, depth to ground water, geology, land use, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Individual (univariate) relations between atrazine/desethyl-atrazine in ground water and atrazine use, depth to ground water, geology, land use, precipitation, soils, and well depth data were evaluated to identify those independent variables significantly related to atrazine/ desethyl-atrazine detections. (3) Several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models which best predicted the presence of atrazine/desethyl-atrazine in ground water were selected. (5) The multivariate models were entered into the geographic information system and the probability maps were constructed. Two models which best predicted the presence of atrazine/desethyl-atrazine in ground water were selected; one with and one without atrazine use. Correlations of the predicted probabilities of atrazine/desethyl-atrazine in ground water with the percent of actual detections were good; r-squared values were 0.91 and 0.96, respectively. Models were verified using a second set of groundwater quality data. Verification showed that wells with water containing atrazine/desethyl-atrazine had significantly higher probability ratings than wells with water containing no atrazine/desethylatrazine (p <0.002). Logistic regression also was used to develop a preliminary model to predict the probability of nitrite plus nitrate as nitrogen concentrations greater than background levels of 2 milligrams per liter. A direct comparison between the atrazine/ desethyl-atrazine and nitrite plus nitrate as nitrogen probability maps was possible because the same ground-water monitoring, hydrogeologic, and anthropogenic data were used to develop both maps. Land use, precipitation, soil hydrologic group, and well depth were significantly related with atrazine/desethyl-atrazine detections. Depth to water, land use, and soil drainage were signifi- cantly related with elevated nitrite plus nitrate as nitrogen concentrations. The differences between atrazine/desethyl-atrazine and nitrite plus nitrate as nitrogen relations were attributed to differences in chemical behavior of these compounds in the environment and possibly to differences in the extent of use and rates of their application.

Idaho↗